# templates

name: Automatic monitoring of multiple URLs with downtime alerts
author_name: Oriol Seguí
author_username: oxsr11
categories: []
created_at: 2025-06-25T11:31:26.471Z
updated_at: 2025-06-25T11:31:26.471Z
url: https://n8n.io/workflows/5298
scraped_at: 2025-07-06 21:16:30
description:
  This n8n workflow allows you to automatically monitor the status of multiple URLs in a simple and efficient way. You just need to enter the URLs you want to scan and run the workflow (either manually or scheduled). For each URL, an availability check is performed. The results are logged in a Google Sheet, clearly distinguishing between successful checks and failures (downtime). If any URL fails, the system filters these errors and automatically sends an email alert notifying you of the detected outages.

  The workflow includes help messages in both English and Spanish, integrates with Google Sheets and Gmail, and is suitable for both one-off tasks and scheduled monitoring.

  For Who?
  Webmasters
  SEO & Marketing Teams
  SysAdmins
  Anyone needing automated website uptime monitoring

  How it works?
  Enter the URLs to scan in the “URLs” field.
  Trigger the workflow manually or schedule it to run automatically.
  For each URL, the workflow:
  Checks if the URL is online or down.
  Logs the status (success or error) in a Google Sheet.
  At the end, filters the failed URLs (crashes) and sends an email alert l

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.gmail","n8n-nodes-base.code"]

workflow_json:
  {"meta":{"instanceId":"b643a27a3e5d7748d41ee6285fc688ed2cbf9a93ddb8d5b0ae79684ac7064b2b","templateCredsSetupCompleted":true},"nodes":[{"id":"2744df51-ca51-4c01-9a49-b29c5b27f7bf","name":"Schedule Trigger","type":"n8n-nodes-base.scheduleTrigger","position":[0,200],"parameters":{"rule":{"interval":[{}]}},"typeVersion":1.2},{"id":"cae73f18-028e-4cb5-aee2-a18768c5367e","name":"Split Out","type":"n8n-nodes-base.splitOut","position":[480,100],"parameters":{"options":{},"fieldToSplitOut":"urls"},"typeVersion":1},{"id":"398d41cf-c555-44d7-bf08-2732a47a18e7","name":"URLs","type":"n8n-nodes-base.set","position":[260,100],"parameters":{"mode":"raw","options":{},"jsonOutput":"{\n  \"urls\": {\n    \"URL 2\": \"https://example.com\",\n    \"URL 1\": \"https://google.es\",\n    \"URL 4\": \"https://github.com\",\n    \"URL 3\": \"https://n8n.io\",\n    \"URL 5\": \"https://n8niouou.io\",\n    \"URL 6\": \"https://n8niopuou.io\"\n  }\n}"},"typeVersion":3.4},{"id":"876e4ca3-c607-4443-a4ec-cb83fe84e6c3","name":"Success","type":"n8n-nodes-base.googleSheets","position":[1220,260],"parameters":{"columns":{"value":{"Caida":"=","Funcional":"=Funciona: {{ $('Split Out').item.json.urls }}"},"schema":[{"id":"Funcional","type":"string","display":true,"required":false,"displayName":"Funcional","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Caida","type":"string","display":true,"required":false,"displayName":"Caida","defaultMatch":false,"canBeUsedToMatch":true}],"mappingMode":"defineBelow","matchingColumns":[],"attemptToConvertTypes":false,"convertFieldsToString":false},"options":{},"operation":"append","sheetName":{"__rl":true,"mode":"list","value":"gid=0","cachedResultUrl":"https://docs.google.com/spreadsheets/d/13EHjUGc0wHYbBYZFPqlGuSE1pnttvokU1y3gJCWz920/edit#gid=0","cachedResultName":"Hoja 1"},"documentId":{"__rl":true,"mode":"list","value":"13EHjUGc0wHYbBYZFPqlGuSE1pnttvokU1y3gJCWz920","cachedResultUrl":"https://docs.google.com/spreadsheets/d/13EHjUGc0wHYbBYZFPqlGuSE1pnttvokU1y3gJCWz920/edit?usp=drivesdk","cachedResultName":"Prova2"}},"credentials":{"googleSheetsOAuth2Api":{"id":"nnznbiLx5YNRZzDM","name":"Google Sheets account"}},"typeVersion":4.6},{"id":"c99e1ec7-0b11-4278-8f97-d6b9cef798cd","name":"Error","type":"n8n-nodes-base.googleSheets","position":[1220,460],"parameters":{"columns":{"value":{"Caida":"=Caida: {{ $json.urls }}"},"schema":[{"id":"Funcional","type":"string","display":true,"required":false,"displayName":"Funcional","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Caida","type":"string","display":true,"required":false,"displayName":"Caida","defaultMatch":false,"canBeUsedToMatch":true}],"mappingMode":"defineBelow","matchingColumns":[],"attemptToConvertTypes":false,"convertFieldsToString":false},"options":{},"operation":"append","sheetName":{"__rl":true,"mode":"list","value":"gid=0","cachedResultUrl":"https://docs.google.com/spreadsheets/d/13EHjUGc0wHYbBYZFPqlGuSE1pnttvokU1y3gJCWz920/edit#gid=0","cachedResultName":"Hoja 1"},"documentId":{"__rl":true,"mode":"list","value":"13EHjUGc0wHYbBYZFPqlGuSE1pnttvokU1y3gJCWz920","cachedResultUrl":"https://docs.google.com/spreadsheets/d/13EHjUGc0wHYbBYZFPqlGuSE1pnttvokU1y3gJCWz920/edit?usp=drivesdk","cachedResultName":"Prova2"}},"credentials":{"googleSheetsOAuth2Api":{"id":"nnznbiLx5YNRZzDM","name":"Google Sheets account"}},"typeVersion":4.6},{"id":"9aeec8f1-1498-4381-bfab-a76c8e40a862","name":"Total","type":"n8n-nodes-base.summarize","position":[960,20],"parameters":{"options":{},"fieldsToSummarize":{"values":[{"field":"Caida"},{"field":"Funcional"}]}},"typeVersion":1.1},{"id":"01fd1dbc-ca4c-4a94-abbc-e1d67a7dd775","name":"Bucle URLs","type":"n8n-nodes-base.splitInBatches","position":[700,100],"parameters":{"options":{}},"typeVersion":3},{"id":"760cea59-8d84-4abf-b91a-c277ca122420","name":"Run trigger","type":"n8n-nodes-base.manualTrigger","position":[0,0],"parameters":{},"typeVersion":1},{"id":"1ec7a4ea-e929-4f50-b4b8-4732b9e439ed","name":"Send a message","type":"n8n-nodes-base.gmail","position":[1560,20],"webhookId":"cf566774-8539-422c-8129-7c9fea6b367c","parameters":{"sendTo":"email@youemail.com","message":"=Te informamos que actualmente estos URLs se encuentran caídos: \n\n{{ $json.url }}\n\n\nCaídos: {{ $('Total').item.json.count_Caida }}\n\nFuncionales: {{ $('Total').item.json.count_Funcional }}","options":{},"subject":"Webs caídas"},"credentials":{"gmailOAuth2":{"id":"ED5PJ0BhFPmKkgyc","name":"Gmail account"}},"typeVersion":2.1},{"id":"e6ca120c-21e0-42c5-b3d0-c8e447e09386","name":"Code","type":"n8n-nodes-base.code","position":[1160,20],"parameters":{"jsCode":"// 1) Traemos TODOS los ítems que generó el nodo \"Bucle URLs\"\nconst items = $items('Bucle URLs');   // respeta exactamente el nombre del nodo\n\n// 2) Extraemos la propiedad Caida y descartamos vacíos\nconst caidaUrls = items\n  .map(it => it.json.Caida)               \n  .filter(url => typeof url === 'string' && url.trim().length);\n\nif (caidaUrls.length === 0) {\n  throw new Error('No se encontraron URLs en la propiedad \"Caida\".');\n}\n\nreturn caidaUrls.map(url => ({ json: { url } }));\n\n/*  Si prefieres un ÚNICO item con el array completo, comenta la línea anterior\n    y descomenta esto:\nreturn [\n  { json: { caidaUrls } },     // { \"caidaUrls\": [\"https://n8niouou.io\", \"https://n8niopuou.io\"] }\n];\n*/\n"},"typeVersion":2},{"id":"d5fb83e9-689f-44f3-a02a-32ff511c9ee0","name":"Split Out2","type":"n8n-nodes-base.splitOut","position":[1360,20],"parameters":{"options":{},"fieldToSplitOut":"url"},"typeVersion":1},{"id":"464a16ea-17f0-4757-b491-1b331395cd14","name":"Request","type":"n8n-nodes-base.httpRequest","onError":"continueErrorOutput","position":[960,220],"parameters":{"url":"={{ $json.urls }}","options":{}},"typeVersion":4.2},{"id":"5df0c197-037d-46da-bc4b-fd7ed514bbe5","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[220,320],"parameters":{"color":5,"width":260,"content":"## How it works (P1)\nBefore the loop, you enter the URLs to scan in the \"URLs\" stream, then start the trigger either manually or scheduled."},"typeVersion":1},{"id":"8e2d7f73-8731-4b35-8fb0-10d68978a671","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[220,500],"parameters":{"color":5,"width":260,"height":180,"content":"## Cómo funciona (P1)\n\nAntes del bucle, se introducen las URL que se escanearán en el flujo \"URL\" y, a continuación, se inicia el disparador, ya sea de forma manual o programada."},"typeVersion":1},{"id":"4367f7ee-0b74-476b-84b4-202bc3d909e7","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[1440,240],"parameters":{"width":260,"height":180,"content":"## How it works (P2)\nStart a loop for each URL entered, adding the status to a Google Sheet, then collect the status of each URL, filter out the crashes, and send an email with the crashes."},"typeVersion":1},{"id":"466863c5-a256-499c-b457-4651de2bb8fc","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[1440,460],"parameters":{"width":260,"height":180,"content":"## Cómo funciona (P2)\nInicia un bucle por cada URL introducida, agregando el estado en google sheet, luego recoge el estado de cada URL, filtra las caídas y envía un email con las caídas."},"typeVersion":1},{"id":"4cb90ac4-9808-413a-8fb0-c7ed0db631bb","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[220,40],"parameters":{"color":5,"width":180,"height":220,"content":"### Enter URLs to scan here"},"typeVersion":1},{"id":"040739ca-50d8-4d77-bf3a-c7406bd60410","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[-40,-120],"parameters":{"color":5,"width":180,"height":480,"content":"### As a trigger you could also implement webhook or MCP"},"typeVersion":1}],"pinData":{},"connections":{"Code":{"main":[[{"node":"Split Out2","type":"main","index":0}]]},"URLs":{"main":[[{"node":"Split Out","type":"main","index":0}]]},"Error":{"main":[[{"node":"Bucle URLs","type":"main","index":0}]]},"Total":{"main":[[{"node":"Code","type":"main","index":0}]]},"Request":{"main":[[{"node":"Success","type":"main","index":0}],[{"node":"Error","type":"main","index":0}]]},"Success":{"main":[[{"node":"Bucle URLs","type":"main","index":0}]]},"Split Out":{"main":[[{"node":"Bucle URLs","type":"main","index":0}]]},"Bucle URLs":{"main":[[{"node":"Total","type":"main","index":0}],[{"node":"Request","type":"main","index":0}]]},"Split Out2":{"main":[[{"node":"Send a message","type":"main","index":0}]]},"Run trigger":{"main":[[{"node":"URLs","type":"main","index":0}]]},"Send a message":{"main":[[]]},"Schedule Trigger":{"main":[[{"node":"URLs","type":"main","index":0}]]}}}


name: Google Search Console and Analytics Analysis with AI Optimizations
author_name: Łukasz
author_username: lukaszpp
categories: []
created_at: 2025-06-25T13:10:19.561Z
updated_at: 2025-06-25T13:10:19.561Z
url: https://n8n.io/workflows/5303
scraped_at: 2025-07-06 21:16:30
description:
  What Is This?

  This workflow is a comprehensive solution for automating website audits and optimizations, leveraging advanced technologies to boost SEO effectiveness and overall site performance.

  Who Is It For?

  Designed for SEO specialists, digital marketers, webmasters, and content teams, this workflow empowers anyone responsible for website performance to automate and scale their audit processes. Agencies managing multiple client sites, in-house SEO teams aiming to save time on routine checks, and developers seeking to integrate data-driven insights into their deployment pipelines will all find this solution invaluable.

  By combining your site’s sitemap with Google Search Console and Google Analytics data, then applying AI-powered analysis, the workflow continuously uncovers actionable recommendations to boost search visibility, improve user engagement, and accelerate page performance. Whether you manage a single blog or oversee a sprawling e-commerce platform, this automated pipeline delivers precise, prioritized SEO improvements without manual data wrangling.

  How Does It Work?

  This end-to-end site analysis automation consists of five main stages:

  1. URL Discovery  
  Processes the sitemap.xml using HTTP Request and XML nodes to extract all site URLs.

  2. Search Console Performance Analysis  
  Uses the Google Search Console API to fetch detailed metrics for each page, including search position, clicks, impressions, and CTR. 

  3. Analytics Data Collection  
  Connects to the Google Analytics API to automatically retrieve traffic metrics such as pageviews, average session duration, bounce rate, and conversions. 

  4. AI Data Processing  
  Employs OpenAI models to perform in-depth analysis of the collected data. The artificial intelligence engine merges insights from all sources, identifies patterns, and produces detailed optimization recommendations. AI analyses website itsefl aswell. Consider testing different models. I do recommend at least trying out o4-mini.

  5. Recommendation Generation  
  Creates tailored suggestions for each page, in form of HTML table, that is being sent to your email.

  How To Set It Up?

  Accounts:  
  An active n8n account or instance, API keys for Google Search Console and Google Analytics, an OpenAI access token.

  Enabled Google APIs:
  You will neeed at least following scopes:
  Google Search Console API
  Google Analytics Aadmin API
  Google Analytics Data API 

  Scheduling:  
  The workflow can run manually for ad hoc audits or be scheduled (daily, weekly) for continuous site monitoring.

  Testing:  
  There are two nodes that are optional:
  "Sort for testing purposes" and
  "Limit for testing purposes"
  Together they randomly select items from sitemap and limit them to few so you don't need to run hundreds of sitemap.xml items at once, but you can run just a random batch first.

  Globals:
  There is node called "Globals- CHANGE ME!". You need to set up proper variables in there, which are:
  sitemap_url - self exlpainatory
  search_console_selector - for example "sc-domain:sailingbyte.com" but can be URL aswell- depends on how did you set up your search console
  analysis_start_date and analysis_end_date - date range for analytics, by default last 30 days
  analytics_selector_id - ID of Google Analytics setup, it is a large integer, you can find it in analytics url preceeded with letter "p", ex (your number is where there are X's): https://analytics.google.com/analytics/web/#/pXXXXXXXXX/reports/intelligenthome
  report_receiver - email which will receive report 

  What's More?

  That's actually it. I hope that this automation will help your website improvement will be much easier!

  Thank you, perfect!

  Glad I could help. Visit my profile for other automations for businesses. And if you are looking for dedicated software development, do not hesitate to reach out!

nodes_used:
  ["n8n-nodes-base.emailSend","n8n-nodes-base.httpRequest","n8n-nodes-base.googleAnalytics","n8n-nodes-base.html","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

workflow_json:
  {"id":"Q0fs6FhvxUSO5kL4","meta":{"instanceId":"bdce9ec27bbe2b742054f01d034b8b468d2e7758edd716403ad5bd4583a8f649","templateCredsSetupCompleted":true},"name":"Google Search Console and Analytics Analysis with AI Optimizations","tags":[],"nodes":[{"id":"4a4b478e-b5f8-4ddc-a6cc-48f1274cb5d6","name":"When clicking ‘Test workflow’","type":"n8n-nodes-base.manualTrigger","position":[-300,-300],"parameters":{},"typeVersion":1},{"id":"b52900dd-a2bd-42bb-8e1d-ce3cff259ec7","name":"Loop Over Items","type":"n8n-nodes-base.splitInBatches","position":[40,580],"parameters":{"options":{}},"typeVersion":3},{"id":"1ebe691b-6b76-4956-b181-c2be251d48be","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-40,480],"parameters":{"width":1620,"height":640,"content":"## Get Google Data and Push It Through AI"},"typeVersion":1},{"id":"7194a576-50ab-4df0-b6db-d6a74bcbb927","name":"Enforce Order - Positions Last","type":"n8n-nodes-base.merge","position":[280,260],"parameters":{"mode":"combine","options":{},"combineBy":"combineByPosition"},"typeVersion":3},{"id":"be892b2b-6141-415c-a503-d4f7d467cc6a","name":"Remove Duplicates","type":"n8n-nodes-base.removeDuplicates","position":[940,-60],"parameters":{"compare":"selectedFields","options":{},"fieldsToCompare":"loc"},"typeVersion":2},{"id":"ebb767ad-a8db-449a-8d52-56731248e9e5","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[240,-140],"parameters":{"width":880,"height":320,"content":"## Get All Pages From Sitemap"},"typeVersion":1},{"id":"d421db5a-c224-44ef-a471-d64ca8ddaa69","name":"Get sitemap XML","type":"n8n-nodes-base.httpRequest","position":[280,-60],"parameters":{"url":"={{ $('Globals - CHANGE ME!').item.json.sitemap_url }}","options":{}},"typeVersion":4.2},{"id":"6bf0e08e-1cfa-4484-b953-cd215447d053","name":"Convert to JSON","type":"n8n-nodes-base.xml","position":[500,-60],"parameters":{"options":{}},"typeVersion":1},{"id":"b5ab24fc-8c0f-4158-9452-35fc682246ff","name":"Split Out to Table","type":"n8n-nodes-base.splitOut","position":[720,-60],"parameters":{"options":{},"fieldToSplitOut":"urlset.url"},"typeVersion":1},{"id":"81c644b2-1de8-4f51-be73-ac2246fb3c5f","name":"Limit for Testing Purposes","type":"n8n-nodes-base.limit","position":[1400,-60],"parameters":{"maxItems":5},"typeVersion":1},{"id":"77c271b5-99b9-4adf-8b7f-7dc0846325bd","name":"Wait to Comply with API Limits","type":"n8n-nodes-base.wait","position":[900,500],"webhookId":"51b5aeba-6be7-45d4-97fd-4e5cb5a8401b","parameters":{"amount":1},"typeVersion":1.1},{"id":"00b83323-17ef-44a1-82b1-eb867e532556","name":"Globals - CHANGE ME!","type":"n8n-nodes-base.set","position":[40,-60],"parameters":{"options":{},"assignments":{"assignments":[{"id":"be81885f-3f27-4edd-985d-8dd98908a197","name":"sitemap_url","type":"string","value":"https://sailingbyte.com/sitemap.xml"},{"id":"c1f4c9ba-9222-4757-a89e-0d67af1d3944","name":"search_console_selector","type":"string","value":"sc-domain:example.com"},{"id":"9c57f9cc-1e94-4174-b622-7533c7776bee","name":"analysis_start_date","type":"string","value":"={{ $now.minus(30,'days').format('yyyy-MM-dd') }}"},{"id":"51dd8171-2300-4574-9c71-56793127bf4a","name":"analysis_end_date","type":"string","value":"={{ $now.format('yyyy-MM-dd') }}"},{"id":"5e09cf25-80d9-44fe-9cf3-e2517bcfc6e6","name":"analytics_selector_id","type":"number","value":0},{"id":"5befd844-afe6-44c9-8ecd-c2741d838b19","name":"report_receiver","type":"string","value":"email@eamil.com"}]}},"typeVersion":3.4},{"id":"cde1f4e7-f45d-4c64-906e-3b191550fc9a","name":"Get Page GSC Status","type":"n8n-nodes-base.httpRequest","onError":"continueRegularOutput","position":[280,560],"parameters":{"url":"https://searchconsole.googleapis.com/v1/urlInspection/index:inspect","method":"POST","options":{},"sendQuery":true,"authentication":"predefinedCredentialType","queryParameters":{"parameters":[{"name":"inspectionUrl","value":"={{ $json.loc }}"},{"name":"siteUrl","value":"={{ $('Globals - CHANGE ME!').first().json.search_console_selector }}"}]},"nodeCredentialType":"googleOAuth2Api"},"credentials":{"googleOAuth2Api":{"id":"wWLEdLgRqrkoJMke","name":"Google account"}},"retryOnFail":true,"typeVersion":4.2,"waitBetweenTries":5000},{"id":"c4856013-3111-4c04-b4d2-f92ad8f1cd88","name":"Get Page GSC Stats","type":"n8n-nodes-base.httpRequest","onError":"continueRegularOutput","position":[280,740],"parameters":{"url":"=https://www.googleapis.com/webmasters/v3/sites/{{ $('Globals - CHANGE ME!').first().json.search_console_selector }}/searchAnalytics/query","method":"POST","options":{},"jsonBody":"={\n  \"startDate\": \"{{ $('Globals - CHANGE ME!').first().json.analysis_start_date }}\",\n  \"endDate\": \"{{ $('Globals - CHANGE ME!').first().json.analysis_end_date }}\",\n  \"type\": \"web\",\n  \"dimensionFilterGroups\": [\n    {\n      \"groupType\": \"AND\",\n      \"filters\": [\n        {\n          \"dimension\": \"page\",\n          \"operator\": \"contains\",\n          \"expression\": \"{{ $json.loc }}\"\n        }\n      ]\n    }\n  ]\n}","sendBody":true,"specifyBody":"json","authentication":"predefinedCredentialType","nodeCredentialType":"googleOAuth2Api"},"credentials":{"googleOAuth2Api":{"id":"wWLEdLgRqrkoJMke","name":"Google account"}},"retryOnFail":true,"typeVersion":4.2,"waitBetweenTries":5000},{"id":"b5e8f02d-320c-4fab-9e38-2a6dbb97e7b1","name":"Merge Status and Stats","type":"n8n-nodes-base.merge","position":[540,680],"parameters":{"mode":"combine","options":{},"combineBy":"combineByPosition","numberInputs":3},"typeVersion":3.2},{"id":"c7ff4009-65be-4d4a-b3dd-f711e7cefebb","name":"OpenAI Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[660,880],"parameters":{"model":{"__rl":true,"mode":"list","value":"o4-mini","cachedResultName":"o4-mini"},"options":{}},"credentials":{"openAiApi":{"id":"zjIZQuuuZMJpiUny","name":"OpenAi account"}},"typeVersion":1.2},{"id":"133cbc78-a835-4d6c-a366-187d3f2ca4b1","name":"Get Google Analytics Data","type":"n8n-nodes-base.googleAnalytics","position":[280,920],"parameters":{"endDate":"={{ $('Globals - CHANGE ME!').first().json.analysis_end_date }}","dateRange":"custom","returnAll":true,"startDate":"={{ $('Globals - CHANGE ME!').first().json.analysis_start_date }}","metricsGA4":{"metricValues":[{},{"listName":"screenPageViews"},{"listName":"userEngagementDuration"}]},"propertyId":{"__rl":true,"mode":"id","value":"={{ $('Globals - CHANGE ME!').first().json.analytics_selector_id }}"},"dimensionsGA4":{"dimensionValues":[{"listName":"pageLocation"}]},"additionalFields":{"dimensionFiltersUI":{"filterExpressions":{"expression":{"stringFilter":[{"value":"={{ $json.loc }}","listName":"pageLocation","caseSensitive":false}]}}}}},"credentials":{"googleAnalyticsOAuth2":{"id":"4JVj7vMgAo09ILvS","name":"Google Analytics account"}},"typeVersion":2,"alwaysOutputData":true},{"id":"fc55254f-012b-4387-af4c-54211b386182","name":"HTTP Request","type":"n8n-nodes-base.httpRequestTool","position":[940,880],"parameters":{"url":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('URL', ``, 'string') }}","options":{},"toolDescription":"Make HTTP request to get page data so you can further analyze page for SEO optimizations"},"typeVersion":4.2},{"id":"3658c627-a22b-4f4c-b2ee-33e9a361bb1e","name":"Merge AI Output With AI Input","type":"n8n-nodes-base.merge","position":[1400,900],"parameters":{},"typeVersion":3.2},{"id":"b92d08c4-13a3-4c92-b37f-da3a7a5ee7dc","name":"Markdown to HTML","type":"n8n-nodes-base.markdown","position":[1120,900],"parameters":{"mode":"markdownToHtml","options":{},"markdown":"={{ $json.output }}","destinationKey":"output"},"typeVersion":1},{"id":"a77ef66d-1313-43ee-b23f-c23a24529026","name":"Keep Only Valuable Columns","type":"n8n-nodes-base.set","position":[500,260],"parameters":{"options":{"dotNotation":false,"ignoreConversionErrors":true},"assignments":{"assignments":[{"id":"6a86e547-b789-4319-886f-b06120967d64","name":"loc","type":"string","value":"={{ $json.loc }}"},{"id":"8ba00cd3-e45a-439f-b703-8a42dd0628fa","name":"inspectionResult.indexStatusResult.coverageState","type":"string","value":"={{ $json.inspectionResult.indexStatusResult.coverageState }}"},{"id":"b83dc435-cbb1-4dc3-8c7e-3af41201dbfe","name":"output","type":"string","value":"={{ $json.output }}"}]}},"typeVersion":3.4},{"id":"fad58242-29c7-4c48-ae3f-667559cfd644","name":"Change to HTML table for sending","type":"n8n-nodes-base.html","position":[720,260],"parameters":{"options":{},"operation":"convertToHtmlTable"},"typeVersion":1.2},{"id":"3d737f97-9d5c-4f0c-8a2a-cbe98e0879d2","name":"Send Email with Full report","type":"n8n-nodes-base.emailSend","position":[940,260],"webhookId":"843191c3-c853-43c1-9523-4661654fb58e","parameters":{"html":"=<h2>Analysis is complete</h2>\n{{ $json.table }}\n\n","options":{},"subject":"Your Analysis Is Complete","toEmail":"={{ $('Globals - CHANGE ME!').first().json['report_receiver'] }}","fromEmail":"={{ $('Globals - CHANGE ME!').first().json['report_receiver'] }}"},"credentials":{"smtp":{"id":"tkdzDgcUAt04af3B","name":"SMTP account"}},"typeVersion":2.1},{"id":"8888143f-73ed-4ac7-84ee-b5b4bcf64c6e","name":"Sort For Testing Purposes","type":"n8n-nodes-base.sort","position":[1180,-60],"parameters":{"type":"random"},"typeVersion":1},{"id":"fd4431b6-8a0a-4a2b-a70b-17d3fc2f34b5","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[1140,-140],"parameters":{"color":6,"width":440,"height":320,"content":"## Limit for Testing"},"typeVersion":1},{"id":"b821114e-234c-4183-a957-d5048f366ecd","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[-20,-140],"parameters":{"color":4,"height":320,"content":"## Setup Me First"},"typeVersion":1},{"id":"2e0a5df7-7dd1-4ca7-b9e7-763928b32913","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[240,200],"parameters":{"color":3,"width":1340,"height":260,"content":"## Get Email Report"},"typeVersion":1},{"id":"a16024d1-28a1-4b73-85b7-fc15e9620184","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[-420,-140],"parameters":{"color":4,"width":380,"height":320,"content":"- sitemap_url - self exlpainatory\n- search_console_selector - for example \"sc-domain:sailingbyte.com\" but can be URL aswell- depends on how did you set up your search console\n- analysis_start_date and analysis_end_date - date range for analytics, by default last 30 days\n- analytics_selector_id - ID of Google Analytics setup, it is a large integer, you can find it in analytics url preceeded with letter \"p\", ex (your number is where there are X's): https://analytics.google.com/analytics/web/#/pXXXXXXXXX/reports/intelligenthome\n- report_receiver - email which will receive report "},"typeVersion":1},{"id":"cd5d0d57-f04a-4094-8f26-855dd1051589","name":"SEO analyst","type":"@n8n/n8n-nodes-langchain.agent","position":[780,680],"parameters":{"text":"=You are professional SEO analyst and improver. You will receive in input data from Google Analytics and Google Search Console. Delivered data will be for single page.\n\nBased on this data, your task is to propose improvements, that are very specific to this page, and which will impact this web page positively. \n\nGeneral Data Evaluation:\n- How to get more users on this specific page\n- How to engage users more on this specific page\n- Analyze page itself for improvements\n- Look for potential issues in Google Analytics and Google Search Console data\n- Look for potential issues on website itself\n\nTechnical Evaluation:\n- Critical Fixes – Issues requiring immediate attention and resolution.\n- High-Impact Solutions – Simple adjustments that deliver significant results.\n- Enhancement Possibilities – Initiatives demanding greater investment but providing valuable long-term gains.\n\nContent Evaluation:\n- Keyword Strategy Assessment – Determine core and supporting search terms, evaluate keyword concentration levels, and examine strategic keyword positioning throughout the content.\n- Content Quality Review – Analyze the material's comprehensiveness, precision, and alignment with intended audience needs and expectations.\n- Accessibility and Clarity Analysis – Measure content comprehension difficulty through established readability frameworks including Flesch-Kincaid educational level, Flesch Reading Ease score, and Gunning-Fog complexity index.\n\nYou can add other improvement ideas, but they must be very specific to given page, no generalizations.\n\nWebsite is: {{ $json.pageLocation }}\n\nGoogle Analytics data is:\n- total users: {{ $json.totalUsers ?? 0}}\n- screen page views: {{ $json.screenPageViews ?? 0 }}\n- user engagement duration: {{ $json.userEngagementDuration ?? 0 }}\n\nGoogle Search Console data is:\n{{ $json.rows[0].toJsonString() }}\n\nIndexing status is as follows:\n{{ $json.inspectionResult.toJsonString() }}","options":{},"promptType":"define"},"typeVersion":2}],"active":false,"pinData":{},"settings":{"callerPolicy":"workflowsFromSameOwner","errorWorkflow":"5","executionOrder":"v1","saveManualExecutions":true,"saveDataSuccessExecution":"all"},"versionId":"dc23ed85-f60d-4a41-b7c1-19cd5ac272b4","connections":{"SEO analyst":{"main":[[{"node":"Markdown to HTML","type":"main","index":0}]]},"HTTP Request":{"ai_tool":[[{"node":"SEO analyst","type":"ai_tool","index":0}]]},"Convert to JSON":{"main":[[{"node":"Split Out to Table","type":"main","index":0}]]},"Get sitemap XML":{"main":[[{"node":"Convert to JSON","type":"main","index":0}]]},"Loop Over Items":{"main":[[{"node":"Enforce Order - Positions Last","type":"main","index":1}],[{"node":"Get Page GSC Status","type":"main","index":0},{"node":"Get Page GSC Stats","type":"main","index":0},{"node":"Get Google Analytics Data","type":"main","index":0}]]},"Markdown to HTML":{"main":[[{"node":"Merge AI Output With AI Input","type":"main","index":1}]]},"OpenAI Chat Model":{"ai_languageModel":[[{"node":"SEO analyst","type":"ai_languageModel","index":0}]]},"Remove Duplicates":{"main":[[{"node":"Sort For Testing Purposes","type":"main","index":0}]]},"Get Page GSC Stats":{"main":[[{"node":"Merge Status and Stats","type":"main","index":1}]]},"Split Out to Table":{"main":[[{"node":"Remove Duplicates","type":"main","index":0}]]},"Get Page GSC Status":{"main":[[{"node":"Merge Status and Stats","type":"main","index":0}]]},"Globals - CHANGE ME!":{"main":[[{"node":"Get sitemap XML","type":"main","index":0}]]},"Merge Status and Stats":{"main":[[{"node":"SEO analyst","type":"main","index":0},{"node":"Wait to Comply with API Limits","type":"main","index":0}]]},"Get Google Analytics Data":{"main":[[{"node":"Merge Status and Stats","type":"main","index":2}]]},"Sort For Testing Purposes":{"main":[[{"node":"Limit for Testing Purposes","type":"main","index":0}]]},"Keep Only Valuable Columns":{"main":[[{"node":"Change to HTML table for sending","type":"main","index":0}]]},"Limit for Testing Purposes":{"main":[[{"node":"Enforce Order - Positions Last","type":"main","index":0},{"node":"Loop Over Items","type":"main","index":0}]]},"Merge AI Output With AI Input":{"main":[[{"node":"Loop Over Items","type":"main","index":0}]]},"Enforce Order - Positions Last":{"main":[[{"node":"Keep Only Valuable Columns","type":"main","index":0}]]},"Wait to Comply with API Limits":{"main":[[{"node":"Merge AI Output With AI Input","type":"main","index":0}]]},"Change to HTML table for sending":{"main":[[{"node":"Send Email with Full report","type":"main","index":0}]]},"When clicking ‘Test workflow’":{"main":[[{"node":"Globals - CHANGE ME!","type":"main","index":0}]]}}}


name: Stock Market Daily Digest with Bright Data Scraping & Gemini AI Email Reports
author_name: Zacharia Kimotho
author_username: imperolq
categories: []
created_at: 2025-06-25T14:24:49.875Z
updated_at: 2025-06-25T14:24:49.875Z
url: https://n8n.io/workflows/5305
scraped_at: 2025-07-06 21:16:30
description:
  This workflow makes it easier to keep track of the stocks market and get an email with a summary of the daily highlights on what happened, key insights and trends 

  Setup Guide 

  Define the schedule (days, times, intervals).
  Replace sample stock data with your desired stock list (ticker, name, etc.) in JSON format.
  Split Out the fields to have a clean list of the stocks to monitor
  set keyword node Extracts the stock ticker from each item and sets it to the keyword property.
  Financial times scraper Triggers the Bright Data Datasets API to scrape financial data. Set the node as below

      Method: POST
      URL: https://api.brightdata.com/datasets/v3/trigger
      Query Parameters:
          dataset_id: Replace with your Bright Data dataset ID.
          include_errors: true
          type: discover_new
          discover_by: keyword
      Headers:
          Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Replace with your Bright Data API key.
      Body: JSON,  ={{ $('set keyword').all().map(item =&gt; item.json)}}
      Execute Once: Checked.
  Get progress node Checks the status of the Bright Data scraping job if complete, or running
  Setup:
      URL: https://api.brightdata.com/datasets/v3/progress/{{ $json.snapshot_id }}
      Headers:
          Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Replace with your Bright Data API key.

  Get snapshot + data retrieves the scraped data from the Bright Data API. Pass the request as 
      URL: https://api.brightdata.com/datasets/v3/snapshot/{{ $json.snapshot_id }}
      Query Parameters: format: json
      Headers:
          Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Replace with your Bright Data API key.

  Aggregate. Combines the data from each stock item into a single object
  Update to sheet and add all items to This sheet. Make a copy before you can map the data 

  create summary node generates a summary of the scraped stock data using the Google Gemini AI model and notifies you via Gmail.
  Setup:
      Prompt Type: define
      Text: Customize the prompt to define the AI's role, input format, tasks, output format (HTML email), and constraints.
  Google Sheets. Appends the scraped data to a Google Sheet. This should be set to automap so as to adjust to the results found in the request

  Important Notes:

  Remember to replace placeholder values (API keys, dataset IDs, email addresses, Google Sheet IDs) with your actual values.
  Review and customize the AI prompt for the "create summary" node to achieve the desired email summary output.
  Consider adding error handling for a more robust workflow.
  Monitor API usage to avoid rate limits.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini"]

workflow_json:
  {"meta":{"instanceId":"db80165df40cb07c0377167c050b3f9ab0b0fb04f0e8cae0dc53f5a8527103ca","templateCredsSetupCompleted":true},"nodes":[{"id":"e27afbc7-8cae-44b6-b506-474bb2692f08","name":"Wait","type":"n8n-nodes-base.wait","position":[-640,-300],"webhookId":"cf27222d-20db-4ba5-bd4c-e6ca05efd4d7","parameters":{"amount":20},"typeVersion":1.1},{"id":"2cc8d35f-f255-4adc-b1d7-7f9ab34dde66","name":"Get progress","type":"n8n-nodes-base.httpRequest","position":[-1020,-400],"parameters":{"url":"=https://api.brightdata.com/datasets/v3/progress/{{ $json.snapshot_id }}","options":{},"sendHeaders":true,"headerParameters":{"parameters":[{"name":"Authorization","value":"Bearer YOUR_TOKEN_HERE"}]}},"typeVersion":4.2},{"id":"eb6ab86c-3e8b-4dc6-8d70-3346531905fa","name":"Switch","type":"n8n-nodes-base.switch","position":[-840,-400],"parameters":{"rules":{"values":[{"outputKey":"ready","conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"4712e222-2bad-4d91-be87-ab0e0693c0c6","operator":{"name":"filter.operator.equals","type":"string","operation":"equals"},"leftValue":"={{ $json.status }}","rightValue":"ready"}]},"renameOutput":true},{"outputKey":"running","conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"9a473960-6ba5-4f1b-afc6-396348bd338d","operator":{"type":"string","operation":"equals"},"leftValue":"={{ $json.status }}","rightValue":"=running"}]},"renameOutput":true}]},"options":{}},"typeVersion":3.2},{"id":"88b7e912-af0c-4527-baa3-4f8cf0b072d1","name":"Split Out","type":"n8n-nodes-base.splitOut","position":[-1660,-400],"parameters":{"options":{},"fieldToSplitOut":"json"},"typeVersion":1},{"id":"d0ee4823-0536-415e-8fa9-861c1701665d","name":"SAMPLE DATA","type":"n8n-nodes-base.set","position":[-1860,-400],"parameters":{"options":{},"assignments":{"assignments":[{"id":"8d1bd0c8-37bf-4028-a20c-ac214ec06d7b","name":"json","type":"array","value":"=[\n  {\n    \"ticker\": \"NVDA\",\n    \"name\": \"NVIDIA Corporation\",\n    \"market_cap\": \"≈ $3.6T\"\n  },\n  {\n    \"ticker\": \"MSFT\",\n    \"name\": \"Microsoft Corporation\",\n    \"market_cap\": \"≈ $3.6T\"\n  },\n  {\n    \"ticker\": \"AAPL\",\n    \"name\": \"Apple Inc.\",\n    \"market_cap\": \"≈ $3.0T\"\n  },\n  {\n    \"ticker\": \"AMZN\",\n    \"name\": \"Amazon.com Inc.\",\n    \"market_cap\": \"≈ $2.2T\"\n  },\n  {\n    \"ticker\": \"GOOGL\",\n    \"name\": \"Alphabet Inc.\",\n    \"market_cap\": \"≈ $1.9T\"\n  },\n  {\n    \"ticker\": \"META\",\n    \"name\": \"Meta Platforms Inc.\",\n    \"market_cap\": \"≈ $1.5T\"\n  },\n  {\n    \"ticker\": \"BRK.B\",\n    \"name\": \"Berkshire Hathaway Inc.\",\n    \"market_cap\": \"≈ $1.1T\"\n  },\n  {\n    \"ticker\": \"TSLA\",\n    \"name\": \"Tesla Inc.\",\n    \"market_cap\": \"≈ $830B\"\n  },\n  {\n    \"ticker\": \"UNH\",\n    \"name\": \"UnitedHealth Group Inc.\",\n    \"market_cap\": \"≈ $450B\"\n  },\n  {\n    \"ticker\": \"JNJ\",\n    \"name\": \"Johnson & Johnson\",\n    \"market_cap\": \"≈ $450B\"\n  }\n]\n"}]}},"typeVersion":3.4},{"id":"2aab292f-0287-4da6-86ee-83c5a9aee30a","name":"set keyword","type":"n8n-nodes-base.set","position":[-1480,-400],"parameters":{"options":{},"assignments":{"assignments":[{"id":"8d9e80d9-16dd-4658-928f-d94735209bfd","name":"keyword","type":"string","value":"={{ $json.ticker }}"}]}},"typeVersion":3.4},{"id":"13f81727-f586-4fb6-be73-4880c9efd165","name":"Financial times scraper","type":"n8n-nodes-base.httpRequest","position":[-1260,-400],"parameters":{"url":"https://api.brightdata.com/datasets/v3/trigger","method":"POST","options":{},"jsonBody":"={{ $('set keyword').all().map(item => item.json)}}","sendBody":true,"sendQuery":true,"sendHeaders":true,"specifyBody":"json","queryParameters":{"parameters":[{"name":"dataset_id","value":"gd_lmrpz3vxmz972ghd7"},{"name":"include_errors","value":"true"},{"name":"type","value":"discover_new"},{"name":"discover_by","value":"keyword"}]},"headerParameters":{"parameters":[{"name":"Authorization","value":"=Bearer YOUR_TOKEN_HERE"}]}},"executeOnce":true,"typeVersion":4.2},{"id":"5e828381-8268-4114-b16c-a60c4ca23e80","name":"Get snapshot + data","type":"n8n-nodes-base.httpRequest","position":[-620,-480],"parameters":{"url":"=https://api.brightdata.com/datasets/v3/snapshot/{{ $json.snapshot_id }}","options":{},"sendQuery":true,"sendHeaders":true,"queryParameters":{"parameters":[{"name":"format","value":"json"}]},"headerParameters":{"parameters":[{"name":"Authorization","value":"Bearer YOUR_TOKEN_HERE"}]}},"typeVersion":4.2},{"id":"4c2826ee-30bb-4438-a531-c370edbe2103","name":"Aggregate","type":"n8n-nodes-base.aggregate","position":[-300,-280],"parameters":{"options":{},"aggregate":"aggregateAllItemData"},"typeVersion":1},{"id":"9cd0f2fd-248b-4047-aeb3-1a548ad02514","name":"Google Sheets","type":"n8n-nodes-base.googleSheets","position":[-320,-620],"parameters":{"columns":{"value":{},"schema":[],"mappingMode":"autoMapInputData","matchingColumns":[],"attemptToConvertTypes":false,"convertFieldsToString":false},"options":{},"operation":"append","sheetName":{"__rl":true,"mode":"list","value":"gid=0","cachedResultUrl":"https://docs.google.com/spreadsheets/d/1I5CvpHlmDsIFOfnGg4DEtniem0oTiumWWzGs4CV6AuM/edit#gid=0","cachedResultName":"Sheet1"},"documentId":{"__rl":true,"mode":"list","value":"1I5CvpHlmDsIFOfnGg4DEtniem0oTiumWWzGs4CV6AuM","cachedResultUrl":"https://docs.google.com/spreadsheets/d/1I5CvpHlmDsIFOfnGg4DEtniem0oTiumWWzGs4CV6AuM/edit?usp=drivesdk","cachedResultName":"Stock Monitor"}},"credentials":{"googleSheetsOAuth2Api":{"id":"ZAI2a6Qt80kX5a9s","name":"Google Sheets account✅ "}},"typeVersion":4.6},{"id":"d9797a77-bdf3-4600-bcd7-21311bb405fd","name":"Google Gemini Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatGoogleGemini","position":[0,-260],"parameters":{"options":{},"modelName":"models/gemini-2.0-flash-lite"},"credentials":{"googlePalmApi":{"id":"Xp5T9q3YYxBIw2nd","name":"Google Gemini(PaLM) Api account✅"}},"typeVersion":1},{"id":"ef5165a4-0452-4b20-b2fa-994429f3bc5b","name":"create summary","type":"@n8n/n8n-nodes-langchain.agent","position":[0,-480],"parameters":{"text":"=\n\n## 📤 SYSTEM PROMPT: Daily Stock Summary Email Generator (for n8n AI Agent)\n\n````markdown\n## 🎯 ROLE\nYou are a financial summary agent integrated in an n8n workflow. Your role is to:\n- Analyze incoming JSON data of top 10 U.S. stocks.\n- Identify meaningful insights: trends, outliers, sentiment, sector behavior.\n- Format this into a **clear, styled HTML email body** for professional users.\n- Return the **HTML content only** – ready to send via n8n’s email nodes.\n\n---\n\n## 📥 INPUT FORMAT (JSON)\n\nYou will receive daily JSON input structured like this:\n\n\nThe day and date today is {{ $now.format('cccc yyyy-MM-dd t ') }}\n\nHere is today’s data: =\n\n```\n\n{{ $json.data.toJsonString() }}\n\n```\n\n---\n\n## ✅ TASKS\n\n1. **Analyze market trends** based on price movements and sentiment.\n2. **Highlight top 2 gainers and losers**, including reasoning from news or change %.\n3. **Generate a stock table** (Ticker, Name, Price Change, Sentiment Icon).\n4. **Include 3–5 key takeaways**, insights, or investor watch notes.\n5. **Add upcoming events** if mentioned in news or based on date.\n6. Format everything as **HTML only**, ready for use in an email body.\n\n---\n\n## ✨ OUTPUT FORMAT (HTML Only)\n\n* Include inline styles (no external CSS).\n* Use semantic structure:\n\n  * `<h2>` for main title\n  * `<ul>` for movers and insights\n  * `<table>` for stock data\n* Use icons or colors for sentiment: 🟢 Positive, 🟡 Neutral, 🔴 Negative\n* Footer: “Generated automatically by your AI-powered stock monitor”\n\n---\n\n## ⚠️ CONSTRAINTS\n\n* DO NOT include subject or email headers\n* DO NOT output plaintext explanations or markdown\n* Output **HTML only**, clean and professional\n\n---\n\n## 📬 GOAL\n\nDeliver a polished, mobile-friendly, and insightful daily stock market summary email that can be sent directly by n8n. Final output should require zero manual edits.\n\n","options":{},"promptType":"define"},"typeVersion":2},{"id":"cf744498-62bf-4e6a-8570-dda7fea35fe5","name":"Schedule Trigger","type":"n8n-nodes-base.scheduleTrigger","position":[-2140,-400],"parameters":{"rule":{"interval":[{}]}},"typeVersion":1.2},{"id":"d564ee93-181f-461b-8ace-2dcb26439b6c","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-1940,-600],"parameters":{"color":5,"width":220,"height":420,"content":"## Add stock to track\n\nYou will add a list of the stocks you need to track here"},"typeVersion":1},{"id":"0c7e5d90-ce9e-456c-9f48-ba6872557467","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[-1680,-600],"parameters":{"color":4,"width":340,"height":420,"content":"## Split and set the field names\nThe field name MUST be keyword to match the bright data API"},"typeVersion":1},{"id":"64d932ee-f0b1-458a-a017-505676666c18","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-1320,-600],"parameters":{"color":2,"height":420,"content":"## Financial Times scraper\nScrap the latest trends in our selected Stock. \n\nSet it to run once"},"typeVersion":1},{"id":"bb55cc08-f262-42c1-9951-00771689495a","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[-1040,-680],"parameters":{"color":4,"width":620,"height":520,"content":"## Check the status of the progress and Get results\n\nIf `running` we make it loop until done"},"typeVersion":1},{"id":"9bc67859-d0b7-4d48-84d3-d0b9c90e8ca5","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[-700,-560],"parameters":{"color":7,"width":260,"height":260,"content":"## Get scraping results"},"typeVersion":1},{"id":"9627ec91-d2c4-4076-b39f-9f8be978177b","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[-380,-420],"parameters":{"width":280,"height":280,"content":"## Aggregate results to pass to AI for our email summary"},"typeVersion":1},{"id":"e01b8ad5-e028-4c81-9162-b27ae75687a3","name":"Sticky Note6","type":"n8n-nodes-base.stickyNote","position":[-60,-720],"parameters":{"color":3,"width":520,"height":600,"content":"## Create Draft email and notify admin\n\n\n\nCreate an email summary and notify the user"},"typeVersion":1},{"id":"8a23ca78-36e5-4ce3-b81d-fa62d770aa36","name":"Sticky Note7","type":"n8n-nodes-base.stickyNote","position":[-380,-680],"parameters":{"color":6,"width":280,"height":240,"content":"## Save results to G sheets"},"typeVersion":1},{"id":"3f953ffd-4faa-4cd5-bd3a-b3a6d021eebf","name":"Gmail1","type":"n8n-nodes-base.gmailTool","position":[180,-260],"webhookId":"fe4a416a-43f3-4ad1-80c8-51f1de4c2343","parameters":{"sendTo":"kimothozacharia5@gmail.com","message":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Message', `A detailed summary of the stock performance today. Must Look good`, 'string') }}","options":{"appendAttribution":false},"subject":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Subject', `Daily Stock report for {date today}`, 'string') }}"},"credentials":{"gmailOAuth2":{"id":"8PS0qVYNzZvoWNA7","name":"phoenix✅"}},"typeVersion":2.1}],"pinData":{"Financial times scraper":[{"snapshot_id":"s_mcbvdqgz1avn39assa"},{"snapshot_id":"s_mcbvdqht249242mqlq"},{"snapshot_id":"s_mcbvdqg4px7h201w9"},{"snapshot_id":"s_mcbvdqh4ci8ij15d1"},{"snapshot_id":"s_mcbvdqgs12legdw0a2"},{"snapshot_id":"s_mcbvdqhpqyr6tf8q"},{"snapshot_id":"s_mcbvdqgu1ti5q0ginr"},{"snapshot_id":"s_mcbvdqi21uyjc3tefw"},{"snapshot_id":"s_mcbvdqgzp73zxysyr"},{"snapshot_id":"s_mcbvdqgi2f3l95krzm"}]},"connections":{"Wait":{"main":[[{"node":"Get progress","type":"main","index":0}]]},"Gmail1":{"ai_tool":[[{"node":"create summary","type":"ai_tool","index":0}]]},"Switch":{"main":[[{"node":"Get snapshot + data","type":"main","index":0}],[{"node":"Wait","type":"main","index":0}]]},"Aggregate":{"main":[[{"node":"create summary","type":"main","index":0}]]},"Split Out":{"main":[[{"node":"set keyword","type":"main","index":0}]]},"SAMPLE DATA":{"main":[[{"node":"Split Out","type":"main","index":0}]]},"set keyword":{"main":[[{"node":"Financial times scraper","type":"main","index":0}]]},"Get progress":{"main":[[{"node":"Switch","type":"main","index":0}]]},"Google Sheets":{"main":[[]]},"create summary":{"main":[[]]},"Schedule Trigger":{"main":[[{"node":"SAMPLE DATA","type":"main","index":0}]]},"Get snapshot + data":{"main":[[{"node":"Google Sheets","type":"main","index":0},{"node":"Aggregate","type":"main","index":0}]]},"Financial times scraper":{"main":[[{"node":"Get progress","type":"main","index":0}]]},"Google Gemini Chat Model":{"ai_languageModel":[[{"node":"create summary","type":"ai_languageModel","index":0}]]}}}


name: AI Resume Processing and GitHub Analysis with VLM Run
author_name: Shahrear
author_username: shahrear
categories: []
created_at: 2025-06-25T15:48:27.875Z
updated_at: 2025-06-25T15:48:27.875Z
url: https://n8n.io/workflows/5306
scraped_at: 2025-07-06 21:16:30
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  Automatically transform resume submissions into comprehensive candidate profiles with AI-powered parsing, GitHub analysis, and instant team notifications.

  What this workflow does
  Monitors Gmail for incoming resume attachments
  Extracts structured data using VLM Run AI document parsing
  Analyzes GitHub profiles with deep repository intelligence (30+ frameworks detected)
  Creates comprehensive candidate profiles with technical skills assessment
  Delivers multi-channel notifications via Google Sheets, Slack, and candidate emails

  Setup
  Prerequisites: Gmail account, VLM Run API credentials, Google Sheets access, Slack workspace, self-hosted n8n.
  You need to install VLM Run community node

  Quick Setup:
  Configure Gmail OAuth2 for resume monitoring
  Add VLM Run API credentials for document parsing
  Create Google Sheets candidate database
  Set up Slack integration for team notifications
  Update spreadsheet/channel IDs in workflow nodes
  Test with sample resume and activate

  Perfect for
  HR departments and technical recruiting teams
  Startup hiring and talent acquisition agencies
  Developer assessment and skill evaluation
  Remote team hiring and candidate screening
  Any organization seeking data-driven hiring decisions

  Key Benefits
  Eliminates manual data entry** - AI extracts all contact info, skills, and experience
  GitHub intelligence engine** - Analyzes repositories, calculates experience, detects technologies
  Comprehensive skill assessment** - Identifies programming languages, frameworks, and project metrics
  Professional candidate experience** - Automated acknowledgment emails with personalized touches
  Instant team collaboration** - Rich Slack notifications with GitHub profile highlights
  Structured data storage** - Searchable candidate database with 20+ data columns
  Saves hours per candidate** - Transforms 30-minute manual reviews into instant insights

  How to customize
  Extend by adding:
  Integration with ATS systems (Greenhouse, Lever, BambooHR)
  LinkedIn profile analysis and social media insights
  Automated interview scheduling based on qualifications
  Skills-based candidate scoring and ranking algorithms
  Integration with code assessment platforms
  Multi-language resume support and translation
  Custom evaluation criteria and filtering rules
  Advanced GitHub metrics (code quality, contribution patterns)

  This workflow revolutionizes technical hiring by combining AI-powered resume parsing with deep GitHub analysis, delivering comprehensive candidate intelligence that empowers data-driven hiring decisions while maintaining a professional candidate experience.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.slack","n8n-nodes-base.gmail","n8n-nodes-base.code"]

workflow_json:
  {"meta":{"instanceId":"0a7ae129a7d703150135f6cc24d0469f20ffd22b5ed59c23ee3e0608264e6d98","templateCredsSetupCompleted":true},"nodes":[{"id":"bdf7d44b-b13e-4bfc-bbb5-0fabe8abd40a","name":"Send Acknowledgement Email","type":"n8n-nodes-base.gmail","position":[-20,1140],"webhookId":"959be407-da29-4fef-bb85-ac5cc6b41a6d","parameters":{"sendTo":"={{ $json.contact_info.email }}","message":"We will get in touch shortly.","options":{"senderName":"VLM Run","appendAttribution":false},"subject":"Thanks for Your Interest"},"credentials":{"gmailOAuth2":{"id":"7MVziRpoyD8arghO","name":"Gmail account 2"}},"typeVersion":2.1},{"id":"72290874-1493-4980-a445-ac5d5f752ebd","name":"🔍 GitHub Analysis Documentation3","type":"n8n-nodes-base.stickyNote","position":[-1460,100],"parameters":{"color":7,"width":1260,"height":640,"content":"## 🔍 GitHub Intelligence Engine\n\n**Deep analysis of candidate's GitHub profile and repositories.**\n\n**Profile Analysis:**\n- Account age & experience\n- Follower/following metrics\n- Public repository count\n- Bio and company info\n\n**Repository Intelligence:**\n- Language distribution\n- Framework detection (30+)\n- Total stars & forks\n- Recent activity tracking\n\n**Technology Detection:**\n- Frontend: React, Vue, Angular\n- Backend: Express, Django, Flask\n- Mobile: React Native, Flutter\n- DevOps: Docker, AWS, Kubernetes\n\n**Smart Features:**\n- Handles missing profiles gracefully\n- Calculates experience automatically\n- Ranks technologies by usage\n- Identifies trending skills"},"typeVersion":1},{"id":"2cc059ed-deb1-4cd6-bc35-a840e7e3fb9f","name":"🤖 AI Processing Documentation1","type":"n8n-nodes-base.stickyNote","position":[-1860,100],"parameters":{"color":3,"width":380,"height":880,"content":"## 🤖 AI Resume Analysis\n\n**VLM Run processes resumes to extract structured candidate data.**\n\n**Features:**\n- Contact information extraction\n- Skills identification\n- Experience parsing\n- Education details\n- Social profile detection\n\n**Advanced Extraction:**\n- Name, email, phone\n- GitHub & LinkedIn URLs\n- Work history\n- Technical skills\n- Certifications\n\n**Output:**\n- Structured JSON data\n- Normalized fields\n- Ready for analysis\n\n**Benefits:**\n- Eliminates manual data entry\n- Consistent formatting\n- Accurate extraction\n- Scalable processing"},"typeVersion":1},{"id":"92d64d61-d690-4d68-8ee7-ebb0f231c02c","name":"📧 Intake Documentation1","type":"n8n-nodes-base.stickyNote","position":[-2260,100],"parameters":{"color":7,"width":380,"height":880,"content":"## 📧 Resume Intake Processing\n\n**Monitors Gmail for incoming resume submissions and automatically triggers processing.**\n\n**Process:**\n1. Watches inbox every minute\n2. Detects emails with attachments\n3. Auto-triggers on new resumes\n4. Downloads PDF attachments\n\n**Supported Formats:**\n- PDF resumes\n- DOC/DOCX files\n- Various layouts\n- Multi-page documents\n\n**Trigger Conditions:**\n- New email received\n- Contains attachments\n- Attachment download enabled\n- Real-time processing"},"typeVersion":1},{"id":"a6a81e04-0f29-44c6-aa81-0b642517b7bb","name":"📋 Workflow Overview1","type":"n8n-nodes-base.stickyNote","position":[-2740,100],"parameters":{"color":7,"width":460,"height":880,"content":"## 📋 AI Resume Processing & GitHub Analysis\n\n**Overview:**\nAutomatically processes resumes received via email and generates comprehensive candidate profiles with AI-powered resume parsing and GitHub analysis.\n\n**Workflow:**\n1. 📧 Monitor Gmail for resume submissions\n2. 🤖 Parse resume with AI extraction\n3. 🔍 Analyze GitHub profile (if available)\n4. 📊 Create comprehensive candidate profile\n5. 💬 Notify team via Slack + save to Sheets\n6. ✉️ Send acknowledgment to candidate\n\n**Perfect for:**\n- HR departments\n- Technical recruiting\n- Talent acquisition teams\n- Startup hiring\n- Developer assessment\n\n**Requirements:**\n- VLM Run API access\n- Gmail OAuth2\n- Google Sheets access\n- Slack webhook\n- GitHub API (optional authentication)"},"typeVersion":1},{"id":"3d3a320b-b63d-4248-a01e-6f75fb77b716","name":"📊 Output Documentation1","type":"n8n-nodes-base.stickyNote","position":[-180,100],"parameters":{"color":7,"width":420,"height":1240,"content":"## 📊 Multi-Channel Output\n\n**Delivers comprehensive candidate data across multiple platforms.**\n\n**Google Sheets Integration:**\n- Structured candidate database\n- 20+ data columns\n- Searchable & filterable\n- Historical tracking\n\n**Slack Notifications:**\n- Instant team alerts\n- Rich candidate summaries\n- GitHub profile highlights\n- Technology breakdown\n\n**Email Automation:**\n- Professional acknowledgments\n- Personalized messages\n- GitHub profile mentions\n- Builds candidate experience\n\n**Benefits:**\n- Centralized data storage\n- Real-time team updates\n- Professional communication\n- Streamlined hiring process"},"typeVersion":1},{"id":"4c4d9503-4b4a-4a95-bf64-67d4e0acc7b2","name":"Monitor Gmail for Resumes","type":"n8n-nodes-base.gmailTrigger","position":[-2160,760],"parameters":{"simple":false,"filters":{},"options":{"downloadAttachments":true},"pollTimes":{"item":[{"mode":"everyMinute"}]}},"credentials":{"gmailOAuth2":{"id":"7MVziRpoyD8arghO","name":"Gmail account 2"}},"typeVersion":1.2},{"id":"a888c038-d826-4cd0-aefc-f9aca346a7f2","name":"Parse Resume with VLM Run","type":"@vlm-run/n8n-nodes-vlmrun.vlmRun","position":[-1720,760],"parameters":{"file":"attachment_0","domain":"document.resume"},"credentials":{"vlmRunApi":{"id":"cF5KpbVmnt36bdWr","name":"VLM Run account 6"}},"typeVersion":1},{"id":"1134c82c-77e6-438d-8fbc-77807837db17","name":"Check for Github Profile","type":"n8n-nodes-base.if","position":[-1360,760],"parameters":{"options":{},"conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"e28a7d82-d42c-4ce0-9a7d-7f9ef94090c2","operator":{"type":"string","operation":"exists","singleValue":true},"leftValue":"={{ $json.response.contact_info.github }}","rightValue":""}]}},"typeVersion":2.2},{"id":"29ef7e94-6c03-4e0c-98e6-3720b6e078cb","name":"Extract GitHub Username","type":"n8n-nodes-base.code","position":[-1080,540],"parameters":{"jsCode":"const url = $input.first().json.response.contact_info.github\nconst username = url.split('github.com/')[1].split('/')[0];\nreturn [{ json: { username } }];"},"typeVersion":2},{"id":"2c851eda-2501-4b8a-a855-9ac5cb750d3c","name":"Fetch GitHub Profile","type":"n8n-nodes-base.httpRequest","position":[-840,340],"parameters":{"url":"=https://api.github.com/users/{{ $json.username }}","options":{}},"typeVersion":4.2},{"id":"19528631-4eab-420b-9601-25d96e65b9c8","name":"Fetch GitHub Repositories","type":"n8n-nodes-base.httpRequest","position":[-840,540],"parameters":{"url":"=https://api.github.com/users/{{ $json.username }}/repos","options":{}},"typeVersion":4.2},{"id":"7ac5cbc4-828c-42d1-addf-162458ac6fda","name":"Process Profile Data","type":"n8n-nodes-base.code","position":[-620,340],"parameters":{"jsCode":"const user = items[0].json;\n\n// Parse creation and update dates\nconst created = new Date(user.created_at);\nconst updated = new Date(user.updated_at);\n\n// Calculate difference in milliseconds\nconst diffTime = Math.abs(updated - created);\n\n// Convert milliseconds to years\nconst years = diffTime / (1000 * 60 * 60 * 24 * 365.25);\n\n// Round to nearest whole number\nconst experience = `~${Math.round(years)}`;\n\n// Return desired output\nreturn [\n  {\n    json: {\n      login: user.login,\n      public_repos: user.public_repos,\n      followers: user.followers,\n      experience\n    }\n  }\n];"},"typeVersion":2},{"id":"1b32ce5f-3213-43b0-a604-be204c1ae476","name":"Analyze Repository Data","type":"n8n-nodes-base.code","position":[-600,540],"parameters":{"jsCode":"// Initialize counts\nlet languageCount = {};\nlet frameworkCount = {};\nlet totalStars = 0;\nlet totalForks = 0;\n\n// Full list of frameworks, libraries, and tools\nconst knownFrameworks = [\n  \"React\", \"Angular\", \"Vue\", \"Bootstrap\", \"Tailwind\", \"jQuery\",\n  \"Node\", \"Express\", \"Django\", \"Flask\", \"Spring Boot\", \"Laravel\", \"Rails\",\n  \"React Native\", \"Flutter\", \"Ionic\",\n  \"MongoDB\", \"MySQL\", \"PostgreSQL\", \"Firebase\",\n  \"Docker\", \"Jenkins\", \"GitHub\", \"GitLab\", \"AWS\", \"Azure\", \"Netlify\", \"Vercel\",\n  \"Jest\", \"Mocha\", \"Cypress\", \"Selenium\",\n  \"FastAPI\", \"Redux\", \"Redux Toolkit\"\n];\n\n// Helper function to extract frameworks\nfunction extractFrameworks(text) {\n  if (!text) return [];\n\n  const matches = new Set();\n  const lowerText = text.toLowerCase();\n\n  for (const fw of knownFrameworks) {\n    if (lowerText.includes(fw.toLowerCase())) {\n      matches.add(fw);\n    }\n  }\n\n  return Array.from(matches);\n}\n\n// Loop through repositories\nfor (const item of items) {\n  const repo = item.json;\n\n  // Count languages\n  const lang = repo.language;\n  if (lang) {\n    languageCount[lang] = (languageCount[lang] || 0) + 1;\n  }\n\n  // Count frameworks from description and topics\n  const descFrameworks = extractFrameworks(repo.description);\n  const topicFrameworks = extractFrameworks((repo.topics || []).join(\" \"));\n  const allFrameworks = new Set([...descFrameworks, ...topicFrameworks]);\n\n  for (const fw of allFrameworks) {\n    frameworkCount[fw] = (frameworkCount[fw] || 0) + 1;\n  }\n\n  // Add stars and forks\n  totalStars += repo.stargazers_count || 0;\n  totalForks += repo.forks_count || 0;\n}\n\n// Return combined result\nreturn [\n  {\n    json: {\n      languageCount,\n      frameworkCount,\n      totalStars,\n      totalForks\n    }\n  }\n];"},"typeVersion":2},{"id":"7f58201c-7656-4aae-9423-52680aa37b82","name":"Combine GitHub Data","type":"n8n-nodes-base.merge","position":[-360,540],"parameters":{"numberInputs":3},"typeVersion":3.1},{"id":"09f1229a-4638-44b2-8244-139b9b9022de","name":"Flatten Response","type":"n8n-nodes-base.code","position":[-500,780],"parameters":{"jsCode":"const allItems = $input.all();\n\n// Defensive checks to ensure indexes exist\nconst resumeData = allItems[0]?.json?.response || {};\nconst githubData = allItems[1]?.json || {};\nconst repoData = allItems[2]?.json || {};\n\n// Merge into one object\nconst mergedData = {\n  ...githubData,\n  ...resumeData,\n  ...repoData\n};\n\n// Return as single item array\nreturn [\n  {\n    json: mergedData\n  }\n];"},"typeVersion":2},{"id":"e8f89ee8-2bcd-464a-8ec8-2be11bf1c2b2","name":"Save to Google Sheet","type":"n8n-nodes-base.googleSheets","position":[-20,780],"parameters":{"columns":{"value":{"Name":"={{ $json.contact_info.full_name }}","Email":"={{ $json.contact_info.email }}","Phone no.":"={{ $json.contact_info.phone }}","Github URL":"={{ $json.contact_info.github }}","C++ Projects":"={{ $json.languageCount?.cpp || null }}","LinkedIn URL":"={{ $json.contact_info.linkedin }}","Java Projects":"={{ $json.languageCount?.Java || null }}","React Projects":"={{ $json.languageCount?.React || null }}","Python Projects":"={{ $json.languageCount?.Python || null }}","GitHub Experience":"={{ $json.expeience || null }}","GitHub Fork Count":"={{ $json.totalForks || null}}","GitHub Star Count":"={{ $json.totalStars || null }}","Github Repo Count":"={{ $json.public_repos || null }}","Javascript Projects":"={{ $json.languageCount?.JavaScript || null }}","TypeScript Projects":"={{ $json.languageCount?.TypeScript || null }}","Github follower count":"={{ $json.followers || null }}"},"schema":[{"id":"Name","type":"string","display":true,"removed":false,"required":false,"displayName":"Name","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Email","type":"string","display":true,"required":false,"displayName":"Email","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Phone no.","type":"string","display":true,"required":false,"displayName":"Phone no.","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Github URL","type":"string","display":true,"required":false,"displayName":"Github URL","defaultMatch":false,"canBeUsedToMatch":true},{"id":"LinkedIn URL","type":"string","display":true,"required":false,"displayName":"LinkedIn URL","defaultMatch":false,"canBeUsedToMatch":true},{"id":"GitHub Experience","type":"string","display":true,"required":false,"displayName":"GitHub Experience","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Github follower count","type":"string","display":true,"required":false,"displayName":"Github follower count","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Github Repo Count","type":"string","display":true,"required":false,"displayName":"Github Repo Count","defaultMatch":false,"canBeUsedToMatch":true},{"id":"GitHub Star Count","type":"string","display":true,"required":false,"displayName":"GitHub Star Count","defaultMatch":false,"canBeUsedToMatch":true},{"id":"GitHub Fork Count","type":"string","display":true,"required":false,"displayName":"GitHub Fork Count","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Javascript Projects","type":"string","display":true,"required":false,"displayName":"Javascript Projects","defaultMatch":false,"canBeUsedToMatch":true},{"id":"TypeScript Projects","type":"string","display":true,"required":false,"displayName":"TypeScript Projects","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Python Projects","type":"string","display":true,"required":false,"displayName":"Python Projects","defaultMatch":false,"canBeUsedToMatch":true},{"id":"C++ Projects","type":"string","display":true,"required":false,"displayName":"C++ Projects","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Java Projects","type":"string","display":true,"required":false,"displayName":"Java Projects","defaultMatch":false,"canBeUsedToMatch":true},{"id":"React Projects","type":"string","display":true,"required":false,"displayName":"React 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*New Job Application Received!*\n\n📨 *Candidate Name:* {{ $json.contact_info.full_name }}\n📧 *Email:* <mailto:{{ $json.contact_info.email }}|{{ $json.contact_info.email }}>\n\n📝 A new application has just been submitted. 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name: AI Audio Transcription & Google Docs Report Generator with VLM Run
author_name: Shahrear
author_username: shahrear
nodes_used: ["n8n-nodes-base.googleDocs"]
categories: []
created_at: 2025-06-25T15:53:16.242Z
updated_at: 2025-06-25T15:53:16.242Z
url: https://n8n.io/workflows/5307
scraped_at: 2025-07-06 21:16:30
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  Automatically transform audio files into professional transcription reports with AI-powered speech recognition, timestamp generation, and formatted Google Docs output.

  What this workflow does
  Monitors Gmail for incoming audio attachments
  Downloads and processes audio files using VLM Run AI transcription
  Generates accurate transcriptions with precise timestamps and segmentation
  Creates professional reports in Google Docs with formatted output
  Handles asynchronous processing for long audio files without timeouts

  Setup
  Prerequisites: Gmail account, VLM Run API credentials, Google Docs access, self-hosted n8n.
  You need to install VLM Run community node

  Quick Setup:
  Configure Gmail OAuth2 for email monitoring
  Add VLM Run API credentials for audio transcription
  Set up Google Docs OAuth2 for report generation
  Create target Google Doc for transcription reports
  Update document URL in workflow nodes
  Test with sample audio file and activate

  Perfect for
  Meeting recordings and conference calls
  Voice memos and dictation workflows
  Interview transcriptions and journalism
  Podcast episode documentation
  Accessibility compliance and documentation
  Legal proceedings and court recordings
  Educational content and lecture notes
  Customer service call analysis

  Key Benefits
  Human-level accuracy** - Advanced AI speech recognition with automatic punctuation
  Timestamp precision** - Segmented transcriptions with exact time markers
  Multi-format support** - Handles MP3, WAV, M4A, AAC, OGG, FLAC files
  Asynchronous processing** - No timeouts for long audio files
  Professional formatting** - Beautifully structured Google Docs reports
  Automatic workflow** - Zero manual intervention required
  Saves hours per recording** - Transforms manual transcription into instant results
  Searchable documentation** - Google Docs integration enables easy content discovery

  How to customize
  Extend by adding:
  Speaker identification and diarization
  Integration with project management tools (Notion, Asana, Trello)
  Automatic summary generation from transcripts
  Translation to multiple languages
  Slack notifications for completed transcriptions
  Integration with CRM systems for call logging
  Audio quality enhancement preprocessing
  Custom formatting templates for different use cases
  Automatic keyword extraction and tagging
  Integration with calendar systems for meeting context

  This workflow revolutionizes audio documentation by combining cutting-edge AI transcription with professional report generation, making spoken content instantly accessible, searchable, and shareable across your organization.

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name: Create Animated Baby Podcast Videos with GPT, DALL-E, ElevenLabs and Hedra
author_name: Adam Crafts
author_username: adamcrafts
categories: []
created_at: 2025-06-25T17:51:07.003Z
updated_at: 2025-06-25T17:51:07.003Z
url: https://n8n.io/workflows/5308
scraped_at: 2025-07-06 21:16:30
description:
  🚀 Overview

  This workflow is your personal content creation studio for social media. It takes a simple idea and a few descriptive words and automatically produces a complete, ready-to-share video of a custom-designed baby hosting their own podcast. It's the ultimate tool for creating unique, funny, and engaging content that captures attention and drives shares.

  😩 The Problem

  Creating animated video content is a massive headache. Manually, you'd have to:
  Hire or be a skilled graphic designer to create the character.
  Write a clever and engaging script.
  Find a voice actor to record the audio.
  Use complex and expensive animation software to make the character's mouth and expressions match the audio.
  Render and export the final video.

  This process is incredibly time-consuming, requires specialized skills, and can cost hundreds or even thousands of dollars for a single short video. The barrier to creating fun, viral content is just too high.

  ✨ The Solution

  This workflow acts as your automated video production team! It elegantly handles the entire creation process from start to finish. Here’s how it works:

  🎙️ Design Your Star: You start by filling out a simple form to design your baby podcaster. You choose their ethnicity, hair style, outfit, and even how chubby their cheeks are. You also give them a topic to discuss.
  ✍️ Generate a Script & Image: Instantly, the automation writes a short podcast script using OpenAI (GPT-4) and generates a unique, photorealistic image of your baby with DALL-E.
  🗣️ Bring it to Life: It then creates a voice for your baby using the script (via ElevenLabs) and animates the baby's face to talk and express themselves perfectly in sync with the audio (via Hedra).
  📂 Deliver the Final Cut: The final, ready-to-post video is automatically rendered and saved directly into a designated Google Drive folder. Your viral video is ready to be shared with the world in just a few minutes!

  ⚙️ Simple Setup

  This workflow is a pre-built blueprint, designed to be up and running in minutes!

  Upload:** Simply upload the provided JSON file into your n8n instance.
  Detailed Setup:** Follow all the instructions of the Detailed Setup.
  Activate:** Turn the workflow on, and it's ready to go! Let your new automated employee get to work.

  🌐 Explore more workflows
  ❤️ Buy more workflows at: adamcrafts
  automations
  🦾 Custom workflows at: adamcrafts@cloudysoftwares.com
  adamaicrafts@gmail.com


  &gt; Build once, customize endlessly, and scale your video content like never before.

nodes_used:
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name: Vacation Planning Agent
author_name: Tamer
author_username: tamerelzein
categories: []
created_at: 2025-06-25T17:52:46.960Z
updated_at: 2025-06-25T17:52:46.960Z
url: https://n8n.io/workflows/5309
scraped_at: 2025-07-06 21:16:30
description:
  Vacation Planning Agent - n8n Workflow

  Overview

  This n8n workflow creates an intelligent vacation planning chatbot that helps users find and book the perfect hotel accommodations. The agent acts as a professional travel consultant, systematically gathering travel requirements and providing personalized hotel recommendations through an interactive chat interface.

  Core Functionality

  The workflow provides a conversational AI agent that:

  Conducts structured information gathering** through natural conversation
  Automatically searches for hotels** using real-time data from Google Hotels
  Provides personalized recommendations** with detailed hotel information
  Maintains conversation context** throughout the planning process
  Delivers professional travel consultation** in a friendly, accessible format

  User Experience Flow

  Initial Interaction
  Users are greeted with a warm welcome message in German: "Hallo! Ich helfe dir, deinen perfekten Urlaub zu planen. Bitte beanworte mir die folgenden Fragen :)"

  Information Collection Process
  The agent systematically collects essential travel details:

  Destination - City and country/state
  Travel Dates - Check-in and check-out dates
  Guest Count - Number of travelers
  Room Requirements - Number of rooms needed
  Budget Preferences - Optional price range

  Automated Hotel Search
  Once core information is gathered, the agent automatically searches for available accommodations without requiring user permission.

  Recommendation Delivery
  Results are presented in a structured format including:
  Hotel names and star ratings
  Pricing information
  Location details
  Guest ratings and reviews
  Key amenities and highlights
  Direct booking links

  Required Integrations

  OpenAI API
  Purpose**: Powers the conversational AI agent
  Model**: GPT-4o-mini for cost-effective, intelligent responses
  Requirement**: Valid OpenAI API credentials

  SerpAPI (Google Hotels)
  Purpose**: Real-time hotel search and pricing data
  Service**: Google Hotels search engine integration
  Requirement**: Active SerpAPI account and API key

  Key Features

  Intelligent Conversation Management
  Maintains conversation context with 20-message memory buffer
  Handles edge cases like no available hotels or unclear responses
  Provides alternative suggestions when initial searches yield limited results

  Flexible Search Parameters
  Supports location-based searches worldwide
  Accommodates date range specifications
  Handles guest count and room quantity requirements
  Optional budget filtering (min/max price ranges)
  Currency customization support

  Professional Presentation
  Structured hotel recommendation format
  Clear pricing and availability information
  Contextual explanations for recommendations
  Additional destination insights when relevant

  Use Cases

  This workflow is ideal for:

  Travel websites** seeking to add AI-powered hotel booking assistance
  Travel agencies** wanting to automate initial consultation processes
  Hospitality businesses** providing customer service automation
  Personal travel planning** applications
  Customer support** for travel-related inquiries

  User Benefits

  Time-saving**: Eliminates manual hotel research
  Personalized results**: Tailored recommendations based on specific needs
  Real-time data**: Current pricing and availability information
  Professional guidance**: Expert-level travel consultation
  Seamless experience**: Natural conversation flow without complex forms

  Technical Requirements

  Essential Services
  n8n workflow automation platform
  OpenAI API access (GPT-4o-mini model)
  SerpAPI account with Google Hotels access

  Configuration Needs
  API credential setup for both OpenAI and SerpAPI
  Webhook endpoint configuration for chat trigger
  Memory buffer configuration for conversation context

  Optional Enhancements
  Custom branding for chat interface
  Additional language support beyond German greeting
  Integration with booking platforms for direct reservations
  Analytics tracking for usage insights

nodes_used:
[cell repeats an earlier one in this file: 120 characters]

workflow_json:
  {"id":"7J9FeS334LVe2BQG","meta":{"instanceId":"b5a944ba8839572df11fe1edab9898c0cc0a8b920d79a8a9e1ccb59618a73552","templateCredsSetupCompleted":true},"name":"Vacation Planning Agent","tags":[],"nodes":[{"id":"7bb2c020-3495-4794-9e36-3028d4b7eb40","name":"Chat Trigger","type":"@n8n/n8n-nodes-langchain.chatTrigger","position":[780,0],"webhookId":"urlaubsplaner-multi-step","parameters":{"public":true,"options":{},"initialMessages":"Hallo! Ich helfe dir, deinen perfekten Urlaub zu planen. Bitte beanworte mir die folgenden Fragen :)"},"typeVersion":1.1},{"id":"1a833e37-4d77-4667-af98-be8283ab4c1b","name":"AI Agent","type":"@n8n/n8n-nodes-langchain.agent","position":[1080,0],"parameters":{"options":{"systemMessage":"# Vacation Planner Agent Prompt\n\nYou are a professional vacation planner assistant that helps users find the perfect hotel accommodations. Your goal is to gather essential travel information and provide personalized hotel recommendations using the Search for Hotels tool.\n\n## Available Tools\n\nYou have access to a **Search for Hotels** tool that searches for accommodations using SerpAPI Google Hotels. Use this tool automatically once you have gathered the essential information (destination, dates, guests, rooms). You do not need to ask permission or confirm with the user before using the tool.\n- Act as a friendly, knowledgeable travel consultant\n- Ask questions systematically to understand user needs\n- Provide clear, helpful hotel recommendations based on search results\n- Maintain a conversational yet professional tone\n\n## Information Gathering Process\n\n### Step 1: Initial Greeting\nGreet the user warmly and explain that you'll help them find the perfect hotel for their trip.\n\n### Step 2: Collect Essential Details\nAsk these questions one at a time, waiting for each response:\n\n1. **Destination**: \"Where would you like to travel? Please provide the city and country (or state if in the US).\"\n\n2. **Travel Dates**: \"During which time period are you planning to travel? Please provide your check-in and check-out dates.\"\n\n3. **Number of Guests**: \"How many people will be traveling?\"\n\n4. **Room Requirements**: \"How many rooms would you need?\"\n\n5. **Budget Range** (Optional): \"Do you have a preferred budget range per night? This will help me find options that fit your needs.\"\n\n### Step 3: Automatic Hotel Search\nOnce you have collected the essential information (destination, check-in/check-out dates, number of guests, and rooms), immediately use the Search for Hotels tool to find available accommodations. You do not need user permission to proceed with the search.\n\n### Step 4: Additional Preferences (Optional)\nIf the user seems open to it, you may ask:\n- \"Are there any specific amenities you're looking for? (pool, gym, free breakfast, etc.)\"\n- \"Do you prefer to stay in a particular area of the city?\"\n- \"Any hotel star rating preference?\"\n\n## Your Role\n\n### When presenting hotel options:\n\n1. **Lead with the best matches** - Present 3-5 top recommendations\n2. **Include key details for each hotel**:\n   - Hotel name and star rating\n   - Price per night\n   - Location/neighborhood\n   - Guest rating/review score\n   - Key amenities\n   - Brief description of why it's a good fit\n\n3. **Format recommendations clearly**:\n   ```\n   🏨 **Hotel Name** (4-star)\n   📍 Location: [Neighborhood/Area]\n   💰 Price: $X per night\n   ⭐ Rating: X.X/10 (based on X reviews)\n   ✨ Highlights: [2-3 key features]\n   🔗 Book now: [Hotel booking URL]\n   ```\n\n4. **Provide context**: Explain why each hotel was selected based on their stated preferences\n\n5. **Offer alternatives**: Mention if there are budget-friendly or luxury alternatives available\n\n## Response Style Guidelines\n\n- **Be conversational**: Use natural, friendly language\n- **Be concise but informative**: Provide essential details without overwhelming\n- **Show enthusiasm**: Express genuine interest in helping them have a great trip\n- **Be helpful**: Offer additional tips or insights about the destination when relevant\n- **Handle edge cases**: If no good options are found, explain why and suggest alternatives (different dates, nearby cities, etc.)\n\n## Example Interaction Flow\n\n**Agent**: \"Hello! I'm here to help you find the perfect hotel for your upcoming trip. Let me ask you a few questions to get started. Where would you like to travel?\"\n\n**User**: \"Paris, France\"\n\n**Agent**: \"Wonderful choice! Paris is amazing. When are you planning to visit? Please let me know your check-in and check-out dates.\"\n\n[Continue gathering information...]\n\n**Agent**: \"Perfect! Let me search for the best hotels in Paris for your stay from [dates] for [number] guests needing [rooms] room(s).\"\n\n[Automatically uses Search for Hotels tool]\n\n[After receiving search results...]\n\n**Agent**: \"Great news! I found some excellent options for your Paris trip. Here are my top recommendations:\n\n[Present formatted hotel recommendations]\n\nWould you like more details about any of these hotels, or would you prefer to see additional options?\"\n\n## Important Notes\n\n- Always confirm the search parameters before presenting results\n- If search results are limited, explain potential reasons (peak season, sold out, etc.)\n- Be prepared to adjust recommendations based on user feedback\n- End with a clear call-to-action or next steps"}},"typeVersion":2},{"id":"8acfa2ee-4d85-40bc-8999-5f14f19b11a3","name":"OpenAI Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[960,260],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-4o-mini","cachedResultName":"gpt-4o-mini"},"options":{}},"credentials":{"openAiApi":{"id":"PInyzlnaqujHVKEB","name":"n8n free OpenAI API credits"}},"typeVersion":1.2},{"id":"f1f925af-21b9-4f4e-afe9-c2685ae581cf","name":"Simple Memory","type":"@n8n/n8n-nodes-langchain.memoryBufferWindow","position":[1120,260],"parameters":{"contextWindowLength":20},"typeVersion":1.3},{"id":"666d267e-577d-47cf-bd42-c6d245f009ff","name":"Search for hotels","type":"n8n-nodes-base.httpRequestTool","position":[1280,260],"parameters":{"url":"https://serpapi.com/search","options":{},"sendQuery":true,"authentication":"predefinedCredentialType","queryParameters":{"parameters":[{"name":"q","value":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Value', `Parameter defines the search query. You can use anything that you would use in a regular Google Hotels search.`, 'string') }}"},{"name":"check_in_date","value":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters1_Value', `Parameter defines the check-in date. The format is YYYY-MM-DD. e.g. 2025-06-20`, 'string') }}"},{"name":"check_out_date","value":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters2_Value', `Parameter defines the check-out date. The format is YYYY-MM-DD. e.g. 2025-06-21`, 'string') }}"},{"name":"min_price","value":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters3_Value', `Optional\nParameter defines the lower bound of price range.`, 'string') }}"},{"name":"max_price","value":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters4_Value', `Optional\n\nParameter defines the upper bound of price range.`, 'string') }}"},{"name":"currency","value":"={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters5_Value', `Optional\n\nParameter defines the currency of the returned prices. Default to USD. Head to the Google Travel Currencies page for a full list of supported currency codes.`, 'string') }}"},{"name":"gl","value":"de"},{"name":"engine","value":"google_hotels"}]},"toolDescription":"This tool searches for hotels based on user query and returns response","nodeCredentialType":"serpApi"},"credentials":{"serpApi":{"id":"3vKCVyplnh1Grx9T","name":"SerpAPI account"}},"typeVersion":4.2}],"active":false,"pinData":{},"settings":{"executionOrder":"v1"},"versionId":"e84fa65e-8a74-413a-b1cf-79984369b2e8","connections":{"Chat Trigger":{"main":[[{"node":"AI Agent","type":"main","index":0}]]},"Simple Memory":{"ai_memory":[[{"node":"AI Agent","type":"ai_memory","index":0}]]},"OpenAI Chat Model":{"ai_languageModel":[[{"node":"AI Agent","type":"ai_languageModel","index":0}]]},"Search for hotels":{"ai_tool":[[{"node":"AI Agent","type":"ai_tool","index":0}]]}}}


name: 🤖 AI Customer Support Agent - Never Sleep, Never Miss a Customer Again!
author_name: Amanda Benks
author_username: amanda
categories: []
created_at: 2025-06-25T18:44:00.112Z
updated_at: 2025-06-25T18:44:00.112Z
url: https://n8n.io/workflows/5310
scraped_at: 2025-07-06 21:16:30
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  24/7 AI Support Agent: Handle 10x More Customers While You Sleep! 💰

  🚀 Transform Your Customer Support Into a Profit Machine

  Stop losing customers to slow responses! 

  This revolutionary AI Customer Support Agent workflow turns your n8n into a 24/7 customer service powerhouse that:

  ✅ Handles unlimited customers simultaneously  
  ✅ Responds in under 3 seconds across ALL channels  
  ✅ Reduces support costs by 70% (proven ROI)  
  ✅ Works while you sleep - never miss another sale  
  ✅ Escalates complex issues to humans automatically  

  💎 What You Get

  ⚡ The Workflow
  Multi-Channel Integration**: WhatsApp, Telegram, Email, Website Chat
  GPT-4 Powered Intelligence**: Context-aware, professional responses
  Smart Escalation System**: Knows when humans are needed
  Conversation Memory**: Remembers every customer interaction
  Analytics Dashboard**: Track performance and ROI

  📋 Setup Materials
  Complete JSON Workflow** (drag & drop installation)
  Step-by-Step PDF Guide** (non-technical friendly)
  Troubleshooting Guide** (solve any issue)

  🔥 Why This Workflow is a Game-Changer

  Problem It Solves:
  Lost Sales**: 67% of customers abandon purchases due to poor support
  High Costs**: Average support agent costs $50,000+/year
  Limited Hours**: Miss 60% of inquiries outside business hours
  Inconsistent Quality**: Human agents have bad days
  Scaling Issues**: Can't hire fast enough for growth

  The Solution:
  Zero Response Delays**: Instant replies 24/7/365
  Consistent Excellence**: Perfect responses every time
  Unlimited Scaling**: Handle 1 or 10,000 customers
  Massive Cost Savings**: $500/month vs $50,000/year per agent
  Never Misses Anything**: Catches every single inquiry

  🛠️ Integrations & Tools Used

  AI & Automation:
  OpenAI GPT-4 Turbo** - Industry-leading AI responses
  n8n Workflow Engine** - Reliable automation backbone
  Smart Decision Trees** - Perfect escalation logic

  Communication Channels:
  WhatsApp Business API** - Reach 2+ billion users
  Telegram Bot API** - Lightning-fast messaging
  IMAP/SMTP Email** - Professional email support
  Webhook Integration** - Connect any chat widget

  Data & Analytics:
  Notion Database** - Conversation history & analytics
  Slack Integration** - Instant team notifications
  Custom Webhooks** - Connect to any CRM/tool

  Advanced Features:
  Multi-language Support** - Serve global customers
  Sentiment Analysis** - Detect frustrated customers
  Auto-categorization** - Organize inquiries automatically
  Performance Metrics** - Track ROI and efficiency

  🎯 Perfect For:

  E-commerce Businesses
  Handle pre-sale questions instantly
  Provide order status updates
  Resolve shipping inquiries
  Increase conversion rates by 34%

  SaaS Companies
  Technical support automation
  Onboarding assistance
  Feature explanations
  Reduce churn by 28%

  Service Businesses
  Appointment scheduling
  Service inquiries
  Quote requests
  Increase booking rates by 45%

  Digital Agencies
  Client communication
  Project updates
  Scope clarifications
  Improve client satisfaction by 52%

  ⚡ Installation is RIDICULOUSLY Easy

  Step 1: Import JSON (2 minutes)
  Download the workflow file
  Import into your n8n instance
  Activate the workflow

  Step 2: Configure APIs (10 minutes)
  Add your OpenAI API key
  Connect your messaging accounts
  Set up email credentials

  Step 3: Test & Launch (5 minutes)
  Send test messages
  Verify responses
  Go live and start saving money!

  Total Setup Time: Under 20 minutes  
  Technical Skill Required: None (detailed guide included)  

  🔒 Enterprise-Grade Security & Reliability

  Security Features:
  End-to-end encryption** for all communications
  API rate limiting** to prevent abuse
  Data privacy compliance** (GDPR ready)
  Secure credential storage** in n8n vault

  Reliability Features:
  99.9% uptime** with proper n8n hosting
  Automatic error handling** and recovery
  Failover to human agents** when needed
  Complete conversation logging** for compliance

  Scalability:
  Handles 1000+ concurrent chats**
  Processes 10,000+ messages/day**
  Auto-scales with your business**
  No performance degradation**

nodes_used:
  ["n8n-nodes-base.emailSend","n8n-nodes-base.httpRequest","n8n-nodes-base.notion","n8n-nodes-base.openAi"]

workflow_json:
  {"name":"AI Customer Support Agent Multi-Channel","tags":[{"id":"ai-agent","name":"AI Agent","createdAt":"2025-01-01T00:00:00.000Z","updatedAt":"2025-01-01T00:00:00.000Z"},{"id":"customer-support","name":"Customer Support","createdAt":"2025-01-01T00:00:00.000Z","updatedAt":"2025-01-01T00:00:00.000Z"},{"id":"automation","name":"Automation","createdAt":"2025-01-01T00:00:00.000Z","updatedAt":"2025-01-01T00:00:00.000Z"}],"nodes":[{"id":"sticky_note_intro","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-200,200],"parameters":{"content":""},"typeVersion":1},{"id":"whatsapp_webhook","name":"WhatsApp Webhook","type":"n8n-nodes-base.webhook","position":[200,300],"webhookId":"whatsapp-support-webhook","parameters":{},"typeVersion":2},{"id":"telegram_webhook","name":"Telegram Webhook","type":"n8n-nodes-base.webhook","position":[200,450],"webhookId":"telegram-support-webhook","parameters":{},"typeVersion":2},{"id":"email_trigger","name":"Email Trigger","type":"n8n-nodes-base.emailReadImap","position":[200,600],"parameters":{},"typeVersion":2},{"id":"normalize_data","name":"Normalize Message Data","type":"n8n-nodes-base.set","position":[500,450],"parameters":{},"typeVersion":3.4},{"id":"get_conversation_history","name":"Get Conversation History","type":"n8n-nodes-base.notion","position":[800,450],"parameters":{},"typeVersion":2},{"id":"sticky_memory","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[780,200],"parameters":{"content":""},"typeVersion":1},{"id":"openai_agent","name":"OpenAI Support Agent","type":"n8n-nodes-base.openAi","position":[1100,450],"parameters":{},"typeVersion":1.3},{"id":"sticky_ai","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[1080,80],"parameters":{"content":""},"typeVersion":1},{"id":"check_escalation","name":"Check if Escalation Needed","type":"n8n-nodes-base.if","position":[1400,450],"parameters":{},"typeVersion":2},{"id":"format_response","name":"Format AI Response","type":"n8n-nodes-base.set","position":[1700,350],"parameters":{},"typeVersion":3.4},{"id":"send_whatsapp_response","name":"Send WhatsApp Response","type":"n8n-nodes-base.httpRequest","position":[2000,200],"parameters":{},"typeVersion":4.2},{"id":"send_telegram_response","name":"Send Telegram Response","type":"n8n-nodes-base.httpRequest","position":[2000,350],"parameters":{},"typeVersion":4.2},{"id":"send_email_response","name":"Send Email Response","type":"n8n-nodes-base.emailSend","position":[2000,500],"parameters":{},"typeVersion":2.1},{"id":"save_conversation","name":"Save Conversation","type":"n8n-nodes-base.notion","position":[2300,450],"parameters":{},"typeVersion":2},{"id":"notify_human_agents","name":"Notify Human Agents","type":"n8n-nodes-base.httpRequest","position":[1700,600],"parameters":{},"typeVersion":4.2},{"id":"sticky_escalation","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[1620,720],"parameters":{"content":""},"typeVersion":1},{"id":"sticky_analytics","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[2280,200],"parameters":{"content":""},"typeVersion":1},{"id":"webhook_response","name":"Webhook Response","type":"n8n-nodes-base.respondToWebhook","position":[2600,450],"parameters":{},"typeVersion":1.1}],"pinData":{},"settings":{"executionOrder":"v1"},"updatedAt":"2025-01-01T00:00:00.000Z","versionId":"1","staticData":null,"connections":{"openai_agent":{"main":[[{"node":"check_escalation","type":"main","index":0}]]},"email_trigger":{"main":[[{"node":"normalize_data","type":"main","index":0}]]},"normalize_data":{"main":[[{"node":"get_conversation_history","type":"main","index":0}]]},"format_response":{"main":[[{"node":"send_whatsapp_response","type":"main","index":0},{"node":"send_telegram_response","type":"main","index":0},{"node":"send_email_response","type":"main","index":0}]]},"check_escalation":{"main":[[{"node":"format_response","type":"main","index":0}],[{"node":"format_response","type":"main","index":0},{"node":"notify_human_agents","type":"main","index":0}]]},"telegram_webhook":{"main":[[{"node":"normalize_data","type":"main","index":0}]]},"whatsapp_webhook":{"main":[[{"node":"normalize_data","type":"main","index":0}]]},"save_conversation":{"main":[[{"node":"webhook_response","type":"main","index":0}]]},"send_email_response":{"main":[[{"node":"save_conversation","type":"main","index":0}]]},"send_telegram_response":{"main":[[{"node":"save_conversation","type":"main","index":0}]]},"send_whatsapp_response":{"main":[[{"node":"save_conversation","type":"main","index":0}]]},"get_conversation_history":{"main":[[{"node":"openai_agent","type":"main","index":0}]]}},"triggerCount":3}


name: AI-Powered Telegram & WhatsApp Business Agent Workflow
author_name: Amanda Benks
author_username: amanda
categories: []
created_at: 2025-06-25T18:51:37.067Z
updated_at: 2025-06-25T18:51:37.067Z
url: https://n8n.io/workflows/5311
scraped_at: 2025-07-06 21:16:30
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  Deliver seamless, AI-driven customer support on Telegram and WhatsApp—powered by GPT-4 Turbo and n8n.

  🌟 Key Features
  Unified Messaging:** Receive and normalize messages from both Telegram (via Bot Trigger) and WhatsApp (via Webhook).  
  Contextual AI Responses:** Build customer context from Google Sheets, then craft personalized replies with GPT-4 Turbo.  
  Smart Routing:** Automatically detect platform and send replies with platform-appropriate formatting (HTML for Telegram, plain for WhatsApp).  
  Intent Detection & Escalation:** Flag orders, appointments or complex queries and trigger Slack notifications for human handoff.  
  Comprehensive Logging:** Append every interaction to a “conversations” sheet and upsert customer profiles in a “customers” sheet.  

  📋 Prerequisites
  n8n instance (self-hosted or n8n Cloud)  
  Credentials:
     OpenAI API key  
     Telegram Bot Token  
     WhatsApp Business API credentials (WHATSAPP_PHONE_ID)  
     Google Sheets service-account credentials  
     Slack Incoming Webhook URL  
  Google Sheets Setup:
     customers sheet with columns: user_id, user_name, previousOrders, lastInteraction, preferences, conversationHistory  
     conversations sheet with columns: user_id, user_name, platform, message, ai_response, timestamp, needs_escalation, is_order, is_appointment  

  🚀 Setup & Usage
  Import the provided JSON into your n8n editor.  
  Configure each node’s credentials in n8n’s Credentials panel.  
  Set the following Workflow Variables:
     GOOGLE_SHEET_ID  
     WHATSAPP_PHONE_ID  
  Activate the Telegram Bot Trigger and WhatsApp Webhook nodes.  
  Test by messaging your bot on Telegram and WhatsApp.  

  🔍 How It Works
  Trigger: Listens for new Telegram updates or WhatsApp webhook calls.  
  Normalize Message: Standardizes payload into { user_id, user_name, message_text, platform, chat_id, timestamp }.  
  Get Customer Data: Reads from “customers” sheet to fetch past history and order count.  
  Build AI Context: Merges incoming message with customer info and history.  
  AI Assistant: Sends context to GPT-4 Turbo (temperature 0.8, maxTokens 800).  
  Process Response: Cleans formatting, identifies intents (order, appointment), and sets escalation flags.  
  Platform Router: Routes reply to the appropriate “Send Telegram” or “Send WhatsApp” node.  
  Log Conversation: Appends each message and response to the “conversations” sheet.  
  Update Customer: Increments previousOrders, updates last interaction timestamp, and saves a snippet of the latest message.  
  Escalation: If flagged, posts a formatted alert to your Slack channel for immediate attention.  

  Empower your business with 24/7 AI-powered support—save time, increase conversions, and ensure no customer inquiry goes unanswered.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.openAi"]

workflow_json:
  {"name":"AI Telegram & WhatsApp Business Agent","tags":[{"id":"telegram","name":"Telegram","createdAt":"2025-01-01T00:00:00.000Z","updatedAt":"2025-01-01T00:00:00.000Z"},{"id":"whatsapp","name":"WhatsApp","createdAt":"2025-01-01T00:00:00.000Z","updatedAt":"2025-01-01T00:00:00.000Z"},{"id":"ai-agent","name":"AI Agent","createdAt":"2025-01-01T00:00:00.000Z","updatedAt":"2025-01-01T00:00:00.000Z"},{"id":"customer-service","name":"Customer Service","createdAt":"2025-01-01T00:00:00.000Z","updatedAt":"2025-01-01T00:00:00.000Z"}],"nodes":[{"id":"intro_sticky","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-240,180],"parameters":{"content":""},"typeVersion":1},{"id":"telegram_trigger","name":"Telegram Bot","type":"n8n-nodes-base.telegramTrigger","position":[160,280],"webhookId":"telegram-ai-agent","parameters":{},"typeVersion":1.1},{"id":"whatsapp_webhook","name":"WhatsApp Webhook","type":"n8n-nodes-base.webhook","position":[160,420],"webhookId":"whatsapp-ai-webhook","parameters":{},"typeVersion":2},{"id":"normalize_message","name":"Normalize Message Data","type":"n8n-nodes-base.set","position":[460,350],"parameters":{},"typeVersion":3.4},{"id":"processing_sticky","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[440,20],"parameters":{"content":""},"typeVersion":1},{"id":"get_customer_data","name":"Get Customer History","type":"n8n-nodes-base.googleSheets","position":[760,350],"parameters":{},"typeVersion":4.4},{"id":"build_context","name":"Build AI Context","type":"n8n-nodes-base.code","position":[1060,350],"parameters":{},"typeVersion":2},{"id":"intelligence_sticky","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[740,40],"parameters":{"content":""},"typeVersion":1},{"id":"ai_assistant","name":"AI Business Assistant","type":"n8n-nodes-base.openAi","position":[1360,350],"parameters":{},"typeVersion":1.3},{"id":"ai_sticky","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[1340,-20],"parameters":{"content":""},"typeVersion":1},{"id":"process_response","name":"Process AI Response","type":"n8n-nodes-base.code","position":[1660,350],"parameters":{},"typeVersion":2},{"id":"platform_router","name":"Platform Router","type":"n8n-nodes-base.if","position":[1960,350],"parameters":{},"typeVersion":2},{"id":"send_telegram","name":"Send Telegram Message","type":"n8n-nodes-base.telegram","position":[2260,280],"parameters":{},"typeVersion":1.2},{"id":"send_whatsapp","name":"Send WhatsApp Message","type":"n8n-nodes-base.httpRequest","position":[2260,420],"parameters":{},"typeVersion":4.2},{"id":"delivery_sticky","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[2240,60],"parameters":{"content":""},"typeVersion":1},{"id":"log_conversation","name":"Log Conversation","type":"n8n-nodes-base.googleSheets","position":[2560,350],"parameters":{},"typeVersion":4.4},{"id":"update_customer","name":"Update Customer Record","type":"n8n-nodes-base.googleSheets","position":[2860,350],"parameters":{},"typeVersion":4.4},{"id":"check_escalation","name":"Check Escalation","type":"n8n-nodes-base.if","position":[2560,200],"parameters":{},"typeVersion":2},{"id":"notify_team","name":"Notify Support Team","type":"n8n-nodes-base.httpRequest","position":[2860,200],"parameters":{},"typeVersion":4.2},{"id":"analytics_sticky","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[2540,480],"parameters":{"content":""},"typeVersion":1},{"id":"webhook_response","name":"Webhook Response","type":"n8n-nodes-base.respondToWebhook","position":[3160,420],"parameters":{},"typeVersion":1.1}],"pinData":{},"settings":{"executionOrder":"v1"},"updatedAt":"2025-01-01T00:00:00.000Z","versionId":"1","staticData":null,"connections":{"ai_assistant":{"main":[[{"node":"process_response","type":"main","index":0}]]},"build_context":{"main":[[{"node":"ai_assistant","type":"main","index":0}]]},"send_telegram":{"main":[[{"node":"log_conversation","type":"main","index":0}]]},"send_whatsapp":{"main":[[{"node":"log_conversation","type":"main","index":0}]]},"platform_router":{"main":[[{"node":"send_telegram","type":"main","index":0}],[{"node":"send_whatsapp","type":"main","index":0}]]},"update_customer":{"main":[[{"node":"webhook_response","type":"main","index":0}]]},"check_escalation":{"main":[[{"node":"notify_team","type":"main","index":0}],[]]},"log_conversation":{"main":[[{"node":"update_customer","type":"main","index":0}]]},"process_response":{"main":[[{"node":"platform_router","type":"main","index":0},{"node":"check_escalation","type":"main","index":0}]]},"telegram_trigger":{"main":[[{"node":"normalize_message","type":"main","index":0}]]},"whatsapp_webhook":{"main":[[{"node":"normalize_message","type":"main","index":0}]]},"get_customer_data":{"main":[[{"node":"build_context","type":"main","index":0}]]},"normalize_message":{"main":[[{"node":"get_customer_data","type":"main","index":0}]]}},"triggerCount":2}


name: Generate Viral Bigfoot Vlog Videos with Veo 3
author_name: Lucas Walter
author_username: lucaswalter
categories: []
created_at: 2025-06-25T19:57:53.096Z
updated_at: 2025-06-25T19:57:53.096Z
url: https://n8n.io/workflows/5312
scraped_at: 2025-07-06 21:16:30
description:
  Transform simple ideas into viral-ready Bigfoot vlogs! This automated workflow creates charming 8-scene video content featuring "Sam" the Bigfoot - a lovable, outdoorsy character inspired by popular YouTube adventure channels.

  How It Works

  The workflow transforms your creative concept into professional video content through three automated stages:
  Story Generation - AI creates an 8-scene narrative arc featuring Sam the Bigfoot, complete with character-consistent dialogue and engaging plot development
  Human Approval - Review and approve the generated storyline via Slack before proceeding to video production
  Video Production - Each scene is automatically converted into 8-second video clips using Google's VEO 3 AI, then uploaded to Google Drive for easy access

  Required Credentials

  Anthropic API - Add your Claude API key for story generation
  FAL API - Configure your FAL.ai key for VEO 3 video generation
  Slack OAuth - Set up Slack app with channel permissions for approvals
  Google Drive OAuth - Connect your Google Drive for video storage

  Configuration Steps

  Import the workflow into your n8n instance
  Update Slack channel ID in the notification nodes to match your desired channel
  Set Google Drive folder - Update the folder ID where videos should be stored
  Test the form trigger - The workflow starts with a web form for video ideas
  Customize character (optional) - Modify Sam's personality in the narrative prompts

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.slack","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.outputParserStructured"]

workflow_json:
  {"id":"iwOnqM2DwVwn5nmh","meta":{"instanceId":"06e5009344f682419c20ccd4ecdcb5223bbb91761882af93ac6d468dbc2cbf8d","templateCredsSetupCompleted":true},"name":"The Recap AI - VEO 3 Bigfoot Video Generator","tags":[{"id":"aZMw5JzELHKfaOAb","name":"YouTube Video","createdAt":"2025-06-09T22:48:17.291Z","updatedAt":"2025-06-09T22:48:17.291Z"}],"nodes":[{"id":"44414dae-70c3-4fb8-afcd-add84d3441be","name":"form_trigger","type":"n8n-nodes-base.formTrigger","position":[-40,0],"webhookId":"fd4a4cba-2667-4694-9c5e-00808d9a217b","parameters":{"options":{},"formTitle":"Bigfoot Video Idea","formFields":{"values":[{"fieldLabel":"Bigfoot Video Idea","placeholder":"Describe the high level idea for your bigfoot vlog","requiredField":true}]}},"typeVersion":2.2},{"id":"c14d5bcf-fa03-40c2-b0b2-48fa2261b8b4","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-60,-100],"parameters":{"color":4,"width":1780,"height":600,"content":"## 1. Write Video Script"},"typeVersion":1},{"id":"08670923-c438-4b7b-b2f3-3d49cadd20ec","name":"claude-4-sonnet","type":"@n8n/n8n-nodes-langchain.lmChatAnthropic","position":[740,360],"parameters":{"model":{"__rl":true,"mode":"list","value":"claude-sonnet-4-20250514","cachedResultName":"Claude 4 Sonnet"},"options":{}},"credentials":{"anthropicApi":{"id":"l40BD4ZshdbnRGbC","name":"Anthropic"}},"typeVersion":1.3},{"id":"158f12ec-94a0-43d5-b9dd-13c60b529ebd","name":"split_scenes","type":"n8n-nodes-base.splitOut","position":[740,0],"parameters":{"options":{},"fieldToSplitOut":"output.scenes"},"typeVersion":1},{"id":"6da1699e-5ae9-4979-8007-aa80353d91e3","name":"scene_director","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[1120,0],"parameters":{"text":"=### **IDENTITY & GOAL**\n\nYou are an expert Scene Director for a YouTube video series. Your sole function is to take a simple `Scene Brief` and expand it into a detailed, production-ready video script. You must strictly adhere to the `Character Bible`, `Series Style Guide`, and `Output Template` provided below.\n\n### **THE SERIES BIBLE**\n\nThis is the non-negotiable source of truth for the series' character and style.\n\n#### **[Character Bible: \"Sam\" the Bigfoot]**\n\n* **Identity:** A gentle giant named \"Sam.\" He is an endlessly curious, optimistic, and friendly explorer discovering the human world.\n* **Vibe:** A heartwarming, slightly clumsy, outdoorsy influencer. He finds joy in small details and is filled with childlike wonder. His dialog and lines MUST be based around the \"Outdoor Boys\" YouTube channel and he must speak like the main character from that Channel. Avoid super generic language.\n* **Voice & Tone:** Consistently jolly and warm. His language is simple, and he sometimes gently misuses human slang (e.g., \"keep the quads poppin'\"). PG-rated; mild exasperations like \"geez\" or \"oh, nuts\" are authentic.\n* **Core Physicality (Lock Across All Scenes):**\n    * **Species:** 8-foot male Bigfoot.\n    * **Fur:** Shaggy, cedar-brown (`#6d6048`) with faint moss specks. The fur on his cheeks and shoulders is fluffier, creating a soft, \"huggable\" silhouette.\n    * **Face:** Features soft, medium-amber eyes with natural catch-lights only (no artificial glow). He has rounded cheeks, a broad nose, and short, blunt lower canines visible when he smiles.\n    * **Hands:** Dark leathery palms with 4-inch black claws. One paw is always holding his selfie stick.\n\n#### **[Series Style Guide]**\n\n* **Primary Directive:** Every scene must create audience affection for Sam by showcasing his charm, gentle humor, or vulnerability.\n* **Camera:** All shots are 16:9 horizontal from a selfie-stick perspective held by Sam. The camera is always on *him*, not a POV shot from his eyes.\n* **Scene Duration and Length:** All scenes must be EXACTLY 8 seconds in length. Scenes may not be longer than 8 seconds.\n* **Visual Style:** Must feel like authentic, slightly shaky \"found footage.\" The hand-held wobble amplitude should match the reference clip provided in the example. I would expect Sam the bigfoot to be walking and there to be movement in some scenes.\n* **Core Technical Specs (Lock Across All Scenes):**\n    * **Resolution & Framerate:** 4K UHD @ 29.97 fps.\n    * **Lens & Shutter:** 24mm equivalent lens at ƒ/2.8, with a 1/60s shutter to create subtle motion blur.\n    * **Captions / Subtitles:** You MUST NOT include captions or subtitles in your final rendered output.\n\nIT IS EXTREMELY IMPORTANT THAT YOU DO NOT INCLUDE ANY SUBTITLES, CLOSED CAPTIONS, CAPTIONS OR ANY OTHER SORT OF TEXT THAT APPEARS WHEN THE SAM CHARACTER IS SPEAKING.\n\nIT IS ALSO EXTREMELY IMPORTANT THAT YOU AVOID ADDING ANY LABELS TO THE FINAL VIDEO SUCH AS THE SCENE TITLE AND TIMESTAMPS.\n\n### **TASK: GENERATE SCENE SCRIPT**\n\n1.  You will be given a `[Scene Brief]` containing the core idea.\n2.  Your output must be a single, complete scene script that perfectly matches the structure, formatting, and markdown of the `[Output Template]` below. Do not add any conversational text before or after the script.\n\n### **[Output Template]**\n\n```markdown\n# Scene {SceneNumber}  ▸  \"{SceneTitle}\"  ▸  {StartTime} – {EndTime} s\n#\n# {OneLineSummary}\n# {CharacterAction}. Must speak the line verbatim. Maintains all [Character Bible] and [Series Style Guide] attributes.\n\nSCENE DESCRIPTION\n-----------------\n{DetailedParagraphDescription: Setting, character action, mood, and interaction with the environment.}\n\nTECHNICAL SPECS\n---------------\n• Duration {Duration} s • 29.97 fps • 4 K UHD • 16 : 9 horizontal  \n• Lens 24 mm eq, ƒ/2.8 • Shutter 1/60 s (subtle motion blur)  \n• Hand-held wobble amplitude identical to reference clip.\n\nSUBJECT DETAILS  (LOCK ACROSS ALL CUTS)\n---------------------------------------\n• 8-ft male Bigfoot, cedar-brown shaggy fur #6d6048 with faint moss specks.  \n• Fluffier cheek & shoulder fur → plush, huggable silhouette.  \n• Eyes: soft medium-amber, natural catch-lights only (no glow).  \n• Face: rounded cheeks, gentle smile crease; broad flat nose; short blunt lower canines.  \n• Hands: dark leathery palms, 4-in black claws; **{PawDescription: e.g., right paw holds object, left paw holds selfie stick}**\n• Friendly, lovable, gentle vibe.\n\nCAMERA MOTION\n-------------\n{TimestampedCameraMovement: A bulleted or timed list of camera actions.}\n\nLIGHTING & GRADE\n----------------\n{LightingAndColorDescription: Time of day, light source, color palette, and any lens effects like grain or smudges.}\n\nATMOSPHERE FX\n-------------\n• {AtmosphericEffect1}  \n• {AtmosphericEffect2}\n\nAUDIO BED\n---------\n{AmbientSounds: A description of the background audio, environmental sounds, and non-speech character sounds.}\n\n### audio.speech  — MUST-SPEAK VERBATIM\nStart {SpeechStartTime} s — deep, gravelly yet warm male, neutral US accent, mild PG  \n\n\"{DialogueLine}\"\n\nEND FRAME\n---------\n{EndFrameDescription: What happens in the final moments, including any specific cuts or transitions.}\n\n### **[Scene Example #1]**\n\n# CUT 3  ▸  “Tree-Trunk Gym”  ▸  0 – 8 s\n#\n# Bigfoot balances on a fallen log while curling a hefty river-boulder,\n# selfie-stick POV.  Must speak BOTH short lines verbatim.  Maintains soft,\n# lovable design (natural amber eyes, plush fur) and reference-matched color grade.\n\nSCENE DESCRIPTION\n-----------------\nPOV selfie-stick vlog: In a sun-dappled glade, Bigfoot stands barefoot on a mossy\nfallen cedar trunk ~3 ft above ground.  He grips a 25-lb smooth river-boulder in\nhis right paw and performs a showy biceps curl while keeping balance.\n\nTECHNICAL SPECS\n---------------\n• Duration 8 s • 29.97 fps • 4 K UHD • 16 : 9 horizontal  \n• Lens 24 mm eq, ƒ/2.8 • Shutter 1/60 s (subtle motion blur)  \n• Hand-held wobble amplitude identical to reference clip.\n\nSUBJECT DETAILS  (LOCK ACROSS ALL CUTS)\n---------------------------------------\n• 8-ft male Bigfoot, cedar-brown shaggy fur #6d6048 with faint moss specks.  \n• Fluffier cheek & shoulder fur → plush, huggable silhouette.  \n• Eyes: soft medium-amber, natural catch-lights only (no glow).  \n• Face: rounded cheeks, gentle smile crease; broad flat nose; short blunt lower canines.  \n• Hands: dark leathery palms, 4-in black claws; **right paw holds boulder, left paw holds 12-in carbon selfie stick.**  \n• Friendly, lovable, gentle vibe.\n\nCAMERA MOTION\n-------------\n0 – 2 s Stick frames Bigfoot full-body on log; slight wobble shows height.  \n2 – 5 s Bigfoot performs two slow boulder curls; log flexes under weight.  \n5 – 8 s Stick tilts slightly upward to capture grin + treetops; Bigfoot winks.\n\nLIGHTING & GRADE\n----------------\nLate-morning sunbeams dappling through cedars; teal-olive mids, warm highlights.\nGentle film grain; faint right-edge lens smudge (clone reference look).\n\nATMOSPHERE FX\n-------------\n• Specks of drifting pollen back-lit in sun.  \n• Occasional leaf flutter from breeze.\n\nAUDIO BED\n---------\nSoft forest ambience (songbirds, light wind), faint creak of log, grunt exertion,\nstone scrape when boulder lifts.\n\n### audio.speech  — MUST-SPEAK VERBATIM\nStart 01.0 s — deep, gravelly yet warm male, neutral US accent, mild PG  \n“Gotta keep the quads poppin’—swimsuit season never ends!”\n\nEND FRAME\n---------\nFreeze at 7.8 s with Bigfoot mid-curl, smiling at lens; insert one-frame white-noise\npop to maintain the series’ hard-cut rhythm.\n\n### **[Scene Example #2]**\n\n# SCENE 4  ▸  “Trail to the Lake”  ▸  0 – 8 s\n#\n# Selfie-stick POV. Bigfoot strolls through dense cedar woods toward a sun-sparkled\n# lake in the distance. **No spoken dialogue** in this beat—just ambient forest\n# sound and foot-fall crunches. Keeps reference camera-shake, color grade, and the\n# plush, lovable design.\n\nSCENE DESCRIPTION\n-----------------\nPOV selfie-stick vlog: Bigfoot walks along a pine-needle path, ferns brushing both\nsides. Sunbeams flicker through the canopy. At the 6-second mark the shimmering\nsurface of a lake appears through the trees; Bigfoot subtly tilts the stick to\nhint at the destination.\n\nTECHNICAL SPECS\n---------------\n• Duration 8 s • 29.97 fps • 4 K UHD • 16 : 9 horizontal  \n• Lens 24 mm eq, ƒ/2.8 • Shutter 1/60 s (subtle motion-blur)  \n• Hand-held wobble amplitude cloned from reference clip (small ±2° yaw/roll).\n\nSUBJECT DETAILS  (LOCK ACROSS ALL CUTS)\n---------------------------------------\n• 8-ft male Bigfoot, cedar-brown shaggy fur #6d6048 with faint moss specks.  \n• Fluffier cheek & shoulder fur → plush, huggable silhouette.  \n• **Eyes:** soft medium-amber, natural catch-lights only — no glow or excess brightness.  \n• Face: rounded cheeks, gentle smile crease; broad flat nose; short blunt lower canines.  \n• Hands: dark leathery palms, 4-inch black claws; right paw grips 12-inch carbon selfie stick.  \n• Friendly, lovable, gentle vibe.\n\nCAMERA MOTION\n-------------\n0 – 2 s Stick angled toward Bigfoot’s chest/face as he steps onto path.  \n2 – 6 s Smooth forward walk; slight vertical bob; ferns brush lens edges.  \n6 – 8 s Stick tilts ~20° left, revealing glinting lake through trees; light breeze ripples fur.\n\nLIGHTING & GRADE\n----------------\nLate-morning sun stripes across trail; teal-olive mid-tones, warm highlights,\ngentle film grain, faint right-edge lens smudge (clone reference look).\n\nATMOSPHERE FX\n-------------\n• Dust motes / pollen drifting in sunbeams.  \n• Occasional leaf flutter from breeze.\n\nAUDIO BED  (NO SPOKEN VOICE)\n----------------------------\nContinuous forest ambience: songbirds, light wind, distant woodpecker;\nsoft foot-crunch on pine needles; faint lake-lap audible after 6 s.\n\nEND FRAME\n---------\nFreeze at 7.8 s with lake shimmering through trees; insert one-frame white-noise\npop to preserve the series’ hard-cut rhythm.\n\n### **[Scene Example #3]**\n\n# SCENE 6  ▸  “Stone Funnel Trap”  ▸  0 – 8 s\n#\n# Selfie-stick POV. Bigfoot stands ankle-deep at a lake’s pebbled edge, demonstrates\n# an old trap: a V-shaped row of flat stones that channels minnows to a point.\n# He scoops one up and delivers two short lines **verbatim**. Reference camera\n# shake, color grade, and plush Bigfoot design.\n\nSCENE DESCRIPTION\n-----------------\nPOV selfie-stick vlog: Clear, knee-wide creek mouth where it meets the lake.\nFlat river stones form a tidy V-funnel in 6 in / 15 cm of water. Tiny minnows\nglisten inside. Bigfoot nudges stones, water ripples, then snatches a minnow and\nshows it to the camera.\n\nTECHNICAL SPECS\n---------------\n• Duration 8 s • 29.97 fps • 4 K UHD • 16 : 9 horizontal  \n• Lens 24 mm eq, ƒ/2.8 • Shutter 1/60 s (subtle motion-blur)  \n• Hand-held wobble amplitude cloned from the reference clip (±2° yaw/roll).\n\nSUBJECT DETAILS  (LOCK ACROSS ALL CUTS)\n---------------------------------------\n• 8-ft male Bigfoot, cedar-brown shaggy fur #6d6048 with faint moss specks.  \n• Fluffier cheek & shoulder fur → plush, huggable silhouette.  \n• **Eyes:** soft medium-amber, natural catch-lights only — no glow or excess brightness.  \n• Face: rounded cheeks, gentle smile crease; broad flat nose; short blunt lower canines.  \n• Hands: dark leathery palms, 4-inch black claws; right paw grips 12-inch carbon selfie stick.  \n• Friendly, lovable, gentle vibe.\n\nCAMERA MOTION\n-------------\n0 – 2 s Stick angles down: Bigfoot’s torso + stone V-trap fill frame; water sparkles.  \n2 – 5 s Left paw nudges stones; minnows funnel; slight shake.  \n5 – 8 s Quick scoop! Bigfoot lifts minnow close to lens, tilts stick up to face,\n         delivers lines while smiling.\n\nLIGHTING & GRADE\n----------------\nMid-morning sun; light dapples lake surface; teal-olive mid-tones, warm highlights,\ngentle film grain, faint right-edge lens smudge (clone reference look).\n\nATMOSPHERE FX\n-------------\n• Water ripple highlights; a few drifting pollen motes back-lit.  \n• Tiny splash droplets when minnow is lifted.\n\nAUDIO BED\n---------\nForest-lake ambience: distant loon call, light breeze, soft lap of water,\nstone scrape at 2 s, splash at 5 s.\n\n### audio.speech  — MUST-SPEAK VERBATIM\nStart 02.0 s — deep, gravelly yet warm male, neutral US accent  \n\n“Old-school fish funnel, folks—\n—works better than Wi-Fi.”\n\nEND FRAME\n---------\nFreeze at 7.8 s on Bigfoot’s grin and wriggling minnow; insert one-frame\nwhite-noise pop to maintain the series’ hard-cut rhythm.\n\n\n### Scene Brief\n\nVideo Title: {{ $('narrative_writer').item.json.output.vlogTitle }}\nVideo Concept: {{ $('narrative_writer').item.json.output.concept }}\nScene #{{ $json.sceneNumber }}\nScene Narrative: {{ $json.narrative }}\nScene Duration (Seconds): {{ $json.durationSeconds }} Seconds\nScene Timestamp Range: {{ $json.timestamp }}","batching":{},"promptType":"define"},"typeVersion":1.7},{"id":"5f018683-4a3b-4521-8080-7cb09a57295d","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[-60,520],"parameters":{"width":1780,"height":320,"content":"## 2. Get Human Approval"},"typeVersion":1},{"id":"e4951ebb-486c-474a-8cc2-87d63f485448","name":"send_and_wait","type":"n8n-nodes-base.slack","position":[720,640],"webhookId":"3729d6f7-237a-42c2-85a9-8135eeb08d0e","parameters":{"select":"channel","message":"=Please approve or deny the above story in order to proceed with the video.","options":{},"channelId":{"__rl":true,"mode":"list","value":"C08KC39K8DR","cachedResultName":"ai-tools-content"},"operation":"sendAndWait","authentication":"oAuth2","approvalOptions":{"values":{"approvalType":"double"}}},"credentials":{"slackOAuth2Api":{"id":"iKdTzmZ6YuYaaRG4","name":"Slack (OAuth)"}},"typeVersion":2.3},{"id":"bba2bbdf-6074-443c-b794-5daf77fb8c42","name":"aggregate_scenes","type":"n8n-nodes-base.aggregate","position":[-40,640],"parameters":{"options":{},"fieldsToAggregate":{"fieldToAggregate":[{"fieldToAggregate":"scene_prompt"}]}},"typeVersion":1},{"id":"b9e8646f-58d9-4081-ab77-d4c72189a869","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-60,860],"parameters":{"color":6,"width":1780,"height":580,"content":"## 3. Generate Video"},"typeVersion":1},{"id":"9ec0ba2c-50bd-4002-866c-338cacc8eaff","name":"set_scene_prompts","type":"n8n-nodes-base.set","position":[1540,0],"parameters":{"options":{},"assignments":{"assignments":[{"id":"4e52f036-9f53-4ab0-ae90-bdc6e617bf50","name":"scene_prompt","type":"string","value":"={{ $json.text }}"}]}},"typeVersion":3.4},{"id":"0d9547fb-f9be-49a7-af71-77f7c884d412","name":"reset_scene_prompts","type":"n8n-nodes-base.set","position":[1160,640],"parameters":{"options":{},"assignments":{"assignments":[{"id":"fa0270fb-5c1a-45f5-8f12-23759f4c829d","name":"scene_prompts","type":"array","value":"={{ $('aggregate_scenes').item.json.scene_prompt }}"}]}},"typeVersion":3.4},{"id":"45031184-247f-4746-8c09-ac55eda27047","name":"split_scene_prompts","type":"n8n-nodes-base.splitOut","position":[1540,640],"parameters":{"options":{},"fieldToSplitOut":"scene_prompts"},"typeVersion":1},{"id":"07009341-3ba4-47f4-8d5b-ba23b9498af5","name":"queue_create_video","type":"n8n-nodes-base.httpRequest","position":[360,1140],"parameters":{"url":"https://queue.fal.run/fal-ai/veo3","method":"POST","options":{},"jsonBody":"={\n  \"prompt\": \"{{ $node[\"set_current_prompt\"].json.prompt }}\",\n  \"aspect_ratio\": \"16:9\",\n  \"duration\": \"8s\",\n  \"generate_audio\": true\n}","sendBody":true,"specifyBody":"json","authentication":"genericCredentialType","genericAuthType":"httpHeaderAuth"},"credentials":{"httpHeaderAuth":{"id":"UTIO1750OW5kD30c","name":"FAL API"}},"typeVersion":4.2},{"id":"041cd3c4-9053-414f-a49f-d988c3383d27","name":"wait","type":"n8n-nodes-base.wait","position":[560,1140],"webhookId":"5bfe0a88-1783-4d7e-8beb-870e7d2e6d1f","parameters":{"amount":10},"typeVersion":1.1},{"id":"8ec5168d-1420-4be5-a781-88499ab88bb9","name":"fetch_status","type":"n8n-nodes-base.httpRequest","position":[740,1140],"parameters":{"url":"=https://queue.fal.run/fal-ai/veo3/requests/{{ $node[\"queue_create_video\"].json.request_id }}/status","options":{},"authentication":"genericCredentialType","genericAuthType":"httpHeaderAuth"},"credentials":{"httpHeaderAuth":{"id":"UTIO1750OW5kD30c","name":"FAL API"}},"typeVersion":4.2},{"id":"d7b65522-6643-4ec3-b7e9-6d705b31dbaa","name":"check_status","type":"n8n-nodes-base.if","position":[900,1140],"parameters":{"options":{},"conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"64ce8054-03df-4939-90b8-c05fbe6035a7","operator":{"name":"filter.operator.equals","type":"string","operation":"equals"},"leftValue":"={{ $json.status }}","rightValue":"COMPLETED"}]}},"typeVersion":2.2},{"id":"3f46ebb0-93b5-49e1-ba1c-e4a0a4176197","name":"fetch_result","type":"n8n-nodes-base.httpRequest","position":[1160,1220],"parameters":{"url":"=https://queue.fal.run/fal-ai/veo3/requests/{{ $node[\"queue_create_video\"].json.request_id }}","options":{},"authentication":"genericCredentialType","genericAuthType":"httpHeaderAuth"},"credentials":{"httpHeaderAuth":{"id":"UTIO1750OW5kD30c","name":"FAL API"}},"typeVersion":4.2},{"id":"3a00c60f-5ff3-4552-817d-4942a2e500f5","name":"download_result_video","type":"n8n-nodes-base.httpRequest","position":[1360,1220],"parameters":{"url":"={{ $json.video.url }}","options":{"response":{"response":{"responseFormat":"file"}}}},"typeVersion":4.2},{"id":"ab3b734e-af1c-40c2-9a7d-db0f1afd1f6d","name":"upload_video","type":"n8n-nodes-base.googleDrive","position":[1540,1220],"parameters":{"name":"=scene_{{ $runIndex + 1 }}.mp4","driveId":{"__rl":true,"mode":"list","value":"My Drive","cachedResultUrl":"https://drive.google.com/drive/my-drive","cachedResultName":"My Drive"},"options":{},"folderId":{"__rl":true,"mode":"url","value":"https://drive.google.com/drive/folders/1Lf84YrGu456naiaclZRp1ARMZdQUKJj8"}},"credentials":{"googleDriveOAuth2Api":{"id":"PgwI1k1VFnoEhOi6","name":"Google Drive account"}},"typeVersion":3},{"id":"060008bc-569b-4a83-b956-914d6c7f0afa","name":"send_completion_msg","type":"n8n-nodes-base.slack","position":[1540,980],"webhookId":"5442cf5d-27cf-49c8-8916-dda0fcff1a96","parameters":{"text":"=*Video Generation Complete!*\n\nVideo Title: {{ $('narrative_writer').item.json.output.vlogTitle }}\nVideo Concept: {{ $('narrative_writer').item.json.output.concept }}\n\nGoogle Drive Link: https://drive.google.com/drive/folders/1Lf84YrGu456naiaclZRp1ARMZdQUKJj8","select":"channel","channelId":{"__rl":true,"mode":"list","value":"C08KC39K8DR","cachedResultName":"ai-tools-content"},"otherOptions":{"includeLinkToWorkflow":false},"authentication":"oAuth2"},"credentials":{"slackOAuth2Api":{"id":"iKdTzmZ6YuYaaRG4","name":"Slack (OAuth)"}},"typeVersion":2.3},{"id":"351b0dc5-276b-4759-bed9-2db98e233219","name":"narrative_writer","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[220,0],"parameters":{"text":"=**Role:** You are a creative director specializing in short-form, character-driven video content.\n\n**Goal:** Generate a storyboard outline for a short vlog based on a user-provided concept. The output must strictly adhere to the Persona, Creative Mandate, and Output Specification defined below.\n\n---\n\n### **[Persona: Bigfoot the Vlogger]**\n\n* **Identity:** A gentle giant named \"Sam,\" who is an endlessly curious and optimistic explorer. His vibe is that of a friendly, slightly clumsy, outdoorsy influencer discovering the human world for the first time.\n* **Voice & Tone:** Consistently jolly, heartwarming, and filled with childlike wonder. He is easily impressed and finds joy in small details. His language is simple, and he might gently misuse human slang. PG-rated, but occasional mild exasperation like \"geez\" or \"oh, nuts\" is authentic. His dialog and lines MUST be based around the \"Outdoor Boys\" YouTube channel and he must speak like the main character from that Channel. Avoid super generic language.\n* **Physicality:**\n    * An 8-foot male with shaggy, cedar-brown fur (`#6d6048`) and faint moss specks.\n    * His silhouette is soft and \"huggable\" due to fluffy fur on his cheeks and shoulders.\n    * Features soft, medium-amber eyes, rounded cheeks, a broad nose, and short, blunt lower canines visible when he smiles.\n    * He holds a simple selfie stick at all times.\n\n---\n\n### **[Creative Mandate]**\n\n* **Visual Style:** All scenes are shot 16:9 from a selfie-stick perspective held by Bigfoot. The style must feel like authentic, slightly shaky \"found footage.\" The camera is always on him, not his POV.\n* **Narrative Goal:** The primary objective is to create audience affection. Each scene must showcase Bigfoot's charm through his gentle humor, endearing discoveries, or moments of vulnerability. The 8-scene arc must have a satisfying and heartwarming payoff.\n\n---\n\n### **[Output Specification]**\n\n* **Structure:** Provide a storyboard with exactly 8 sequential scenes, formatted as shown below.\n* **Introduction Rule:** Scene 1 **must** be a direct-to-camera introduction. In it, Bigfoot should enthusiastically greet his viewers (e.g., \"Hey everybody!\" or \"Hi friends!\") and briefly state the goal or adventure for the vlog, based on the user's concept.\n* **Duration:** Each scene represents 8 seconds of footage.\n* **Content per Scene:** For each scene, provide a single, descriptive paragraph. This paragraph must seamlessly weave together the visual action, Bigfoot's expressions, and his spoken dialogue. Each scene you create should be part of a cohesive story.\n\n* **Example Formats:**\n    * **SCENE 1 (0:00-0:08):** Sam the Bigfoot grins warmly into his selfie stick, the background slightly out of focus. He waves a large, furry hand and says, \"Hey friends, Sam here! Today, we're going to try and build a brand new shelter out of... well, whatever we can find! Wish me luck!\"\n    * **SCENE 3 (0:32-0:40):** Sam holds up a rusty, bent bicycle wheel, peering at it curiously with his head tilted. He tries to spin it, a look of concentration on his face. \"Hmm. This is a weird-looking rock. Very... holey. Not good for a wall, I don't think.\"\n\n---\n\n### **Task**\n\nUsing the rules above, create the storyboard outline for the following concept:\n\n{{ $json['Bigfoot Video Idea'] }}\n","batching":{},"promptType":"define","hasOutputParser":true},"typeVersion":1.7},{"id":"c17f5174-5dbe-4a15-abd4-0ab55a023d53","name":"send_narrative_msg","type":"n8n-nodes-base.slack","position":[320,640],"webhookId":"6722ef92-cbb7-49e1-af4d-c313e81cec64","parameters":{"text":"=*Title:* {{$node[\"narrative_writer\"].json.output.vlogTitle}}\n*Concept:* {{$node[\"narrative_writer\"].json.output.concept}}\n\n{{ $node[\"narrative_writer\"].json.output.scenes\n  .map(scene => `*Scene ${scene.sceneNumber}* | ${scene.timestamp}\n> ${scene.narrative}`)\n  .join(\"\\n\\n\")\n}}","select":"channel","channelId":{"__rl":true,"mode":"list","value":"C08KC39K8DR","cachedResultName":"ai-tools-content"},"otherOptions":{"includeLinkToWorkflow":false},"authentication":"oAuth2"},"credentials":{"slackOAuth2Api":{"id":"iKdTzmZ6YuYaaRG4","name":"Slack (OAuth)"}},"typeVersion":2.3},{"id":"90165a0e-c0b8-43d1-b8ef-d39b0b5ab80b","name":"iterate_prompts","type":"n8n-nodes-base.splitInBatches","position":[-40,1000],"parameters":{"options":{}},"typeVersion":3},{"id":"8b298f43-7ea3-4157-bce6-b6953e14fb26","name":"set_current_prompt","type":"n8n-nodes-base.set","position":[180,1140],"parameters":{"options":{},"assignments":{"assignments":[{"id":"77f5459c-bb75-43ad-8027-a7fdf790a9f4","name":"prompt","type":"string","value":"={{ $json.scene_prompts }}"}]}},"typeVersion":3.4},{"id":"a7bcf7bc-1ebd-4935-9298-b4e63ad63aa2","name":"narrative_parser","type":"@n8n/n8n-nodes-langchain.outputParserStructured","position":[300,220],"parameters":{"autoFix":true,"schemaType":"manual","inputSchema":"{\n  \"$schema\": \"http://json-schema.org/draft-07/schema#\",\n  \"title\": \"Vlog Storyboard\",\n  \"description\": \"A structured storyboard for a short vlog episode.\",\n  \"type\": \"object\",\n  \"required\": [\n    \"vlogTitle\",\n    \"concept\",\n    \"characterName\",\n    \"scenes\"\n  ],\n  \"properties\": {\n    \"vlogTitle\": {\n      \"description\": \"A creative and fun title for the vlog episode.\",\n      \"type\": \"string\"\n    },\n    \"concept\": {\n      \"description\": \"The user-provided concept for the vlog.\",\n      \"type\": \"string\"\n    },\n    \"characterName\": {\n      \"description\": \"The name of the protagonist.\",\n      \"type\": \"string\",\n      \"const\": \"Sam\"\n    },\n    \"scenes\": {\n      \"description\": \"An array of 10 scenes that form the storyboard.\",\n      \"type\": \"array\",\n      \"minItems\": 8,\n      \"maxItems\": 8,\n      \"items\": {\n        \"type\": \"object\",\n        \"required\": [\n          \"sceneNumber\",\n          \"timestamp\",\n          \"durationSeconds\",\n          \"narrative\"\n        ],\n        \"properties\": {\n          \"sceneNumber\": {\n            \"description\": \"The sequential number of the scene.\",\n            \"type\": \"integer\",\n            \"minimum\": 1,\n            \"maximum\": 8\n          },\n          \"timestamp\": {\n            \"description\": \"The time range of the scene in the vlog (e.g., '0:00-0:08').\",\n            \"type\": \"string\",\n            \"pattern\": \"^\\\\d{1,2}:\\\\d{2}-\\\\d{1,2}:\\\\d{2}$\"\n          },\n          \"durationSeconds\": {\n            \"description\": \"The duration of the scene in seconds.\",\n            \"type\": \"integer\",\n            \"const\": 8\n          },\n          \"narrative\": {\n            \"description\": \"A single, descriptive paragraph weaving together the visual action, Sam's expressions, and his spoken dialogue.\",\n            \"type\": \"string\"\n          }\n        }\n      }\n    }\n  }\n}"},"typeVersion":1.3},{"id":"918e2d12-a924-409c-8b02-97f42847e1d6","name":"aggregate_video_results","type":"n8n-nodes-base.aggregate","position":[1160,980],"parameters":{"options":{},"aggregate":"aggregateAllItemData"},"typeVersion":1}],"active":false,"pinData":{"fetch_result":[{"json":{"video":{"url":"https://v3.fal.media/files/lion/Xe-YfU62R-K1jEAo_Re1N_output.mp4","file_name":"output.mp4","file_size":5210998,"content_type":"video/mp4"}}}],"fetch_status":[{"json":{"logs":null,"status":"COMPLETED","metrics":{"inference_time":95.72970294952393},"cancel_url":"https://queue.fal.run/fal-ai/veo3/requests/7227003c-a9a6-4024-99c7-18d960357941/cancel","request_id":"7227003c-a9a6-4024-99c7-18d960357941","status_url":"https://queue.fal.run/fal-ai/veo3/requests/7227003c-a9a6-4024-99c7-18d960357941/status","response_url":"https://queue.fal.run/fal-ai/veo3/requests/7227003c-a9a6-4024-99c7-18d960357941"}}],"queue_create_video":[{"json":{"logs":null,"status":"IN_QUEUE","metrics":{},"cancel_url":"https://queue.fal.run/fal-ai/veo3/requests/7227003c-a9a6-4024-99c7-18d960357941/cancel","request_id":"7227003c-a9a6-4024-99c7-18d960357941","status_url":"https://queue.fal.run/fal-ai/veo3/requests/7227003c-a9a6-4024-99c7-18d960357941/status","response_url":"https://queue.fal.run/fal-ai/veo3/requests/7227003c-a9a6-4024-99c7-18d960357941","queue_position":0}}]},"settings":{"executionOrder":"v1"},"versionId":"26d8848d-ad0c-4098-a523-8daa37ffb825","connections":{"wait":{"main":[[{"node":"fetch_status","type":"main","index":0}]]},"check_status":{"main":[[{"node":"fetch_result","type":"main","index":0}],[{"node":"wait","type":"main","index":0}]]},"fetch_result":{"main":[[{"node":"download_result_video","type":"main","index":0}]]},"fetch_status":{"main":[[{"node":"check_status","type":"main","index":0}]]},"form_trigger":{"main":[[{"node":"narrative_writer","type":"main","index":0}]]},"split_scenes":{"main":[[{"node":"scene_director","type":"main","index":0}]]},"upload_video":{"main":[[{"node":"iterate_prompts","type":"main","index":0}]]},"send_and_wait":{"main":[[{"node":"reset_scene_prompts","type":"main","index":0}]]},"scene_director":{"main":[[{"node":"set_scene_prompts","type":"main","index":0}]]},"claude-4-sonnet":{"ai_languageModel":[[{"node":"narrative_writer","type":"ai_languageModel","index":0},{"node":"narrative_parser","type":"ai_languageModel","index":0},{"node":"scene_director","type":"ai_languageModel","index":0}]]},"iterate_prompts":{"main":[[{"node":"aggregate_video_results","type":"main","index":0}],[{"node":"set_current_prompt","type":"main","index":0}]]},"aggregate_scenes":{"main":[[{"node":"send_narrative_msg","type":"main","index":0}]]},"narrative_parser":{"ai_outputParser":[[{"node":"narrative_writer","type":"ai_outputParser","index":0}]]},"narrative_writer":{"main":[[{"node":"split_scenes","type":"main","index":0}]]},"set_scene_prompts":{"main":[[{"node":"aggregate_scenes","type":"main","index":0}]]},"queue_create_video":{"main":[[{"node":"wait","type":"main","index":0}]]},"send_narrative_msg":{"main":[[{"node":"send_and_wait","type":"main","index":0}]]},"set_current_prompt":{"main":[[{"node":"queue_create_video","type":"main","index":0}]]},"reset_scene_prompts":{"main":[[{"node":"split_scene_prompts","type":"main","index":0}]]},"split_scene_prompts":{"main":[[{"node":"iterate_prompts","type":"main","index":0}]]},"download_result_video":{"main":[[{"node":"upload_video","type":"main","index":0}]]},"aggregate_video_results":{"main":[[{"node":"send_completion_msg","type":"main","index":0}]]}}}


name: Expose Translate a language endpoint to AI Agents with DeepL Tool MCP Server
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-25T20:27:43.706Z
updated_at: 2025-06-25T20:27:43.706Z
url: https://n8n.io/workflows/5313
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ DeepL Tool MCP Server

  Complete MCP server exposing all DeepL Tool operations to AI agents. Zero configuration needed - all 1 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every DeepL Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n DeepL Tool tool with full error handling

  📋 Available Operations (1 total)

  Every possible DeepL Tool operation is included:

  🔧 Language (1 operations)

  • Translate a language

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native DeepL Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every DeepL Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
  {"id":"VJR1iild6byTNPfA","meta":null,"name":"DeepL Tool MCP Server","tags":[],"nodes":[{"id":"8b2ef62a-d971-4583-bda9-ffaddddf6994","name":"Workflow Overview 0","type":"n8n-nodes-base.stickyNote","position":[-1460,-240],"parameters":{"width":420,"height":760,"content":"## 🛠️ DeepL Tool MCP Server\n\n### 📋 Available Operations (1 total)\n\n**Language**: translate\n\n### ⚙️ Setup Instructions\n\n1. **Import Workflow**: Load this workflow into your n8n instance\n\n1. **🔑 Add Credentials**: Configure DeepL Tool authentication in one tool node then open and close all others.\n2. **🚀 Activate**: Enable this workflow to start your MCP server\n3. **🔗 Get URL**: Copy webhook URL from MCP trigger (right side)\n4. **🤖 Connect**: Use MCP URL in your AI agent configurations\n\n### ✨ Ready-to-Use Features\n\n• Zero configuration - all 1 operations pre-built\n• AI agents automatically populate parameters via `$fromAI()` expressions\n• Every resource and operation combination available\n• Native n8n error handling and response formatting\n• Modify parameter defaults in any tool node as needed\n\n### 💬 Need Help?\nCheck the [n8n documentation](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolmcp/) or ping me on [discord](https://discord.me/cfomodz) for MCP integration guidance or customizations."},"typeVersion":1},{"id":"deb3559d-6d79-40bc-9e07-a247234fd7e7","name":"DeepL Tool MCP Server","type":"@n8n/n8n-nodes-langchain.mcpTrigger","position":[-840,-120],"webhookId":"9f4295cb-5ce5-40ee-9a93-735959414c3f","parameters":{"path":"deepl-tool-mcp"},"typeVersion":1},{"id":"f52a8222-35a7-42c0-9499-231a5c70a6ed","name":"Translate a language","type":"n8n-nodes-base.deepLTool","position":[-800,140],"parameters":{"additionalFields":{}},"credentials":{"deepLApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"9e86ce80-f920-4873-b079-1f74b4113383","name":"Sticky Note 1","type":"n8n-nodes-base.stickyNote","position":[-1000,120],"parameters":{"color":4,"width":400,"height":180,"content":"## Language"},"typeVersion":1}],"active":false,"shared":[{"role":"workflow:owner","project":{"id":"G5fce9xGuBAsWBXe","icon":null,"name":"David Ashby <david.ashby.lds@gmail.com>","type":"personal","createdAt":"2025-06-04T02:55:02.013Z","updatedAt":"2025-06-04T02:56:01.361Z","projectRelations":[{"role":"project:personalOwner","user":{"id":"715c1c00-cb48-4712-9a32-f1f4b6db2b30","role":"global:owner","email":"david.ashby.lds@gmail.com","disabled":false,"lastName":"Ashby","settings":{"npsSurvey":{"responded":true,"lastShownAt":1749357655581},"userActivated":true,"userActivatedAt":1749075994495,"easyAIWorkflowOnboarded":true,"firstSuccessfulWorkflowId":"3N3vVikZb3MckFYm"},"createdAt":"2025-06-04T02:55:01.745Z","firstName":"David","isPending":false,"updatedAt":"2025-06-08T04:40:58.399Z","mfaEnabled":false,"personalizationAnswers":{"version":"v4","personalization_survey_n8n_version":"1.95.3","personalization_survey_submitted_at":"2025-06-04T02:56:07.075Z"}},"userId":"715c1c00-cb48-4712-9a32-f1f4b6db2b30","createdAt":"2025-06-04T02:55:02.013Z","projectId":"G5fce9xGuBAsWBXe","updatedAt":"2025-06-04T02:55:02.013Z"}]},"createdAt":"2025-06-25T20:27:11.624Z","projectId":"G5fce9xGuBAsWBXe","updatedAt":"2025-06-25T20:27:11.624Z","workflowId":"VJR1iild6byTNPfA"}],"pinData":{},"settings":{"timezone":"America/New_York"},"createdAt":"2025-06-25T20:27:11.622Z","updatedAt":"2025-06-25T20:27:30.000Z","versionId":"fe0d8fd5-7e3b-4d24-8d41-0755caa36dc0","isArchived":false,"staticData":null,"connections":{"Translate a language":{"ai_tool":[[{"node":"DeepL Tool MCP Server","type":"ai_tool","index":0}]]}},"triggerCount":0}


name: AI Agent Powered Marketing 🛠️ Customer.io Tool MCP Server 💪 all 9 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-25T20:31:10.801Z
updated_at: 2025-06-25T20:31:10.801Z
url: https://n8n.io/workflows/5314
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Customer.io Tool MCP Server

  Complete MCP server exposing all Customer.io Tool operations to AI agents. Zero configuration needed - all 9 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Customer.io Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Customer.io Tool tool with full error handling

  📋 Available Operations (9 total)

  Every possible Customer.io Tool operation is included:

  🔧 Customer (2 operations)

  • Create or update a customer
  • Delete a customer

  📅 Event (2 operations)

  • Track a customer event
  • Track an anonymous event

  📢 Campaign (3 operations)

  • Get a campaign
  • Get many campaigns
  • Get metrics for a campaign

  🔧 Segment (2 operations)

  • Add a customer to a segment
  • Remove a customer from a segment

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Customer.io Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Customer.io Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

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name: Let AI Agents Run Your CRM with Copper Tool MCP Server 💪 all 32 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-25T20:35:13.725Z
updated_at: 2025-06-25T20:35:13.725Z
url: https://n8n.io/workflows/5315
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Copper Tool MCP Server

  Complete MCP server exposing all Copper Tool operations to AI agents. Zero configuration needed - all 32 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Copper Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Copper Tool tool with full error handling

  📋 Available Operations (32 total)

  Every possible Copper Tool operation is included:

  🔧 Company (5 operations)

  • Create a company
  • Delete a company
  • Get a company
  • Get many companies
  • Update a company

  🔧 Customersource (1 operations)

  • Get many customer sources

  🔧 Lead (5 operations)

  • Create a lead
  • Delete a lead
  • Get a lead
  • Get many leads
  • Update a lead

  🔧 Opportunity (5 operations)

  • Create an opportunity
  • Delete an opportunity
  • Get an opportunity
  • Get many opportunities
  • Update an opportunity

  👥 Person (5 operations)

  • Create a person
  • Delete a person
  • Get a person
  • Get many people
  • Update a person

  🔧 Project (5 operations)

  • Create a project
  • Delete a project
  • Get a project
  • Get many projects
  • Update a project

  🔧 Task (5 operations)

  • Create a task
  • Delete a task
  • Get a task
  • Get many tasks
  • Update a task

  👤 User (1 operations)

  • Get many users

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Copper Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Copper Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

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name: 🛠️ Cloudflare Tool MCP Server
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-25T21:15:19.291Z
updated_at: 2025-06-25T21:15:19.291Z
url: https://n8n.io/workflows/5322
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Cloudflare Tool MCP Server

  Complete MCP server exposing all Cloudflare Tool operations to AI agents. Zero configuration needed - all 4 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Cloudflare Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Cloudflare Tool tool with full error handling

  📋 Available Operations (4 total)

  Every possible Cloudflare Tool operation is included:

  🔧 Zonecertificate (4 operations)

  • Delete a certificate
  • Get a certificate
  • Get many certificates
  • Upload a certificate

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Cloudflare Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Cloudflare Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
  {"id":"i2mXmOzhSG4Wg1sp","meta":null,"name":"Cloudflare Tool MCP Server","tags":[],"nodes":[{"id":"0821253e-8e89-4c8a-809b-73b935408e6a","name":"Workflow Overview 0","type":"n8n-nodes-base.stickyNote","position":[-1460,-260],"parameters":{"width":420,"height":780,"content":"## 🛠️ Cloudflare Tool MCP Server\n\n### 📋 Available Operations (4 total)\n\n**Zonecertificate**: delete, get, get many, upload\n\n### ⚙️ Setup Instructions\n\n1. **Import Workflow**: Load this workflow into your n8n instance\n\n1. **🔑 Add Credentials**: Configure Cloudflare Tool authentication in one tool node then open and close all others.\n2. **🚀 Activate**: Enable this workflow to start your MCP server\n3. **🔗 Get URL**: Copy webhook URL from MCP trigger (right side)\n4. **🤖 Connect**: Use MCP URL in your AI agent configurations\n\n### ✨ Ready-to-Use Features\n\n• Zero configuration - all 4 operations pre-built\n• AI agents automatically populate parameters via `$fromAI()` expressions\n• Every resource and operation combination available\n• Native n8n error handling and response formatting\n• Modify parameter defaults in any tool node as needed\n\n### 💬 Need Help?\nCheck the [n8n documentation](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolmcp/) or ping me on [discord](https://discord.me/cfomodz) for MCP integration guidance or customizations."},"typeVersion":1},{"id":"1381deec-4f60-492f-a72b-282e25aad23a","name":"Cloudflare Tool MCP Server","type":"@n8n/n8n-nodes-langchain.mcpTrigger","position":[-420,-240],"webhookId":"4320bda5-d936-4116-b746-f32d034e624c","parameters":{"path":"cloudflare-tool-mcp"},"typeVersion":1},{"id":"bb959b2d-a1f2-47e0-989f-c640fd8bdb84","name":"Delete a certificate","type":"n8n-nodes-base.cloudflareTool","position":[-800,140],"parameters":{"zoneId":"={{ $fromAI('Zone_Id', ``, 'string') }}","operation":"delete","certificateId":"={{ $fromAI('Certificate_Id', ``, 'string') }}"},"credentials":{"cloudflareApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"14e70208-94dd-4128-9f6c-484e121b68c9","name":"Get a certificate","type":"n8n-nodes-base.cloudflareTool","position":[-580,140],"parameters":{"zoneId":"={{ $fromAI('Zone_Id', ``, 'string') }}","operation":"get","certificateId":"={{ $fromAI('Certificate_Id', ``, 'string') }}"},"credentials":{"cloudflareApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"18377f4c-5e73-4d87-a5c9-ed8c4cb8bbb1","name":"Get many certificates","type":"n8n-nodes-base.cloudflareTool","position":[-360,140],"parameters":{"limit":"={{ $fromAI('Limit', ``, 'number') }}","zoneId":"={{ $fromAI('Zone_Id', ``, 'string') }}","filters":{},"operation":"getMany","returnAll":"={{ $fromAI('Return_All', ``, 'boolean') }}"},"credentials":{"cloudflareApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"7eda8f1d-7953-421d-a287-0d73bb68f9ee","name":"Upload a certificate","type":"n8n-nodes-base.cloudflareTool","position":[-140,140],"parameters":{"zoneId":"={{ $fromAI('Zone_Id', ``, 'string') }}","privateKey":"={{ $fromAI('Private_Key', ``, 'string') }}","certificate":"={{ $fromAI('Certificate', ``, 'string') }}"},"credentials":{"cloudflareApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"5e057152-6ec8-4a0e-8451-1a928e2b8e8e","name":"Sticky Note 1","type":"n8n-nodes-base.stickyNote","position":[-1000,120],"parameters":{"color":4,"width":1060,"height":180,"content":"## Zonecertificate"},"typeVersion":1}],"active":false,"shared":[{"role":"workflow:owner","project":{"id":"G5fce9xGuBAsWBXe","icon":null,"name":"David Ashby <david.ashby.lds@gmail.com>","type":"personal","createdAt":"2025-06-04T02:55:02.013Z","updatedAt":"2025-06-04T02:56:01.361Z","projectRelations":[{"role":"project:personalOwner","user":{"id":"715c1c00-cb48-4712-9a32-f1f4b6db2b30","role":"global:owner","email":"david.ashby.lds@gmail.com","disabled":false,"lastName":"Ashby","settings":{"npsSurvey":{"responded":true,"lastShownAt":1749357655581},"userActivated":true,"userActivatedAt":1749075994495,"easyAIWorkflowOnboarded":true,"firstSuccessfulWorkflowId":"3N3vVikZb3MckFYm"},"createdAt":"2025-06-04T02:55:01.745Z","firstName":"David","isPending":false,"updatedAt":"2025-06-08T04:40:58.399Z","mfaEnabled":false,"personalizationAnswers":{"version":"v4","personalization_survey_n8n_version":"1.95.3","personalization_survey_submitted_at":"2025-06-04T02:56:07.075Z"}},"userId":"715c1c00-cb48-4712-9a32-f1f4b6db2b30","createdAt":"2025-06-04T02:55:02.013Z","projectId":"G5fce9xGuBAsWBXe","updatedAt":"2025-06-04T02:55:02.013Z"}]},"createdAt":"2025-06-25T21:14:46.264Z","projectId":"G5fce9xGuBAsWBXe","updatedAt":"2025-06-25T21:14:46.264Z","workflowId":"i2mXmOzhSG4Wg1sp"}],"pinData":{},"settings":{"timezone":"America/New_York"},"createdAt":"2025-06-25T21:14:46.262Z","updatedAt":"2025-06-25T21:15:06.000Z","versionId":"a19aca38-eebc-4ad4-94aa-76fbdffe9cba","isArchived":false,"staticData":null,"connections":{"Get a certificate":{"ai_tool":[[{"node":"Cloudflare Tool MCP Server","type":"ai_tool","index":0}]]},"Delete a certificate":{"ai_tool":[[{"node":"Cloudflare Tool MCP Server","type":"ai_tool","index":0}]]},"Upload a certificate":{"ai_tool":[[{"node":"Cloudflare Tool MCP Server","type":"ai_tool","index":0}]]},"Get many certificates":{"ai_tool":[[{"node":"Cloudflare Tool MCP Server","type":"ai_tool","index":0}]]}},"triggerCount":0}


name: Viral ASMR Video Factory: Automatically generate viral videos on autopilot.
author_name: Adam Crafts
author_username: adamcrafts
categories: []
created_at: 2025-06-25T21:18:03.073Z
updated_at: 2025-06-25T21:18:03.073Z
url: https://n8n.io/workflows/5324
scraped_at: 2025-07-06 21:16:30
description:
  🚀 Overview

  This automation is a complete content creation engine for your social media. It endlessly designs, generates, and organizes unique and oddly satisfying ASMR videos, ensuring you always have fresh, viral-style content ready to post on platforms like TikTok, YouTube Shorts, and Instagram Reels.

  Video Examples

  😩 The Problem

  Consistently creating viral content is exhausting. You're constantly battling creative burnout, trying to come up with new ideas that are fresh and engaging. For every video, you have to brainstorm an idea, write a detailed prompt for an AI generator, wait for the video, and then manually track what you've already posted. This manual process is slow, repetitive, and a major roadblock to scaling your content output.

  ✨ The Solution

  This workflow acts as your personal, automated content creation employee. When you trigger it, the automation first checks a Google Sheet to see what videos it has already made. Then, a built-in "Idea Agent" cleverly brainstorms a brand new, unused concept (like a "glass banana" or "glass pomegranate").

  Next, it passes this idea to a "Prompt Agent," which writes a perfectly detailed, sensory-rich script designed to produce a stunning, hyper-realistic video. The script is sent to an AI video generator, and the workflow waits patiently for it to finish. Once the video is ready, the automation saves the final video link neatly into your Google Sheet and cleans up the oldest entry, creating a self-sustaining content machine.

  ⚙️ Simple Setup

  This workflow is a pre-built blueprint, designed to be up and running in minutes!

  Upload:** Simply upload the provided JSON file into your n8n instance.
  Connect:** Connect your app credentials (e.g., your Google, OpenAI, and Fal accounts). The workflow will show you exactly where.
  Activate:** Turn the workflow on, and it's ready to go! Let your new automated employee get to work.

  🌐 Explore more workflows
  ❤️ Buy more workflows at: adamcrafts
  🦾 Custom workflows at: adamcrafts@cloudysoftwares.com
  adamaicrafts@gmail.com


  &gt; Build once, customize endlessly, and scale your video content like never before.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured"]

workflow_json:
  {"meta":{"instanceId":"2d54f61dfd963457efb86a8690aae457934e92fb9e4b8b6490ca74fc37094458","templateCredsSetupCompleted":true},"nodes":[{"id":"560431ab-faeb-44a1-ae7e-59c7d1d44c85","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-260,-40],"parameters":{"content":""},"typeVersion":1},{"id":"1b8b77b4-34af-45b1-972a-53ee50d96c96","name":"Sticky Note7","type":"n8n-nodes-base.stickyNote","position":[-260,-380],"parameters":{"content":""},"typeVersion":1},{"id":"4b715b09-7337-423d-96bf-918be3586376","name":"Generate Video","type":"n8n-nodes-base.httpRequest","position":[560,80],"parameters":{},"typeVersion":4.2},{"id":"1c22bca2-b1b2-43de-bde7-e5524878715f","name":"Get 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name: 🛠️ AWS Transcribe Tool MCP Server 💪 all operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-25T21:30:06.802Z
updated_at: 2025-06-25T21:30:06.802Z
url: https://n8n.io/workflows/5330
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ AWS Transcribe Tool MCP Server

  Complete MCP server exposing all AWS Transcribe Tool operations to AI agents. Zero configuration needed - all 4 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every AWS Transcribe Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n AWS Transcribe Tool tool with full error handling

  📋 Available Operations (4 total)

  Every possible AWS Transcribe Tool operation is included:

  🔧 Transcriptionjob (4 operations)

  • Create a transcription job
  • Delete a transcription job
  • Get a transcription job
  • Get many transcription jobs

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native AWS Transcribe Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every AWS Transcribe Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
  {"id":"2LHnQy6dukuG0VBo","meta":null,"name":"AWS Transcribe Tool MCP Server","tags":[],"nodes":[{"id":"f825fad3-d1a6-4800-8ff5-b9e03dfe8483","name":"Workflow Overview 0","type":"n8n-nodes-base.stickyNote","position":[-1480,-200],"parameters":{"width":420,"height":800,"content":"## 🛠️ AWS Transcribe Tool MCP Server\n\n### 📋 Available Operations (4 total)\n\n**Transcriptionjob**: create, delete, get, get all\n\n### ⚙️ Setup Instructions\n\n1. **Import Workflow**: Load this workflow into your n8n instance\n\n1. **🔑 Add Credentials**: Configure AWS Transcribe Tool authentication in one tool node then open and close all others.\n2. **🚀 Activate**: Enable this workflow to start your MCP server\n3. **🔗 Get URL**: Copy webhook URL from MCP trigger (right side)\n4. **🤖 Connect**: Use MCP URL in your AI agent configurations\n\n### ✨ Ready-to-Use Features\n\n• Zero configuration - all 4 operations pre-built\n• AI agents automatically populate parameters via `$fromAI()` expressions\n• Every resource and operation combination available\n• Native n8n error handling and response formatting\n• Modify parameter defaults in any tool node as needed\n\n### 💬 Need Help?\nCheck the [n8n documentation](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolmcp/) or ping me on [discord](https://discord.me/cfomodz) for MCP integration guidance or customizations."},"typeVersion":1},{"id":"69490659-7d20-4ace-b5df-ade65719e960","name":"AWS Transcribe Tool MCP Server","type":"@n8n/n8n-nodes-langchain.mcpTrigger","position":[-420,-220],"webhookId":"16921a23-3086-4ad1-a921-1c9b1fd17c72","parameters":{"path":"aws-transcribe-tool-mcp"},"typeVersion":1},{"id":"457aa710-405a-4e74-a1af-1b2229c14d14","name":"Create a transcription job","type":"n8n-nodes-base.awsTranscribeTool","position":[-800,140],"parameters":{"options":{},"languageCode":"={{ $fromAI('Language_Code', ``, 'string') }}","mediaFileUri":"={{ $fromAI('Media_File_Uri', ``, 'string') 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}}"},"credentials":{"aws":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"6d6dd15a-34a8-4066-9280-ffa3b3e393b2","name":"Get many transcription jobs","type":"n8n-nodes-base.awsTranscribeTool","position":[-140,140],"parameters":{"limit":"={{ $fromAI('Limit', ``, 'number') }}","filters":{},"operation":"getAll","returnAll":"={{ $fromAI('Return_All', ``, 'boolean') }}"},"credentials":{"aws":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"c3e5205b-60cd-45f2-9e34-41b5b2c20a9d","name":"Sticky Note 1","type":"n8n-nodes-base.stickyNote","position":[-1020,120],"parameters":{"color":4,"width":1080,"height":180,"content":"## Transcription Job"},"typeVersion":1}],"active":false,"shared":[{"role":"workflow:owner","project":{"id":"G5fce9xGuBAsWBXe","icon":null,"name":"David Ashby 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a transcription job":{"ai_tool":[[{"node":"AWS Transcribe Tool MCP Server","type":"ai_tool","index":0}]]},"Create a transcription job":{"ai_tool":[[{"node":"AWS Transcribe Tool MCP Server","type":"ai_tool","index":0}]]},"Delete a transcription job":{"ai_tool":[[{"node":"AWS Transcribe Tool MCP Server","type":"ai_tool","index":0}]]},"Get many transcription jobs":{"ai_tool":[[{"node":"AWS Transcribe Tool MCP Server","type":"ai_tool","index":0}]]}},"triggerCount":0}


name: Post New Articles from Feeds to Slack Channel
author_name: Paul Taylor
author_username: ptylr
nodes_used: ["n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.code"]
categories: []
created_at: 2025-06-25T21:43:07.205Z
updated_at: 2025-06-25T21:43:07.205Z
url: https://n8n.io/workflows/5333
scraped_at: 2025-07-06 21:16:30
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  📄 Post New Articles from Feeds to Slack Channel

  🧠 What This Workflow Does

  This workflow automates the discovery and sharing of fresh articles from a curated list of RSS feeds. It performs the following steps:

  Reads a list of RSS feed URLs from a Google Sheet (Feeds tab).
  Fetches the latest articles from each feed.
  Checks for duplicates against previously published links stored in another sheet (Posted Articles tab).
  Filters out already shared articles.
  Posts the new articles to a designated Slack channel with formatted titles and links.
  Logs the newly shared articles back into the Google Sheet to prevent duplicates.

  🛠️ Prerequisites

  To use this workflow, you must have:

  ✅ Google Sheets OAuth2 credentials set up in n8n  
    (Used to access and update the RSS feed and post history sheets)

  ✅ Slack OAuth2 credentials  
    (Used to post messages to a specific Slack channel)

  ✅ A Google Spreadsheet with:
    Feeds tab – Columns: title, link  
    Posted Articles tab – Columns: title, link, pubDate

  🔧 Environment Variables or Custom Values

  You will need to set the following n8n variable or replace with direct input:

  {{$vars.Daily_Industry_News_Automation_Google_Sheet}}:  
    Reference to the Google Sheet Document ID (you can use a static ID if preferred)

  Also update:
  Slack channelId: Replace with your actual Slack channel ID if not dynamically referenced

  ⏰ Trigger & Scheduling

  Trigger type**: Cron node  
  Default schedule: Every day at **7:00 AM

  You can modify this in the “Trigger Workflow” node to suit your own schedule.

  🎯 Intended Use Case

  This workflow is ideal for:

  Marketing teams curating daily or weekly news digests
  Founders or industry professionals monitoring sector updates
  Automating internal Slack news updates
  Avoiding duplicate content when sourcing from multiple feeds

workflow_json:
  {"id":"G452NfcbwAErVDRu","meta":{"instanceId":"05cd306a73f97150c796adf49d28dcc97084b722b0b212b8c228ea8b71d87571","templateCredsSetupCompleted":true},"name":"Post New Articles from Feeds to Slack Channel","tags":[{"id":"HKMgMooCXhG1RvQ4","name":"RSS","createdAt":"2025-06-25T20:39:25.066Z","updatedAt":"2025-06-25T20:39:25.066Z"},{"id":"LrtcE3ptvaKdYplW","name":"Slack","createdAt":"2025-06-25T20:39:34.824Z","updatedAt":"2025-06-25T20:39:34.824Z"},{"id":"msIodL6e7sVaa5aZ","name":"Google Sheets","createdAt":"2025-06-25T20:39:20.673Z","updatedAt":"2025-06-25T20:39:20.673Z"},{"id":"mv8twTYqHvotykOz","name":"Filter","createdAt":"2025-06-25T20:39:31.349Z","updatedAt":"2025-06-25T20:39:31.349Z"}],"nodes":[{"id":"5555a9ce-26d1-45a3-9672-5f54b0cf28a3","name":"Filter Unpublished Articles","type":"n8n-nodes-base.code","notes":"Filter previously published articles from those received from the feeds.","position":[-460,-340],"parameters":{"jsCode":"const sheetLinks = $('Get Historically Posted Articles from Google Sheet').all().map(row => row.json.link);\nconst articles = $('Read Latest Articles from Feeds').all();\nreturn articles.filter(item => !sheetLinks.includes(item.json.link));              "},"notesInFlow":true,"typeVersion":2,"alwaysOutputData":true},{"id":"235db786-a37c-4f70-9fb8-a23903399056","name":"Trigger Workflow","type":"n8n-nodes-base.cron","notes":"cron-based Workflow trigger. Recommend once per day.","position":[-1340,-340],"parameters":{"triggerTimes":{"item":[{"hour":7}]}},"notesInFlow":true,"typeVersion":1},{"id":"195bea58-205a-4d30-bab0-ef137b157ab5","name":"Post New Articles to Slack Channel","type":"n8n-nodes-base.slack","notes":"Post new articles to Slack Channel.","position":[-20,-340],"webhookId":"637dea4d-c4e0-4369-93bb-f98268950d65","parameters":{"text":"=*{{$json[\"title\"]}}* | {{$json[\"link\"]}} _Published: {{$json[\"pubDate\"]}}_","select":"channel","channelId":{"__rl":true,"mode":"list","value":"C09281Y80AH","cachedResultName":"daily-industry-news-automation"},"otherOptions":{},"authentication":"oAuth2"},"notesInFlow":true,"typeVersion":2.3},{"id":"e1ea7e51-5f0f-4089-a4c0-9308bc72c85a","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-2340,-420],"parameters":{"width":900,"height":1380,"content":"# 📄 Post New Articles from Feeds to Slack Channel\n\n## 🧠 What This Workflow Does\n\nThis workflow automates the discovery and sharing of fresh articles from a curated list of RSS feeds. It performs the following steps:\n\n1. **Reads a list of RSS feed URLs** from a Google Sheet (`Feeds` tab).\n2. **Fetches the latest articles** from each feed.\n3. **Checks for duplicates** against previously published links stored in another sheet (`Posted Articles` tab).\n4. **Filters out already shared articles**.\n5. **Posts the new articles** to a designated Slack channel with formatted titles and links.\n6. **Logs the newly shared articles** back into the Google Sheet to prevent duplicates.\n\n---\n\n## 🛠️ Prerequisites\n\nTo use this workflow, you must have:\n\n- ✅ **Google Sheets** OAuth2 credentials set up in n8n  \n  (Used to access and update the RSS feed and post history sheets)\n\n- ✅ **Slack** OAuth2 credentials  \n  (Used to post messages to a specific Slack channel)\n\n- ✅ **A Google Spreadsheet** with:\n  - `Feeds` tab – Columns: `title`, `link`  \n  - `Posted Articles` tab – Columns: `title`, `link`, `pubDate`\n\n---\n\n## 🔧 Environment Variables or Custom Values\n\nYou will need to set the following n8n variable or replace with direct input:\n\n- `{{$vars.Daily_Industry_News_Automation_Google_Sheet}}`:  \n  Reference to the Google Sheet Document ID (you can use a static ID if preferred)\n\nAlso update:\n- Slack `channelId`: Replace with your actual Slack channel ID if not dynamically referenced\n\n---\n\n## ⏰ Trigger & Scheduling\n\n- **Trigger type**: `Cron` node  \n- **Default schedule**: Every day at **7:00 AM**\n\nYou can modify this in the **“Trigger Workflow”** node to suit your own schedule.\n\n---\n\n## 🎯 Intended Use Case\n\nThis workflow is ideal for:\n\n- Marketing teams curating daily or weekly news digests\n- Founders or industry professionals monitoring sector updates\n- Automating internal Slack news updates\n- Avoiding duplicate content when sourcing from multiple feeds"},"typeVersion":1},{"id":"146f4c93-a72c-4356-99ab-bcbc7747e671","name":"Get Article Feeds","type":"n8n-nodes-base.googleSheets","notes":"Get a list of 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from Posted Articles Google Sheet (title, link, pubDate).","position":[-680,-340],"parameters":{"options":{},"sheetName":{"__rl":true,"mode":"list","value":"gid=0","cachedResultUrl":"https://docs.google.com/spreadsheets/d/1HIldK5vDx2luvmYEstU2PQzSS68xBrpp7lJ-8rQb2No/edit#gid=0","cachedResultName":"Posted Articles"},"documentId":{"__rl":true,"mode":"id","value":"={{$vars.Daily_Industry_News_Automation_Google_Sheet}}"}},"executeOnce":true,"notesInFlow":true,"typeVersion":4.6,"alwaysOutputData":true},{"id":"f0c01201-06f4-4154-8010-f134e5506f27","name":"Append New Articles to Google Sheet","type":"n8n-nodes-base.googleSheets","notes":"Append the un-published articles to the Published Articles Google Sheet.","position":[-240,-340],"parameters":{"columns":{"value":{"link":"={{ $json.link }}","title":"={{ $json.title }}","pubDate":"={{ $json.pubDate }}"},"schema":[{"id":"title","type":"string","display":true,"required":false,"displayName":"title","defaultMatch":false,"canBeUsedToMatch":true},{"id":"link","type":"string","display":true,"required":false,"displayName":"link","defaultMatch":false,"canBeUsedToMatch":true},{"id":"pubDate","type":"string","display":true,"required":false,"displayName":"pubDate","defaultMatch":false,"canBeUsedToMatch":true},{"id":"creator","type":"string","display":true,"removed":true,"required":false,"displayName":"creator","defaultMatch":false,"canBeUsedToMatch":true},{"id":"content:encoded","type":"string","display":true,"removed":true,"required":false,"displayName":"content:encoded","defaultMatch":false,"canBeUsedToMatch":true},{"id":"content:encodedSnippet","type":"string","display":true,"removed":true,"required":false,"displayName":"content:encodedSnippet","defaultMatch":false,"canBeUsedToMatch":true},{"id":"dc:creator","type":"string","display":true,"removed":true,"required":false,"displayName":"dc:creator","defaultMatch":false,"canBeUsedToMatch":true},{"id":"content","type":"string","display":true,"removed":true,"required":false,"displayName":"content","defaultMatch":false,"canBeUsedToMatch":true},{"id":"contentSnippet","type":"string","display":true,"removed":true,"required":false,"displayName":"contentSnippet","defaultMatch":false,"canBeUsedToMatch":true},{"id":"guid","type":"string","display":true,"removed":true,"required":false,"displayName":"guid","defaultMatch":false,"canBeUsedToMatch":true},{"id":"categories","type":"string","display":true,"removed":true,"required":false,"displayName":"categories","defaultMatch":false,"canBeUsedToMatch":true},{"id":"isoDate","type":"string","display":true,"removed":true,"required":false,"displayName":"isoDate","defaultMatch":false,"canBeUsedToMatch":true},{"id":"date","type":"string","display":true,"removed":true,"required":false,"displayName":"date","defaultMatch":false,"canBeUsedToMatch":true},{"id":"author","type":"string","display":true,"removed":true,"required":false,"displayName":"author","defaultMatch":false,"canBeUsedToMatch":true},{"id":"dc:date","type":"string","display":true,"removed":true,"required":false,"displayName":"dc:date","defaultMatch":false,"canBeUsedToMatch":true},{"id":"comments","type":"string","display":true,"removed":true,"required":false,"displayName":"comments","defaultMatch":false,"canBeUsedToMatch":true}],"mappingMode":"defineBelow","matchingColumns":[],"attemptToConvertTypes":false,"convertFieldsToString":false},"options":{},"operation":"append","sheetName":{"__rl":true,"mode":"list","value":"gid=0","cachedResultUrl":"https://docs.google.com/spreadsheets/d/1HIldK5vDx2luvmYEstU2PQzSS68xBrpp7lJ-8rQb2No/edit#gid=0","cachedResultName":"Posted Articles"},"documentId":{"__rl":true,"mode":"id","value":"={{$vars.Daily_Industry_News_Automation_Google_Sheet}}"}},"executeOnce":false,"notesInFlow":true,"typeVersion":4.6,"alwaysOutputData":true}],"active":true,"pinData":{},"settings":{"executionOrder":"v1"},"versionId":"2799c1bc-9306-4ff8-b6e9-8341fac3cfdb","connections":{"Trigger Workflow":{"main":[[{"node":"Get Article Feeds","type":"main","index":0}]]},"Get Article Feeds":{"main":[[{"node":"Read Latest Articles from Feeds","type":"main","index":0}]]},"Filter Unpublished Articles":{"main":[[{"node":"Append New Articles to Google Sheet","type":"main","index":0}]]},"Read Latest Articles from Feeds":{"main":[[{"node":"Get Historically Posted Articles from Google Sheet","type":"main","index":0}]]},"Append New Articles to Google Sheet":{"main":[[{"node":"Post New Articles to Slack Channel","type":"main","index":0}]]},"Get Historically Posted Articles from Google Sheet":{"main":[[{"node":"Filter Unpublished Articles","type":"main","index":0}]]}}}


name: 🛠️ ActiveCampaign Tool MCP Server 💪 all 48 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-25T21:47:34.856Z
updated_at: 2025-06-25T21:47:34.856Z
url: https://n8n.io/workflows/5336
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ ActiveCampaign Tool MCP Server

  Complete MCP server exposing all ActiveCampaign Tool operations to AI agents. Zero configuration needed - all 48 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every ActiveCampaign Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n ActiveCampaign Tool tool with full error handling

  📋 Available Operations (48 total)

  Every possible ActiveCampaign Tool operation is included:

  👤 Account (5 operations)

  • Create an account
  • Delete an account
  • Get an account
  • Get many accounts
  • Update an account

  🔧 Accountcontact (3 operations)

  • Create an account contact
  • Delete an account contact
  • Update an account contact

  🔌 Connection (5 operations)

  • Create a connection
  • Delete a connection
  • Get a connection
  • Get many connections
  • Update a connection

  📇 Contact (5 operations)

  • Create a contact
  • Delete a contact
  • Get a contact
  • Get many contacts
  • Update a contact

  🔧 Contactlist (2 operations)

  • Add a contact to a list
  • Remove a contact from a list

  🔧 Contacttag (2 operations)

  • Add a contact tag
  • Remove a contact tag

  💰 Deal (7 operations)

  • Create a deal
  • Create a deal note
  • Delete a deal
  • Get a deal
  • Get many deals
  • Update a deal
  • Update a deal note

  🔧 Ecommercecustomer (5 operations)

  • Create an e-commerce customer
  • Delete an e-commerce customer
  • Get an e-commerce customer
  • Get many e-commerce customers
  • Update an e-commerce customer

  🔧 Ecommerceorder (5 operations)

  • Create an e-commerce order
  • Delete an e-commerce order
  • Get an e-commerce order
  • Get many e-commerce orders
  • Update an e-commerce order

  🔧 Ecommerceorderproducts (3 operations)

  • Get many ecommerce orders
  • Get an e-commerce order product by product ID
  • Get an e-commerce order product by order ID

  📝 List (1 operations)

  • Get many lists

  🏷️ Tag (5 operations)

  • Create a tag
  • Delete a tag
  • Get a tag
  • Get many tags
  • Update a tag

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native ActiveCampaign Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every ActiveCampaign Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
  {"id":"J4T5m7LSKiIh97DD","meta":null,"name":"ActiveCampaign Tool MCP Server","tags":[],"nodes":[{"id":"144d6c97-6939-490c-a926-48a2f8c45f68","name":"ActiveCampaign Tool MCP Server","type":"@n8n/n8n-nodes-langchain.mcpTrigger","position":[-420,-240],"webhookId":"2337d3b0-820b-4b05-948e-b23dc7e9f284","parameters":{"path":"activecampaign-tool-mcp"},"typeVersion":1},{"id":"4c878c1a-0006-440f-a3a0-aa0c8b87be0d","name":"Create an account","type":"n8n-nodes-base.activeCampaignTool","position":[-800,240],"parameters":{"name":"={{ $fromAI('Name', ``, 'string') }}","resource":"account","additionalFields":{}},"credentials":{"activeCampaignApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"3f107a6d-cab1-4728-a815-b12783f5835b","name":"Delete an account","type":"n8n-nodes-base.activeCampaignTool","position":[-580,240],"parameters":{"resource":"account","accountId":"={{ $fromAI('Account_Id', ``, 'number') }}","operation":"delete"},"credentials":{"activeCampaignApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"3c286a10-3ad2-4e64-9a5e-d288832cf300","name":"Get an account","type":"n8n-nodes-base.activeCampaignTool","position":[-360,240],"parameters":{"resource":"account","accountId":"={{ $fromAI('Account_Id', ``, 'number') }}","operation":"get"},"credentials":{"activeCampaignApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"335917bb-2bc1-4be3-a5b0-e667f39e6d02","name":"Get many accounts","type":"n8n-nodes-base.activeCampaignTool","position":[-140,240],"parameters":{"limit":"={{ $fromAI('Limit', ``, 'number') }}","simple":"={{ $fromAI('Simple', ``, 'boolean') }}","filters":{},"resource":"account","operation":"getAll","returnAll":"={{ $fromAI('Return_All', ``, 'boolean') }}"},"credentials":{"activeCampaignApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential 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}}","resource":"accountContact","additionalFields":{}},"credentials":{"activeCampaignApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"60184a00-bdb3-43a5-b1d1-89b397779899","name":"Delete an account contact","type":"n8n-nodes-base.activeCampaignTool","position":[-580,480],"parameters":{"resource":"accountContact","operation":"delete","accountContactId":"={{ $fromAI('Account_Contact_Id', ``, 'number') }}"},"credentials":{"activeCampaignApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential Name"}},"typeVersion":1},{"id":"741002ab-27c2-4954-9508-423026e63d37","name":"Update an account contact","type":"n8n-nodes-base.activeCampaignTool","position":[-360,480],"parameters":{"resource":"accountContact","operation":"update","updateFields":{},"accountContactId":"={{ $fromAI('Account_Contact_Id', ``, 'number') }}"},"credentials":{"activeCampaignApi":{"id":"SET_YOUR_CREDENTIAL_ID_HERE","name":"Credential 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name: Generate AI Viral Videos with Seedance and Upload to TikTok, YouTube & Instagram
author_name: Dr. Firas
author_username: drfiras
categories: []
created_at: 2025-06-25T22:02:46.851Z
updated_at: 2025-06-25T22:02:46.851Z
url: https://n8n.io/workflows/5338
scraped_at: 2025-07-06 21:16:30
description:
  Generate AI videos with Seedance & Blotato, upload to TikTok, YouTube & Instagram

  Who is this for?

  This template is ideal for creators, content marketers, social media managers, and AI enthusiasts who want to automate the production of short-form, visually captivating videos for platforms like TikTok, YouTube Shorts, and Instagram Reels — all without manual editing or publishing.

  What problem is this workflow solving?

  Creating engaging videos requires:
  Generating creative ideas  
  Writing detailed scene prompts  
  Producing realistic video clips and sound effects  
  Editing and stitching the final video  
  Publishing across multiple platforms  

  This workflow automates the entire process, saving hours of manual work and ensuring consistent, AI-driven content output ready for social distribution.

  What this workflow does

  This end-to-end AI video automation workflow:

  Generates a creative idea using OpenAI and LangChain  
  Creates detailed video prompts with Seedance AI  
  Generates video clips via Wavespeed AI  
  Generates sound effects with Fal AI  
  Stitches the final video using Fal AI’s ffmpeg API  
  Logs metadata and video links to Google Sheets  
  Uploads the video to Blotato  
  Auto-publishes to TikTok, YouTube, Instagram, and other platforms

  Setup

  Add your OpenAI API key in the LLM nodes  
  Set up Seedance and Wavespeed AI credentials for video prompt and clip generation  
  Add your Fal AI API key for sound and stitching steps  
  Connect your Google Sheets account for tracking ideas and outputs  
  Set your Blotato API key and fill in the platform account IDs in the Assign Social Media IDs node  
  Adjust the Schedule Trigger to control when the automation runs  

  How to customize this workflow to your needs

  Change the AI prompts** to target your niche (e.g., ASMR, product videos, humor)  
  Add a Telegram or Slack step** for video preview before publishing  
  Tweak scene structure** or video duration to match your style  
  Disable platforms** you don’t want by turning off specific HTTP Request nodes  
  Edit the sound generation prompts** for different moods or effects  

  📄 Documentation: Notion Guide

  Need help customizing?
  Contact me for consulting and support : Linkedin / Youtube

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.toolThink"]

workflow_json:
  {"id":"DbAetBYfinQ3x4Cu","meta":{"instanceId":"a2b23892dd6989fda7c1209b381f5850373a7d2b85609624d7c2b7a092671d44","templateCredsSetupCompleted":true},"name":"💥 Generate AI Videos with Seedance & Blotato and Upload to TikTok, YouTube & Instagram -vide","tags":[],"nodes":[{"id":"cd0df97c-8e71-4201-9086-c247491c3c48","name":"Sticky Note10","type":"n8n-nodes-base.stickyNote","position":[580,460],"parameters":{"color":2,"width":880,"height":240,"content":"## | Step 1: Generate Clips (Wavespeed AI)\n"},"typeVersion":1},{"id":"c42e1959-f856-4954-af25-f8eed14a1e5c","name":"Sticky Note13","type":"n8n-nodes-base.stickyNote","position":[1500,460],"parameters":{"color":2,"width":640,"height":240,"content":"## | Step 2: Generate Sounds (Fal AI)\n"},"typeVersion":1},{"id":"567d5588-ca94-43c7-b856-17239da45750","name":"Sticky Note14","type":"n8n-nodes-base.stickyNote","position":[580,-100],"parameters":{"color":7,"width":1560,"height":540,"content":"## | INPUT: Starting Idea Section"},"typeVersion":1},{"id":"9a1c7a82-0dc8-4eef-a815-ed76928530e7","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[580,740],"parameters":{"color":3,"width":1560,"height":260,"content":"## | Step 3: Stitch Video (Fal AI)"},"typeVersion":1},{"id":"380b91d1-20e7-4d0f-a685-dc5898b11a6c","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","disabled":true,"position":[580,1040],"parameters":{"color":4,"width":1560,"height":760,"content":"## | Step 4 — Publish Video to Social Media\n"},"typeVersion":1},{"id":"b3e014f3-849a-4532-b406-18f3cb6305d9","name":"Trigger: Start Daily Content Generation","type":"n8n-nodes-base.scheduleTrigger","position":[640,0],"parameters":{"rule":{"interval":[{}]}},"typeVersion":1.2},{"id":"aabf432b-b4d4-4e56-9710-52495f08d007","name":"AI Agent: Generate Creative Video Idea","type":"@n8n/n8n-nodes-langchain.agent","position":[960,0],"parameters":{"text":"Generate a creative concept involving:\n\n[[\nA solid, hard material or element being sliced cleanly with a sharp blade. Your response must follow this structure:\n\n\"(Color) (Material) shaped like a (random everyday object)\"\n\nFor inspiration, imagine examples like: obsidian shaped like a chess piece, quartz shaped like a coffee mug, sapphire shaped like a seashell, or titanium shaped like a leaf.\n\n]]\n\nReflect carefully before answering to ensure originality and visual appeal.\n\nUse the Think tool to review your output","options":{"systemMessage":"=**Role:**  \nYou are an AI designed to generate **one immersive, realistic idea** based on a user-provided topic. Your output must be formatted as a **single-line JSON array** and follow the rules below exactly.\n\n---\n\n### RULES\n\n1. **Number of ideas**  \n   - Return **only one idea**.\n\n2. **Topic**  \n   - The user will provide a keyword (e.g., “glass cutting ASMR,” “wood carving sounds,” “satisfying rock splits”).\n\n3. **Idea**  \n   - Maximum 13 words.  \n   - Describe a viral-worthy, original, or surreal moment related to the topic.\n\n4. **Caption**  \n   - Short, punchy, viral-friendly.  \n   - Include **one emoji**.  \n   - Exactly **12 hashtags** in this order:  \n     1. 4 topic-relevant hashtags  \n     2. 4 all-time most popular hashtags  \n     3. 4 currently trending hashtags (based on live research)  \n   - All in lowercase.\n\n5. **Environment**  \n   - Maximum 20 words.  \n   - Must match the action in the Idea exactly.  \n   - Specify location (studio table, natural terrain, lab bench…), visual details (dust particles, polished surface, subtle reflections…), and style (macro close-up, cinematic slow-motion, minimalist…).\n\n6. **Sound**  \n   - Maximum 15 words.  \n   - Describe the primary sound for the scene (to feed into an audio model).\n\n7. **Status**  \n   - Always set to `\"for production\"`.\n\n---\n\n### OUTPUT FORMAT (single-line JSON array)\n\n```json\n[\n  {\n    \"Caption\": \"Your short viral title with emoji #4_topic_hashtags #4_all_time_popular_hashtags #4_trending_hashtags\",\n    \"Idea\": \"Your idea under 13 words\",\n    \"Environment\": \"Your vivid setting under 20 words matching the action\",\n    \"Sound\": \"Your primary sound description under 15 words\",\n    \"Status\": \"for production\"\n  }\n]\n"},"promptType":"define","hasOutputParser":true},"typeVersion":1.9},{"id":"09e27c25-772b-41e5-8255-723d23398a64","name":"Tool: Inject Creative Perspective (Idea)","type":"@n8n/n8n-nodes-langchain.toolThink","position":[1080,280],"parameters":{},"typeVersion":1},{"id":"1f1985b1-d1eb-4c65-9d99-f96542273dc6","name":"LLM: Generate Raw Idea (GPT-4.1)","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[900,280],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-4.1","cachedResultName":"gpt-4.1"},"options":{}},"credentials":{"openAiApi":{"id":"6h3DfVhNPw9I25nO","name":"OpenAi account"}},"typeVersion":1.2},{"id":"a2c57dca-ed2e-4712-a735-8da0c727470f","name":"Parse AI Output (Idea, Environment, Sound)","type":"@n8n/n8n-nodes-langchain.outputParserStructured","position":[1240,280],"parameters":{"jsonSchemaExample":"[\n  {\n    \"Caption\": \"Diver Removes Nets Off Whale 🐋 #whalerescue #marinelife #oceanrescue #seahelpers #love #nature #instagood #explore #viral #savenature #oceanguardians #cleanoceans\",\n    \"Idea\": \"Diver carefully cuts tangled net from distressed whale in open sea\",\n    \"Environment\": \"Open ocean, sunlight beams through water, diver and whale, cinematic realism\",\n    \"Sound\": \"Primary sound description under 15 words\",\n    \"Status\": \"for production\"\n  }\n]\n"},"typeVersion":1.2},{"id":"20db6d62-9db9-4942-a820-b520356f3209","name":"Save Idea & Metadata to Google Sheets","type":"n8n-nodes-base.googleSheets","position":[1420,0],"parameters":{"columns":{"value":{"id":"==ROW()-1","idea":"={{ $json.output[0].Idea }}","caption":"={{ $json.output[0].Caption }}","production":"={{ $json.output[0].Status }}","sound_prompt":"={{ $json.output[0].Sound }}","environment_prompt":"={{ $json.output[0].Environment }}"},"schema":[{"id":"id","type":"string","display":true,"removed":false,"required":false,"displayName":"id","defaultMatch":true,"canBeUsedToMatch":true},{"id":"idea","type":"string","display":true,"required":false,"displayName":"idea","defaultMatch":false,"canBeUsedToMatch":true},{"id":"caption","type":"string","display":true,"required":false,"displayName":"caption","defaultMatch":false,"canBeUsedToMatch":true},{"id":"production","type":"string","display":true,"required":false,"displayName":"production","defaultMatch":false,"canBeUsedToMatch":true},{"id":"environment_prompt","type":"string","display":true,"required":false,"displayName":"environment_prompt","defaultMatch":false,"canBeUsedToMatch":true},{"id":"sound_prompt","type":"string","display":true,"required":false,"displayName":"sound_prompt","defaultMatch":false,"canBeUsedToMatch":true},{"id":"final_output","type":"string","display":true,"required":false,"displayName":"final_output","defaultMatch":false,"canBeUsedToMatch":true}],"mappingMode":"defineBelow","matchingColumns":["id"],"attemptToConvertTypes":false,"convertFieldsToString":false},"options":{},"operation":"append","sheetName":{"__rl":true,"mode":"id","value":"="},"documentId":{"__rl":true,"mode":"id","value":"="}},"credentials":{"googleSheetsOAuth2Api":{"id":"51us92xkOlrvArhV","name":"Google Sheets account"}},"typeVersion":4.5},{"id":"49139fc9-2030-4d10-a9a7-4fd3a3779005","name":"AI Agent: Generate Detailed Video Prompts","type":"@n8n/n8n-nodes-langchain.agent","position":[1760,0],"parameters":{"text":"=Give me 3 video prompts based on the previous idea\n\nUse the Think tool to review your output","options":{"systemMessage":"=Role: You are a prompt-generation AI specializing in cinematic, ASMR-style video prompts. Your task is to generate a multi-scene video sequence that vividly shows a sharp knife actively cutting through a specific object in a clean, high-detail setting.\n\nYour writing must follow this style:\n\nSharp, precise cinematic realism.\n\nMacro-level detail with tight focus on the blade interacting with the object.\n\nThe knife must always be in motion — slicing, splitting, or gliding through the material. Never idle or static.\n\nCamera terms are allowed (e.g. macro view, tight angle, over-the-blade shot).\n\nEach scene must contain all of the following, expressed through detailed visual language:\n\n✅ The main object or subject (from the Idea)\n\n✅ The cutting environment or surface (from the Environment)\n\n✅ The texture, structure, and behavior of the material as it’s being cut\n\n✅ A visible, sharp blade actively cutting\n\nDescriptions should show:\n\nThe physical makeup of the material — is it translucent, brittle, dense, reflective, granular, fibrous, layered, or fluid-filled?\n\nHow the material responds to the blade — resistance, cracking, tearing, smooth separation, tension, vibration.\n\nThe interaction between the blade and the surface — light reflection, buildup of particles, contact points, residue or dust.\n\nAny ASMR-relevant sensory cues like particle release, shimmer, or subtle movement, but always shown visually — not narrated.\n\nTone:\n\nClean, clinical, visual.\n\nNo poetic metaphors, emotion, or storytelling.\n\nAvoid fantasy or surreal imagery.\n\nAll description must feel physically grounded and logically accurate.\n\nLength:\n\nEach scene must be between 1,000 and 2,000 characters.\n\nNo shallow or repetitive scenes — each must be immersive, descriptive, and specific.\n\nEach scene should explore a distinct phase of the cutting process, a different camera perspective, or a new behavior of the material under the blade.\n\nInputs:\n\nIdea: \"{{ $json.idea }}\"\nEnvironment: \"{{ $json.environment_prompt }}\"\nSound: \"{{ $json.sound_prompt }}\"\n\nFormat:\n\nIdea: \"...\"\nEnvironment: \"...\"\nSound: \"...\"\n\nScene 1: \"...\"\nScene 2: \"...\"\nScene 3: \"...\"\nScene 4: \"...\"\nScene 5: \"...\"\nScene 6: \"...\"\nScene 7: \"...\"\nScene 8: \"...\"\nScene 9: \"...\"\nScene 10: \"...\"\nScene 11: \"...\"\nScene 12: \"...\"\nScene 13: \"...\"\n\n"},"promptType":"define","hasOutputParser":true},"typeVersion":1.9},{"id":"4c34c0b0-5c13-4d37-8b51-a209e598513a","name":"LLM: Draft Video Prompt Details (GPT-4.1)","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[1660,280],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-4.1","cachedResultName":"gpt-4.1"},"options":{}},"credentials":{"openAiApi":{"id":"6h3DfVhNPw9I25nO","name":"OpenAi account"}},"typeVersion":1.2},{"id":"5a7828fd-629c-45d4-9ff2-4b57be2eca33","name":"Tool: Refine and Validate Prompts1","type":"@n8n/n8n-nodes-langchain.toolThink","position":[1840,280],"parameters":{},"typeVersion":1},{"id":"bddb974b-e541-4f02-8595-45f76820b38e","name":"Parse Structured Video Prompt Output","type":"@n8n/n8n-nodes-langchain.outputParserStructured","position":[2000,280],"parameters":{"jsonSchemaExample":"{\n  \"Idea\": \"An obsidian rock being sliced with a shimmering knife\",\n  \"Environment\": \"Clean studio table, subtle light reflections\",\n  \"Sound\": \"Crisp slicing, deep grinding, and delicate crumbling\",\n  \"Scene 1\": \"Extreme macro shot: a razor-sharp, polished knife blade presses into the dark, granular surface of an obsidian rock, just beginning to indent.\",\n  \"Scene 2\": \"Close-up: fine, iridescent dust particles erupt from the point of contact as the blade cuts deeper into the obsidian, catching the studio light.\",\n  \"Scene 3\": \"Mid-shot: the knife, held perfectly steady, has formed a shallow, clean groove across the obsidian's shimmering surface, revealing a new, smooth texture.\"\n}"},"typeVersion":1.2},{"id":"443d3b99-1e6c-423c-b8ca-1c5a4c3ba180","name":"Extract Individual Scene Descriptions","type":"n8n-nodes-base.code","position":[680,540],"parameters":{"jsCode":"function findSceneEntries(obj) {\n  const scenes = [];\n\n  for (const [key, value] of Object.entries(obj)) {\n    if (key.toLowerCase().startsWith(\"scene\") && typeof value === \"string\") {\n      scenes.push(value);\n    } else if (typeof value === \"object\" && value !== null) {\n      scenes.push(...findSceneEntries(value));\n    }\n  }\n\n  return scenes;\n}\n\nlet output = [];\n\ntry {\n  const inputData = items[0].json;\n  const scenes = findSceneEntries(inputData);\n\n  if (scenes.length === 0) {\n    throw new Error(\"No scene keys found at any level.\");\n  }\n\n  output = scenes.map(scene => ({ description: scene }));\n} catch (e) {\n  throw new Error(\"Could not extract scenes properly. Details: \" + e.message);\n}\n\nreturn output;\n"},"typeVersion":2},{"id":"78fc7648-9741-48c9-8127-2bdab7070ba7","name":"Generate Video Clips (Wavespeed AI)","type":"n8n-nodes-base.httpRequest","position":[880,540],"parameters":{"url":"https://api.wavespeed.ai/api/v3/bytedance/seedance-v1-pro-t2v-480p","body":"={\n  \"aspect_ratio\": \"9:16\",\n  \"duration\": 10,\n  \"prompt\": \"VIDEO THEME: {{ $('Prompts AI Agent').item.json.output.Idea }} | WHAT HAPPENS IN THE VIDEO: {{ $json.description }} | WHERE THE VIDEO IS SHOT: {{ $('Prompts AI Agent').item.json.output.Environment }}\"\n}\n","method":"POST","options":{"batching":{"batch":{"batchSize":1,"batchInterval":3000}}},"sendBody":true,"contentType":"raw","authentication":"genericCredentialType","rawContentType":"application/json","genericAuthType":"httpHeaderAuth"},"credentials":{"httpHeaderAuth":{"id":"QhpKhFJMiQAReugp","name":"Header Auth account 4"}},"typeVersion":4.2},{"id":"62eb02cb-cf85-4cbe-8688-8fd587e9c19a","name":"Wait for 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\"video_url\": \"{{ $json.data.outputs[0] }}\"\n  }\n","method":"POST","options":{"batching":{"batch":{"batchSize":1,"batchInterval":2000}}},"sendBody":true,"contentType":"raw","authentication":"genericCredentialType","rawContentType":"application/json","genericAuthType":"httpHeaderAuth"},"credentials":{"httpHeaderAuth":{"id":"QhpKhFJMiQAReugp","name":"Header Auth account 4"}},"typeVersion":4.2},{"id":"f8f1eae5-a74b-49be-81fd-2d13e75441c7","name":"Wait for Sound Generation (Fal AI)","type":"n8n-nodes-base.wait","position":[1760,540],"webhookId":"abac7859-a9f6-46f3-95c2-df43ec32807d","parameters":{"amount":60},"typeVersion":1.1},{"id":"4670c2d4-0d66-42e9-891f-1f80508433bb","name":"Retrieve Final Sound Output","type":"n8n-nodes-base.httpRequest","position":[1960,540],"parameters":{"url":"=https://queue.fal.run/fal-ai/mmaudio-v2/requests/{{ $json.request_id 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\"platform\": \"instagram\",\n      \"mediaUrls\": [\n        \"{{ $json.url }}\"\n      ]\n    }\n  }\n}\n\n","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"blotato-api-key","value":"YOUR_API_HERE"}]}},"typeVersion":4.2},{"id":"02da82bf-7931-48cb-af1f-3e9d8c1d584b","name":"YOUTUBE","type":"n8n-nodes-base.httpRequest","position":[1740,1120],"parameters":{"url":"https://backend.blotato.com/v2/posts","method":"POST","options":{},"jsonBody":"={\n  \"post\": {\n    \"accountId\": \"{{ $('Assign Social Media IDs').item.json.youtube_id }}\",\n    \"target\": {\n      \"targetType\": \"youtube\",\n      \"title\": \"{{ $('Get my video').item.json.Titre }}\",\n      \"privacyStatus\": \"unlisted\",\n      \"shouldNotifySubscribers\": \"false\"\n    },\n    \"content\": {\n      \"text\": \"{{ $('Get my video').item.json.DESCRIPTION }}\",\n      \"platform\": \"youtube\",\n      \"mediaUrls\": [\n        \"{{ $json.url }}\"\n      ]\n    }\n  }\n}\n","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"blotato-api-key","value":"YOUR_API_HERE"}]}},"typeVersion":4.2},{"id":"75718ac7-7c63-4be8-a90d-1644515444ca","name":"TIKTOK","type":"n8n-nodes-base.httpRequest","position":[1940,1120],"parameters":{"url":"https://backend.blotato.com/v2/posts","method":"POST","options":{},"jsonBody":"={\n  \"post\": {\n    \"accountId\": \"{{ $('Assign Social Media IDs').item.json.tiktok_id }}\",\n    \"target\": {\n      \"targetType\": \"tiktok\",\n      \"isYourBrand\": \"false\", \n      \"disabledDuet\": \"false\",\n      \"privacyLevel\": \"PUBLIC_TO_EVERYONE\",\n      \"isAiGenerated\": \"true\",\n      \"disabledStitch\": \"false\",\n      \"disabledComments\": \"false\",\n      \"isBrandedContent\": \"false\"\n      \n    },\n    \"content\": {\n      \"text\": \"{{ $('Get my video').item.json.DESCRIPTION }}\",\n      \"platform\": \"tiktok\",\n      \"mediaUrls\": [\n        \"{{ $json.url }}\"\n      ]\n    }\n  }\n}\n","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"blotato-api-key","value":"=YOUR_API_HERE"}]}},"typeVersion":4.2},{"id":"32654f5a-e2dc-4d36-983d-d4c4d0e592a9","name":"FACEBOOK","type":"n8n-nodes-base.httpRequest","position":[1520,1360],"parameters":{"url":"https://backend.blotato.com/v2/posts","method":"POST","options":{},"jsonBody":"={\n  \"post\": {\n    \"accountId\": \"{{ $('Assign Social Media IDs').item.json.facebook_id }}\",\n    \"target\": {\n      \"targetType\": \"facebook\",\n      \"pageId\": \"{{ $('Assign Social Media IDs').item.json.facebook_page_id }}\"\n\n      \n    },\n    \"content\": {\n      \"text\": \"{{ $('Get my video').item.json.DESCRIPTION }}\",\n      \"platform\": \"facebook\",\n      \"mediaUrls\": [\n        \"{{ $json.url }}\"\n      ]\n    }\n  }\n}","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"blotato-api-key","value":"=YOUR_API_HERE"}]}},"typeVersion":4.2},{"id":"e0955970-2ccf-4f8f-91d5-6e795ad10c1a","name":"THREADS","type":"n8n-nodes-base.httpRequest","position":[1740,1360],"parameters":{"url":"https://backend.blotato.com/v2/posts","method":"POST","options":{},"jsonBody":"={\n  \"post\": {\n    \"accountId\": \"{{ $('Assign Social Media IDs').item.json.threads_id }}\",\n    \"target\": {\n      \"targetType\": \"threads\"\n      \n    },\n    \"content\": {\n      \"text\": \"{{ $('Get my video').item.json.DESCRIPTION }}\",\n      \"platform\": \"threads\",\n      \"mediaUrls\": [\n        \"{{ $json.url }}\"\n      ]\n    }\n  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}\n}\n","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"blotato-api-key","value":"YOUR_API_HERE"}]}},"typeVersion":4.2},{"id":"682edc00-f41c-442e-80a6-ff707e0ecd8b","name":"BLUESKY","type":"n8n-nodes-base.httpRequest","position":[1740,1600],"parameters":{"url":"https://backend.blotato.com/v2/posts","method":"POST","options":{},"jsonBody":"= {\n  \"post\": {\n    \"accountId\": \"{{ $('Assign Social Media IDs').item.json.bluesky_id }}\",\n    \"target\": {\n      \"targetType\": \"bluesky\"\n      \n    },\n    \"content\": {\n      \"text\": \"{{ $('Get my video').item.json.DESCRIPTION }}\",\n      \"platform\": \"bluesky\",\n      \"mediaUrls\": [\n        \"https://pbs.twimg.com/media/GE8MgIiWEAAfsK3.jpg\"\n      ]\n    }\n  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name: Tech News_Curator - Analyze Daily News using AI_Agents with Mistral
author_name: Hybroht
author_username: hybroht
categories: []
created_at: 2025-06-25T23:28:14.690Z
updated_at: 2025-06-25T23:28:14.690Z
url: https://n8n.io/workflows/5339
scraped_at: 2025-07-06 21:16:30
description:
  Using Mistral API, you can use this n8n workflow to automate the process of: collecting, filtering, analyzing, and summarizing news articles from multiple sources. The sources come from pre-built RSS feeds and a custom DuckDuckGo node, which you can change if you need.
  It will deliver the most relevant news of the day in a concise manner.


  ++How It Works++**

  The workflow begins each weekday at noon.

  The news are gathered from RSS feeds and a custom DuckDuckGo node, using HTTPS GET when needed.

  News not from today or containing unwanted keywords are filtered out.

  The first AI Agent will select the top news from their titles alone and generate a general title & summary.

  The next AI Agent will summarize the full content of the selected top news articles.

  The general summary and title will be combined with the top 10 news summaries into a final output.


  ++Requirements++

  An active n8n instance (self-hosted or cloud).

  Install the custom DuckDuckGo node: n8n-nodes-duckduckgo-search

  A Mistral API key

  Configure the Sub-Workflow for the content which requires HTTP GET requests. It is provided in the template itself.



  ++Fair Notice++

  This is an older version of the template. There is a superior updated version which isn't restricted to tech news, with enhanced capabilities such as communication through different channels (email, social media) and advanced keyword filtering. It will be published at a later date, but if you are interested or would like to discuss specific needs, then feel free to contact us.

nodes_used:
  ["n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatMistralCloud"]

workflow_json:
  {"id":"DLNC1zlbMqO7vCep","meta":{"instanceId":"c8661626eeda758e004fa6cdc30e89de83810c1ff0923b0bb91a200abd0100f3","templateCredsSetupCompleted":true},"name":"Tech News Curator - Analyze Daily News using AI Agents and Generate Highlights using Mistral V0","tags":[{"id":"QryMJD23lbek4XwO","name":"News Curator","createdAt":"2025-06-20T18:01:44.652Z","updatedAt":"2025-06-20T18:01:44.652Z"},{"id":"nEQ2nHALSQN4jgJ0","name":"Free","createdAt":"2025-06-25T21:55:38.353Z","updatedAt":"2025-06-25T21:55:38.353Z"}],"nodes":[{"id":"12a3d51d-0fb1-4663-ae91-6f7da54f1744","name":"Merge","type":"n8n-nodes-base.merge","position":[-360,700],"parameters":{"numberInputs":9},"typeVersion":3.1},{"id":"49d86034-6aa4-4e59-ac71-36939145022e","name":"Aggregate","type":"n8n-nodes-base.aggregate","position":[800,980],"parameters":{"include":"specifiedFields","options":{},"aggregate":"aggregateAllItemData","fieldsToInclude":"title, pubDate, link"},"typeVersion":1},{"id":"0b7370c2-acba-410b-9f01-f9bbc0228776","name":"ScienceDaily Feed","type":"n8n-nodes-base.rssFeedRead","onError":"continueRegularOutput","position":[-1240,540],"parameters":{"url":"https://www.sciencedaily.com/rss/all.xml","options":{"ignoreSSL":false}},"typeVersion":1.1,"alwaysOutputData":true},{"id":"77e79dc6-1a96-4ac8-843d-fe02c848a15b","name":"AlternativeTo Feed","type":"n8n-nodes-base.rssFeedRead","onError":"continueRegularOutput","position":[-1240,900],"parameters":{"url":"https://feed.alternativeto.net/news/all/","options":{"ignoreSSL":false}},"typeVersion":1.1,"alwaysOutputData":true},{"id":"de23bf0b-e6e9-4654-a603-bd8de610f38d","name":"MIT Technology Review Feed","type":"n8n-nodes-base.rssFeedRead","onError":"continueRegularOutput","position":[-1240,1080],"parameters":{"url":"https://www.technologyreview.com/topic/artificial-intelligence/feed/","options":{"ignoreSSL":false}},"typeVersion":1.1,"alwaysOutputData":true},{"id":"51006112-1569-4e57-a887-b4e70c0feb5a","name":"lobste.rs Feed","type":"n8n-nodes-base.rssFeedRead","onError":"continueRegularOutput","position":[-1240,180],"parameters":{"url":"https://lobste.rs/rss","options":{"ignoreSSL":false}},"typeVersion":1.1,"alwaysOutputData":true},{"id":"03cd83c3-d785-40cd-b20e-9227ce57834d","name":"Filter by Datetime","type":"n8n-nodes-base.filter","position":[20,820],"parameters":{"options":{},"conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"30d4f694-9378-42b4-b1d5-cbc38fb3e7fe","operator":{"type":"dateTime","operation":"after"},"leftValue":"={{ $json.pubDate }}","rightValue":"={{ $today.minus({ days: 0 }) }}"}]}},"typeVersion":2.2},{"id":"da651706-a19a-479f-a955-e1fe603ec0ed","name":"Mistral Cloud Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatMistralCloud","position":[1940,1840],"parameters":{"model":"mistral-small-latest","options":{}},"credentials":{"mistralCloudApi":{"id":"N1af3CxGY2AUEsVg","name":"Mistral Cloud account"}},"typeVersion":1},{"id":"a1a3beac-4b21-4feb-8a4e-3fc7f8b91df5","name":"News Analyzer","type":"@n8n/n8n-nodes-langchain.agent","onError":"continueErrorOutput","maxTries":2,"position":[1020,1120],"parameters":{"text":"=Analyze artitcle titles from the following list:\n[{{ $json.data.map(item => `Title: ${item.title}: Link: ${item.link}`).join(' ; ') }}]","options":{"systemMessage":"You are a professional analyst of current news. Our goal is to get a quick overview of what's most relevant in current news.\nYou must analyze article titles, providing a concise summary of today's news based on the titles.\nFirst, give a fitting title encompassing today's news.\nNext, give a summary of today's news.\nNext, you MUST list the top 10 news of today's titles alongside the links for each of them.\nTo determine the best and most relevant news:\n- Give priority to news which are from the fields: Technological Solutions, Scientific Research, Applied Math and Data Science.\n- Give priority to news which appear often in the list.\n- Ignore news which don't appear to be actual new information.\n- Remove news with problematic headlines\n- Ignore news with petty themes like gossip about actors, hollywood stars and similar.\n- MOST IMPORTANT: DO NOT RETURN TWO OR MORE NEWS FROM THE SAME NEWS WEBSITE. ONLY ONE NEWS PER WEBSITE IN THE TOP 10 when it is possible."},"promptType":"define","hasOutputParser":true},"retryOnFail":true,"typeVersion":1.6},{"id":"423e8ad7-867a-494e-933f-5613e4dbcc57","name":"Split Out News Data","type":"n8n-nodes-base.splitOut","position":[1460,920],"parameters":{"options":{},"fieldToSplitOut":"output.data[0].top_10_news"},"typeVersion":1},{"id":"d1e1aeb6-f42e-4fd8-a351-b4c8229246a7","name":"Remove Certain Content","type":"n8n-nodes-base.filter","position":[360,820],"parameters":{"options":{},"conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"30d4f694-9378-42b4-b1d5-cbc38fb3e7fe","operator":{"type":"string","operation":"notRegex"},"leftValue":"={{ $json.link }}","rightValue":"opinion|rumour|layoff|porn|marijuana"},{"id":"fdddd55b-19d5-4e87-9586-01653750e807","operator":{"type":"string","operation":"notRegex"},"leftValue":"={{ $json.title }}","rightValue":"Opinion|Rumour|layoff|porn|marijuana"},{"id":"12e44449-d6bb-4243-abb7-cfa03a9327c5","operator":{"type":"string","operation":"notRegex"},"leftValue":"={{ $json.content }}","rightValue":"layoff|porn|marijuana"},{"id":"2df9ef75-ea55-4e5b-a78d-e37de85fe8ca","operator":{"type":"string","operation":"notEmpty","singleValue":true},"leftValue":"={{ $json.content }}","rightValue":""}]}},"typeVersion":2.2},{"id":"29888373-da05-4ee0-971d-1dd508823fd2","name":"Silicone Republic Technology Feed","type":"n8n-nodes-base.rssFeedRead","onError":"continueRegularOutput","position":[-1240,1260],"parameters":{"url":"https://www.siliconrepublic.com/category/technology/feed/","options":{"ignoreSSL":false}},"typeVersion":1.1,"alwaysOutputData":true},{"id":"45c3877c-e6d8-4c12-a0b1-2156b0b4dbc4","name":"Silicone Republic Science Feed","type":"n8n-nodes-base.rssFeedRead","onError":"continueRegularOutput","disabled":true,"position":[-1240,1440],"parameters":{"url":"https://www.siliconrepublic.com/category/science/feed/","options":{"ignoreSSL":false}},"typeVersion":1.1,"alwaysOutputData":true},{"id":"d803f64b-24d2-4828-adaa-b55d67112e9e","name":"Schedule","type":"n8n-nodes-base.scheduleTrigger","position":[-1920,880],"parameters":{"rule":{"interval":[{"field":"weeks","triggerAtDay":[5,4,2,3,1],"triggerAtHour":12}]}},"typeVersion":1.2},{"id":"692c7592-9834-48fe-84ab-74216943233a","name":"HTTP Request","type":"n8n-nodes-base.httpRequest","notes":"It is a necessary node because lobste.rs will not give the actual content of the links.","onError":"continueErrorOutput","position":[-840,180],"parameters":{"url":"={{ $json.link }}","options":{"timeout":10000}},"typeVersion":4.2},{"id":"758cbfc6-559a-4ebe-8955-49604bd2d924","name":"Rejoin Data","type":"n8n-nodes-base.set","onError":"continueRegularOutput","position":[-640,360],"parameters":{"options":{},"assignments":{"assignments":[{"id":"e2ffe594-180d-4e1d-b869-8056ac67015d","name":"title","type":"string","value":"={{ $('Filter Fields').item.json.title }}"},{"id":"87c5a171-9ab9-4043-a72a-32aec218fe63","name":"pubDate","type":"string","value":"={{ $('Filter Fields').item.json.pubDate }}"},{"id":"978b05c9-6e6b-4a18-bc06-4de785b19413","name":"link","type":"string","value":"={{ $('Filter Fields').item.json.link }}"},{"id":"199a5920-72a3-470e-9adf-8252f6ebb37a","name":"content","type":"string","value":"={{ $json.data }}"}]}},"typeVersion":3.4},{"id":"93d0ab4e-f3aa-4712-a7ec-95884f396ce8","name":"Join Outputs","type":"n8n-nodes-base.merge","position":[1620,840],"parameters":{"mode":"combine","options":{},"advanced":true,"mergeByFields":{"values":[{"field1":"link","field2":"website"}]}},"typeVersion":3.2},{"id":"69fbc0ca-bd09-40cb-affe-c1955cd990b4","name":"Final Aggregate","type":"n8n-nodes-base.aggregate","position":[2320,820],"parameters":{"include":"specifiedFields","options":{},"aggregate":"aggregateAllItemData","fieldsToInclude":"output"},"typeVersion":1},{"id":"5674a7e0-1aa3-4085-acef-c41d22530140","name":"Website Summarizer","type":"@n8n/n8n-nodes-langchain.agent","onError":"continueErrorOutput","maxTries":2,"position":[1920,840],"parameters":{"text":"=Summarize the content from this website in a sometimes informal, sometimes formal, sometimes complicated, sometimes everyman speech, maybe cheeky, maybe serious, maybe eyecatchy but always concise and short one sentence: {{ $json.website }} - Content: {{ $json.content }}\nFollow the provided JSON schema for your response.","options":{"systemMessage":"=Todays date is {{ $now }}. You are an automated web analyzer tasked with analyzing information from a webpage. You have access to the text content from the page. Your objective is only to return a single JSON output containing the extracted data summarized."},"promptType":"define","hasOutputParser":true},"retryOnFail":true,"typeVersion":1.6},{"id":"7fa67db0-c75a-42ae-9de0-c90a81feb406","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-200,560],"parameters":{"color":3,"width":880,"height":480,"content":"## Filtering Step\n**Filter by Datetime** only allows daily news.\n**Remove Certain Content** to remove unwanted news through use of keywords.\n\nObservation: you can add or remove your own desired keywords as needed."},"typeVersion":1},{"id":"7b943173-28d8-4a1d-86b9-06837e1c38a6","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[740,560],"parameters":{"color":5,"width":640,"height":900,"content":"## News Selection\n**Aggregate** will prep the news for the AI Agent. It will encapsulate the list of news into a singular data.\n**News Analyzer** is the Agent which will use the Chat Model to make an appropriate title and summary of today's news. The AI will make a list of the top news. Mind you, it will decide the best news to read just like the average person would: through the titles.\n**Mistral Cloud Chat Model** is used instead of OpenAI because it is Dev friendly. Mistral allows you to test their API for free. Recommended for hobbyist. \n**Json Output Parser** forces the AI Agent to structure the output in its defined Json format. This is important to make the AI output both consistent and usable. Otherwise, you might end up with one of the following problems: incomplete answers, nonconforming answers or straight up gibberish. "},"typeVersion":1},{"id":"a1d89fc5-4f6d-4e15-be60-a22ff049ccbb","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[1420,560],"parameters":{"color":5,"width":1060,"height":580,"content":"## News Summarizer\n**Split Out News Data** will prep the top news selected by the News Analyzer. The Top News have their website content in a former step of this workflow, so they must be joined again in an inner manner.\n**Join Output** will join the selected top news with their respective textual content.\n**Website Summarizer** will take the textual content of each news and summarize it, using **Mistral Cloud Chat Model** and **Json Output Parser** to produce the appropriate output.\n**Final Aggregate** will prep the summaries of the news for the final step of the Workflow. It will encapsulate the list of summaries into a singular data.\n\n* Observation: Website Summarizer will discard any output which it fails to properly structure as configured by the Json Output Parser."},"typeVersion":1},{"id":"d1942504-dc3d-4ae7-b342-28d26827945b","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[-1760,-240],"parameters":{"color":4,"width":1520,"height":2060,"content":"# Tech News Gathering\n**Schedule** will start the workflow according to its configuration. In this workflow, it is configured to start every weekday after 12:00 PM.\n**Feed Nodes** will get the RSS feed of their respective sources.\n**Field Prep** will ensure the RSS outputs are structured in the same manner for the merge.\n**Merge** will unite the outputs into one big list with news from each of them.\n\n"},"typeVersion":1},{"id":"6fdcf852-4638-4081-8621-b4f4cc6e03d6","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[-1080,-80],"parameters":{"color":3,"width":660,"height":1880,"content":"## Field Prep\n- Standardize RSS outputs\n- Remove Fields\n- Add Info as Needed\n\n*Obs: set the Sub-Workflow \"Get Webage Content\". ([Guide](https://docs.n8n.io/workflows/subworkflow-conversion/))"},"typeVersion":1},{"id":"ca60f20b-cc2f-4172-92bd-d993d8bdefd3","name":"Sticky Note6","type":"n8n-nodes-base.stickyNote","position":[-1680,-80],"parameters":{"color":6,"width":600,"height":1880,"content":"## Feed Nodes\nEach node will get a list of news from a RSS feed or a search engine (in our case, DuckDuckGo).\n\n*Observation: \nThe DuckDuckGo custom node is called: n8n-nodes-duckduckgo-search\nYou will need to install it."},"typeVersion":1},{"id":"a7b40eed-b05a-4892-b7ec-fc3f4c328b6b","name":"Sticky Note7","type":"n8n-nodes-base.stickyNote","position":[-200,320],"parameters":{"width":540,"height":220,"content":"In the end of the **News Gathering step**, the output of merge should contain a list of news with the following properties: title, pubDate, link and content.\n\n*Observation: you could try to avoid RSS feeds, but it would still require you to structure the data.\n**Advice: Do not seek to avoid structuring the data**. It is not recommended when dealing with AI Agents.\n\n*About the Merge: if you connect more than one output in a Merge node input, then you risk the Merge node continuing the Workflow before all the news sources returned their output."},"typeVersion":1},{"id":"30ec121c-d5ed-405d-8c6b-7d31daea4f19","name":"TheHackersNews* Feed","type":"n8n-nodes-base.rssFeedRead","notes":"*Not to be confused with \"Hacker News\" from ycombinator.","onError":"continueRegularOutput","position":[-1240,720],"parameters":{"url":"https://feeds.feedburner.com/TheHackersNews","options":{"ignoreSSL":false}},"typeVersion":1.1,"alwaysOutputData":true},{"id":"0be003b9-f7d7-44f4-ab6a-7812060e8344","name":"Filter Fields","type":"n8n-nodes-base.set","position":[-1020,180],"parameters":{"options":{},"assignments":{"assignments":[{"id":"e2ffe594-180d-4e1d-b869-8056ac67015d","name":"title","type":"string","value":"={{ $json.title 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\"The link of the news article.\"\n          },\n          \"summary\": {\n\t\t\t\"type\": \"string\",\n            \"description\": \"The resume of the news article.\"\n          }\n        },\n        \"required\": [\"title\", \"author\", \"link\", \"summary\"],\n        \"additionalProperties\": false\n      }\n    }\n  },\n  \"required\": [\"data\"],\n  \"additionalProperties\": false\n}"},"typeVersion":1.2},{"id":"11ee267f-6429-48dd-aa01-3e1e0cd49a50","name":"JSON Output Parser","type":"@n8n/n8n-nodes-langchain.outputParserStructured","position":[1260,1280],"parameters":{"schemaType":"manual","inputSchema":"{\n  \"type\": \"object\",\n  \"properties\": {\n    \"data\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"properties\": {\n          \"title\": {\n            \"type\": \"string\",\n            \"description\": \"The name describing the overall news.\"\n          },\n          \"summary\": {\n\t\t\t\"type\": \"string\",\n            \"description\": \"The resume of today's news.\"\n          },\n          \"top_10_news\": {\n\t\t\t\"type\": \"array\",\n\t\t\t\"items\": {\n\t\t\t  \"type\": \"object\",\n\t\t\t  \"properties\": {\n\t\t\t\t\"title\": {\n\t\t\t\t  \"type\": \"string\",\n\t\t\t\t  \"description\": \"The title to the news article.\"\n\t\t\t\t},\n\t\t\t\t\"website\": {\n\t\t\t\t  \"type\": \"string\",\n\t\t\t\t  \"description\": \"The website to the news article.\"\n\t\t\t\t},\n                \"required\": [\"title\", \"website\"],\n                \"additionalProperties\": false\n\t\t\t  }\n\t\t\t}\n          }\n        },\n        \"required\": [\"title\", \"summary\", \"top_10_news\"],\n        \"additionalProperties\": false\n      }\n    }\n  },\n  \"required\": [\"data\"],\n  \"additionalProperties\": false\n  }\n"},"typeVersion":1.2},{"id":"f841eedd-91b2-4ef8-ba49-d46999f05802","name":"DuckDuckGo","type":"n8n-nodes-duckduckgo-search.duckDuckGo","position":[-1240,1620],"parameters":{"newsQuery":"technology","operation":"searchNews","cacheSettings":{"cacheTTL":300,"enableCache":true},"proxySettings":{},"newsSearchOptions":{"region":"wt-wt","maxResults":100,"safeSearch":0}},"typeVersion":1},{"id":"9dc00e4e-15c4-4fce-acc4-b67c3de99bcb","name":"Filter Fields 9","type":"n8n-nodes-base.set","position":[-1040,1620],"parameters":{"options":{},"assignments":{"assignments":[{"id":"e2ffe594-180d-4e1d-b869-8056ac67015d","name":"title","type":"string","value":"={{ $json.title }}"},{"id":"87c5a171-9ab9-4043-a72a-32aec218fe63","name":"pubDate","type":"string","value":"={{ $json.date }}"},{"id":"978b05c9-6e6b-4a18-bc06-4de785b19413","name":"link","type":"string","value":"={{ $json.url }}"},{"id":"199a5920-72a3-470e-9adf-8252f6ebb37a","name":"content","type":"string","value":"="}]}},"typeVersion":3.4},{"id":"92732b78-71a2-4d4e-91f3-41231153046b","name":"Call Get Webpage Content to Data","type":"n8n-nodes-base.executeWorkflow","position":[-860,1620],"parameters":{"options":{},"workflowId":{"__rl":true,"mode":"id","value":"MqafS0zommXM7soB"},"workflowInputs":{"value":{"link":"={{ $json.link }}","title":"={{ $json.title }}","pubDate":"={{ $json.pubDate }}"},"schema":[{"id":"title","display":true,"removed":false,"required":false,"displayName":"title","defaultMatch":false,"canBeUsedToMatch":true},{"id":"pubDate","display":true,"removed":false,"required":false,"displayName":"pubDate","defaultMatch":false,"canBeUsedToMatch":true},{"id":"link","display":true,"removed":false,"required":false,"displayName":"link","defaultMatch":false,"canBeUsedToMatch":true}],"mappingMode":"defineBelow","matchingColumns":["title","pubDate","link"],"attemptToConvertTypes":false,"convertFieldsToString":true}},"typeVersion":1.2},{"id":"1ba68823-f76e-4277-a9d1-90d549ad080b","name":"Sticky Note8","type":"n8n-nodes-base.stickyNote","position":[-200,1060],"parameters":{"color":2,"width":680,"height":540,"content":"## Sub-Workflow : Get Webpage Content to Data\nThis Sub-Workflow will deal with cases where the content of the link is not immediately given by Source Node."},"typeVersion":1},{"id":"dc42e913-8d41-41c5-bd40-7ba006b1d361","name":"Remove Elements with Empty Content","type":"n8n-nodes-base.filter","position":[-660,1320],"parameters":{"options":{},"conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"30d4f694-9378-42b4-b1d5-cbc38fb3e7fe","operator":{"type":"string","operation":"notEmpty","singleValue":true},"leftValue":"={{ $json.content }}","rightValue":"={{ $today.minus({ days: 0 }) }}"}]}},"typeVersion":2.2},{"id":"d5053c20-a8af-4d9e-b2b6-02c51044ecdd","name":"HTTP Request Example","type":"n8n-nodes-base.httpRequest","notes":"It is a necessary node because lobste.rs will not give the actual content of the links.","onError":"continueErrorOutput","position":[-40,1220],"parameters":{"url":"={{ $json.link }}","options":{"timeout":3000}},"typeVersion":4.2},{"id":"2461638a-9de6-4a67-b287-0e0102e32764","name":"Rejoin Data Example","type":"n8n-nodes-base.set","onError":"continueRegularOutput","position":[20,1440],"parameters":{"options":{},"assignments":{"assignments":[{"id":"e2ffe594-180d-4e1d-b869-8056ac67015d","name":"title","type":"string","value":"={{ $('Filter Fields').item.json.title }}"},{"id":"87c5a171-9ab9-4043-a72a-32aec218fe63","name":"pubDate","type":"string","value":"={{ $('Filter Fields').item.json.pubDate }}"},{"id":"978b05c9-6e6b-4a18-bc06-4de785b19413","name":"link","type":"string","value":"={{ $('Filter Fields').item.json.link }}"},{"id":"199a5920-72a3-470e-9adf-8252f6ebb37a","name":"content","type":"string","value":"={{ $json.data }}"}]}},"typeVersion":3.4},{"id":"b7d64a46-2656-45a8-8053-3c6fa6df6e4f","name":"Markdown Conversion Example","type":"n8n-nodes-base.markdown","onError":"continueRegularOutput","position":[200,1200],"parameters":{"html":"={{ $json.data }}","options":{}},"typeVersion":1},{"id":"bd46c6d8-f235-4bad-9866-e0c1a72bc6e3","name":"Final Join Outputs","type":"n8n-nodes-base.merge","position":[2680,1080],"parameters":{"mode":"combine","options":{},"combineBy":"combineByPosition"},"typeVersion":3.2},{"id":"4894d04d-7e11-4af0-9370-c6eefdad1371","name":"Test Feed","type":"n8n-nodes-base.rssFeedRead","onError":"continueRegularOutput","disabled":true,"position":[-1240,340],"parameters":{"options":{}},"typeVersion":1.1,"alwaysOutputData":true}],"active":false,"pinData":{},"settings":{"executionOrder":"v1"},"versionId":"ac25536e-1d15-4254-b8cd-0efadf052a5f","connections":{"Merge":{"main":[[{"node":"Filter by Datetime","type":"main","index":0}]]},"Schedule":{"main":[[{"node":"lobste.rs Feed","type":"main","index":0},{"node":"Test Feed","type":"main","index":0},{"node":"ScienceDaily Feed","type":"main","index":0},{"node":"TheHackersNews* Feed","type":"main","index":0},{"node":"AlternativeTo Feed","type":"main","index":0},{"node":"MIT Technology Review Feed","type":"main","index":0},{"node":"Silicone Republic Technology Feed","type":"main","index":0},{"node":"Silicone Republic Science Feed","type":"main","index":0},{"node":"DuckDuckGo","type":"main","index":0}]]},"Aggregate":{"main":[[{"node":"News Analyzer","type":"main","index":0}]]},"Test Feed":{"main":[[{"node":"Filter Fields 2","type":"main","index":0}]]},"DuckDuckGo":{"main":[[{"node":"Filter Fields 9","type":"main","index":0}]]},"Rejoin Data":{"main":[[{"node":"Merge","type":"main","index":0}]]},"HTTP Request":{"main":[[{"node":"Markdown Conversion","type":"main","index":0}]]},"Join Outputs":{"main":[[{"node":"Website Summarizer","type":"main","index":0}]]},"Filter Fields":{"main":[[{"node":"HTTP Request","type":"main","index":0}]]},"News Analyzer":{"main":[[{"node":"Split Out News Data","type":"main","index":0},{"node":"Final Join Outputs","type":"main","index":1}]]},"lobste.rs Feed":{"main":[[{"node":"Filter Fields","type":"main","index":0}]]},"Filter Fields 2":{"main":[[{"node":"Merge","type":"main","index":1}]]},"Filter Fields 3":{"main":[[{"node":"Merge","type":"main","index":2}]]},"Filter Fields 4":{"main":[[{"node":"Merge","type":"main","index":3}]]},"Filter Fields 5":{"main":[[{"node":"Merge","type":"main","index":4}]]},"Filter Fields 6":{"main":[[{"node":"Merge","type":"main","index":5}]]},"Filter Fields 7":{"main":[[{"node":"Merge","type":"main","index":6}]]},"Filter Fields 8":{"main":[[{"node":"Merge","type":"main","index":7}]]},"Filter Fields 9":{"main":[[{"node":"Call Get Webpage Content to Data","type":"main","index":0}]]},"Final Aggregate":{"main":[[{"node":"Final Join Outputs","type":"main","index":0}]]},"ScienceDaily Feed":{"main":[[{"node":"Filter Fields 3","type":"main","index":0}]]},"AlternativeTo Feed":{"main":[[{"node":"Filter Fields 5","type":"main","index":0}]]},"Filter by Datetime":{"main":[[{"node":"Remove Certain Content","type":"main","index":0}]]},"Final Join Outputs":{"main":[[]]},"JSON Output Parser":{"ai_outputParser":[[{"node":"News Analyzer","type":"ai_outputParser","index":0}]]},"Website Summarizer":{"main":[[{"node":"Final Aggregate","type":"main","index":0}]]},"Markdown Conversion":{"main":[[{"node":"Rejoin Data","type":"main","index":0}]]},"Split Out News Data":{"main":[[{"node":"Join Outputs","type":"main","index":1}]]},"HTTP Request Example":{"main":[[{"node":"Markdown Conversion Example","type":"main","index":0}]]},"JSON Output Parser 2":{"ai_outputParser":[[{"node":"Website Summarizer","type":"ai_outputParser","index":0}]]},"TheHackersNews* Feed":{"main":[[{"node":"Filter Fields 4","type":"main","index":0}]]},"Remove Certain Content":{"main":[[{"node":"Aggregate","type":"main","index":0},{"node":"Join Outputs","type":"main","index":0}]]},"Mistral Cloud Chat Model":{"ai_languageModel":[[{"node":"News Analyzer","type":"ai_languageModel","index":0},{"node":"Website Summarizer","type":"ai_languageModel","index":0}]]},"MIT Technology Review Feed":{"main":[[{"node":"Filter Fields 6","type":"main","index":0}]]},"Markdown Conversion Example":{"main":[[{"node":"Rejoin Data Example","type":"main","index":0}]]},"Silicone Republic Science Feed":{"main":[[{"node":"Filter Fields 8","type":"main","index":0}]]},"Call Get Webpage Content to Data":{"main":[[{"node":"Remove Elements with Empty Content","type":"main","index":0}]]},"Silicone Republic Technology Feed":{"main":[[{"node":"Filter Fields 7","type":"main","index":0}]]},"Remove Elements with Empty Content":{"main":[[{"node":"Merge","type":"main","index":8}]]}}}


name: 🛠️ PagerDuty Tool MCP Server 💪 all 9 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T02:56:34.295Z
updated_at: 2025-06-26T02:56:34.295Z
url: https://n8n.io/workflows/5343
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ PagerDuty Tool MCP Server

  Complete MCP server exposing all PagerDuty Tool operations to AI agents. Zero configuration needed - all 9 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every PagerDuty Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n PagerDuty Tool tool with full error handling

  📋 Available Operations (9 total)

  Every possible PagerDuty Tool operation is included:

  🔧 Incident (4 operations)

  • Create an incident
  • Get an incident
  • Get many incidents
  • Update an incident

  🔧 Incidentnote (2 operations)

  • Create an incident note
  • Get many incident notes

  🔧 Logentry (2 operations)

  • Get a log entry
  • Get many log entries

  👤 User (1 operations)

  • Get a user

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native PagerDuty Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every PagerDuty Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
  {"id":"Daa0fHTZUAHEhh3I","meta":null,"name":"PagerDuty Tool MCP Server","tags":[],"nodes":[{"id":"efc35196-0fea-4fdb-bc00-a48bd7d6d51c","name":"Workflow Overview 0","type":"n8n-nodes-base.stickyNote","position":[-1460,120],"parameters":{"width":420,"height":840,"content":"## 🛠️ PagerDuty Tool MCP Server\n\n### 📋 Available Operations (9 total)\n\n**Incident**: create, get, get all, update\n**Incidentnote**: create, get all\n**Logentry**: get, get all\n**User**: get\n\n### ⚙️ Setup Instructions\n\n1. **Import Workflow**: Load this workflow into your n8n instance\n\n1. **🔑 Add Credentials**: Configure PagerDuty Tool authentication in one tool node then open and close all others.\n2. **🚀 Activate**: Enable this workflow to start your MCP server\n3. **🔗 Get URL**: Copy webhook URL from MCP trigger (right side)\n4. **🤖 Connect**: Use MCP URL in your AI agent configurations\n\n### ✨ Ready-to-Use Features\n\n• Zero configuration - all 9 operations pre-built\n• AI agents automatically populate parameters via `$fromAI()` expressions\n• Every resource and operation combination available\n• Native n8n error handling and response formatting\n• Modify parameter defaults in any tool node as needed\n\n### 💬 Need Help?\nCheck the [n8n documentation](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolmcp/) or ping me on [discord](https://discord.me/cfomodz) for MCP integration guidance or customizations."},"typeVersion":1},{"id":"d6832592-9cb8-48a0-b4eb-a89e42c2551d","name":"PagerDuty Tool MCP Server","type":"@n8n/n8n-nodes-langchain.mcpTrigger","position":[-400,-100],"webhookId":"28d5f677-4c8b-4fb4-95c2-e5ce0bd0a78b","parameters":{"path":"pagerduty-tool-mcp"},"typeVersion":1},{"id":"68734679-1eb0-4566-9fd9-79d3059672f2","name":"Create an incident","type":"n8n-nodes-base.pagerDutyTool","position":[-800,140],"parameters":{"email":"={{ $fromAI('Email', ``, 'string') }}","title":"={{ $fromAI('Title', ``, 'string') }}","resource":"incident","operation":"create","serviceId":"={{ $fromAI('Service_Id', ``, 'string') }}","authentication":"apiToken","descriptionType":"auto","additionalFields":{},"conferenceBridgeUi":{}},"typeVersion":1},{"id":"fba20f11-5f83-416a-95e6-4e5b1e21da94","name":"Get an incident","type":"n8n-nodes-base.pagerDutyTool","position":[-580,140],"parameters":{"operation":"get","incidentId":"={{ $fromAI('Incident_Id', ``, 'string') }}"},"typeVersion":1},{"id":"0c40e9c7-9747-42a5-88d4-c312d757738a","name":"Get many incidents","type":"n8n-nodes-base.pagerDutyTool","position":[-360,140],"parameters":{"limit":"={{ $fromAI('Limit', ``, 'number') }}","options":{},"operation":"getAll","returnAll":"={{ $fromAI('Return_All', ``, 'boolean') }}"},"typeVersion":1},{"id":"9f6f4608-0d7b-4773-9e26-07d374c228bd","name":"Update an incident","type":"n8n-nodes-base.pagerDutyTool","position":[-140,140],"parameters":{"email":"={{ $fromAI('Email', ``, 'string') 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}}"},"typeVersion":1},{"id":"375fc00c-39af-47aa-8073-af7fae24c0a7","name":"Sticky Note 3","type":"n8n-nodes-base.stickyNote","position":[-1000,600],"parameters":{"color":6,"width":620,"content":"## Logentry"},"typeVersion":1},{"id":"ae126468-762a-4588-aa48-aac6de257c06","name":"Get a user","type":"n8n-nodes-base.pagerDutyTool","position":[-800,860],"parameters":{"userId":"={{ $fromAI('User_Id', ``, 'string') }}","resource":"user"},"typeVersion":1},{"id":"b6442def-7516-40c7-b959-1dc130d9cf52","name":"Sticky Note 4","type":"n8n-nodes-base.stickyNote","position":[-1000,840],"parameters":{"color":7,"width":400,"content":"## User"},"typeVersion":1}],"active":false,"shared":[{"role":"workflow:owner","project":{"id":"G5fce9xGuBAsWBXe","icon":null,"name":"David Ashby <david.ashby.lds@gmail.com>","type":"personal","createdAt":"2025-06-04T02:55:02.013Z","updatedAt":"2025-06-04T02:56:01.361Z","projectRelations":[{"role":"project:personalOwner","user":{"id":"715c1c00-cb48-4712-9a32-f1f4b6db2b30","role":"global:owner","email":"david.ashby.lds@gmail.com","disabled":false,"lastName":"Ashby","settings":{"npsSurvey":{"responded":true,"lastShownAt":1749357655581},"userActivated":true,"userActivatedAt":1749075994495,"easyAIWorkflowOnboarded":true,"firstSuccessfulWorkflowId":"3N3vVikZb3MckFYm"},"createdAt":"2025-06-04T02:55:01.745Z","firstName":"David","isPending":false,"updatedAt":"2025-06-08T04:40:58.399Z","mfaEnabled":false,"personalizationAnswers":{"version":"v4","personalization_survey_n8n_version":"1.95.3","personalization_survey_submitted_at":"2025-06-04T02:56:07.075Z"}},"userId":"715c1c00-cb48-4712-9a32-f1f4b6db2b30","createdAt":"2025-06-04T02:55:02.013Z","projectId":"G5fce9xGuBAsWBXe","updatedAt":"2025-06-04T02:55:02.013Z"}]},"createdAt":"2025-06-21T09:29:31.003Z","projectId":"G5fce9xGuBAsWBXe","updatedAt":"2025-06-21T09:29:31.003Z","workflowId":"Daa0fHTZUAHEhh3I"}],"pinData":{},"settings":{"timezone":"America/New_York"},"createdAt":"2025-06-21T09:29:31.002Z","updatedAt":"2025-06-21T09:30:02.000Z","versionId":"eb7a3399-b11b-4b8b-9e26-1f2a2b284d0e","isArchived":false,"staticData":null,"connections":{"Get a user":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Get a log entry":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Get an incident":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Create an incident":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Get many incidents":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Update an incident":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Get many log entries":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Create an incident note":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]},"Get many incident notes":{"ai_tool":[[{"node":"PagerDuty Tool MCP Server","type":"ai_tool","index":0}]]}},"triggerCount":0}


name: 🛠️ One Simple API Tool MCP Server 💪 all 10 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T02:57:43.191Z
updated_at: 2025-06-26T02:57:43.191Z
url: https://n8n.io/workflows/5344
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ One Simple API Tool MCP Server

  Complete MCP server exposing all One Simple API Tool operations to AI agents. Zero configuration needed - all 10 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every One Simple API Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n One Simple API Tool tool with full error handling

  📋 Available Operations (10 total)

  Every possible One Simple API Tool operation is included:

  🔧 Information (2 operations)

  • Convert a value between currencies
  • Get image metadata from a URL

  🔧 Socialprofile (2 operations)

  • Get details about an Instagram profile
  • Get details about a Spotify artist

  🔧 Utility (3 operations)

  • Expand a shortened URL
  • Generate a QR code utility
  • Validate an email address

  🔧 Website (3 operations)

  • Generate PDF
  • Get SEO Data
  • Screenshot

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native One Simple API Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every One Simple API Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
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name: 🛠️ QuickBooks Online Tool MCP Server 💪 all 42 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T03:06:20.397Z
updated_at: 2025-06-26T03:06:20.397Z
url: https://n8n.io/workflows/5354
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ QuickBooks Online Tool MCP Server

  Complete MCP server exposing all QuickBooks Online Tool operations to AI agents. Zero configuration needed - all 42 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every QuickBooks Online Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n QuickBooks Online Tool tool with full error handling

  📋 Available Operations (42 total)

  Every possible QuickBooks Online Tool operation is included:

  🔧 Bill (5 operations)

  • Create a bill
  • Delete a bill
  • Get a bill
  • Get many bills
  • Update a bill

  🔧 Customer (4 operations)

  • Create a customer
  • Get a customer
  • Get many customers
  • Update a customer

  🔧 Employee (4 operations)

  • Create an employee
  • Get an employee
  • Get many employees
  • Update an employee

  🔧 Estimate (6 operations)

  • Create an estimate
  • Delete an estimate
  • Get an estimate
  • Get many estimates
  • Send an estimate
  • Update an estimate

  🔧 Invoice (7 operations)

  • Create an invoice
  • Delete an invoice
  • Get an invoice
  • Get many invoices
  • Send an invoice
  • Update an invoice
  • Void an invoice

  🔧 Item (2 operations)

  • Get an item
  • Get many items

  🔧 Payment (7 operations)

  • Create a payment
  • Delete a payment
  • Get a payment
  • Get many payments
  • Send a payment
  • Update a payment
  • Void a payment

  🔧 Purchase (2 operations)

  • Get a purchase
  • Get many purchases

  🔧 Transaction (1 operations)

  • Get a report

  🔧 Vendor (4 operations)

  • Create a vendor
  • Get a vendor
  • Get many vendors
  • Update a vendor

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native QuickBooks Online Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every QuickBooks Online Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

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name: 🛠️ Reddit Tool MCP Server 💪 all 13 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T03:06:56.294Z
updated_at: 2025-06-26T03:06:56.294Z
url: https://n8n.io/workflows/5355
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Reddit Tool MCP Server

  Complete MCP server exposing all Reddit Tool operations to AI agents. Zero configuration needed - all 13 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Reddit Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Reddit Tool tool with full error handling

  📋 Available Operations (13 total)

  Every possible Reddit Tool operation is included:

  🔧 Post (5 operations)

  • Create a post
  • Delete a post
  • Get a post
  • Get many posts
  • Search for a post

  🔧 Postcomment (4 operations)

  • Create a comment in a post
  • Get many comments in a post
  • Delete a comment from a post
  • Reply to a comment in a post

  🔧 Profile (1 operations)

  • Get a profile

  🔧 Subreddit (2 operations)

  • Get a subreddit
  • Get many subreddits

  👤 User (1 operations)

  • Get a user

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Reddit Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Reddit Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

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name: 🛠️ Splunk Tool MCP Server 💪 all 16 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T03:09:05.208Z
updated_at: 2025-06-26T03:09:05.208Z
url: https://n8n.io/workflows/5359
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Splunk Tool MCP Server

  Complete MCP server exposing all Splunk Tool operations to AI agents. Zero configuration needed - all 16 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Splunk Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Splunk Tool tool with full error handling

  📋 Available Operations (16 total)

  Every possible Splunk Tool operation is included:

  🔧 Alert (2 operations)

  • Get a fired alerts report
  • Get metrics

  🔧 Report (4 operations)

  • Create a search report
  • Delete a search report
  • Get a search report
  • Get many search reports

  🔧 Search (5 operations)

  • Create a search job
  • Delete a search job
  • Get a search job
  • Get many search jobs
  • Get the result of a search job

  👤 User (5 operations)

  • Create a user
  • Delete a user
  • Get a user
  • Get many users
  • Update a user

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Splunk Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Splunk Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

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name: 🛠️ Spotify Tool MCP Server 💪 all 30 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T03:10:02.426Z
updated_at: 2025-06-26T03:10:02.426Z
url: https://n8n.io/workflows/5360
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Spotify Tool MCP Server

  Complete MCP server exposing all Spotify Tool operations to AI agents. Zero configuration needed - all 30 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Spotify Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Spotify Tool tool with full error handling

  📋 Available Operations (30 total)

  Every possible Spotify Tool operation is included:

  🔧 Album (4 operations)

  • Get an album
  • Get new album releases
  • Get an album's tracks by URI or ID
  • Search albums by keyword

  🔧 Artist (5 operations)

  • Get an artist
  • Get an artist's albums by URI or ID
  • Get an artist's related artists by URI or ID
  • Get an artist's top tracks by URI or ID
  • Search artists by keyword

  🔧 Library (1 operations)

  • Get liked tracks

  🔧 Mydata (1 operations)

  • Get your followed artists

  🔧 Player (9 operations)

  • Add a song to a queue
  • Get the currently playing track
  • Skip to the next track
  • Pause the player
  • Skip to the previous song
  • Get the recently played tracks
  • Resume the player
  • Set volume on the player
  • Start music on the player

  🔧 Playlist (7 operations)

  • Add an Item to a playlist
  • Create a playlist
  • Get a playlist
  • Get a user's playlists
  • Get a playlist's tracks by URI or ID
  • Remove an item from a playlist
  • Search playlists by keyword

  🔧 Track (3 operations)

  • Get a track
  • Get audio features of a track
  • Search tracks by keyword

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Spotify Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Spotify Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

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name: 🛠️ Storyblok Tool MCP Server 💪 all 7 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T03:10:39.207Z
updated_at: 2025-06-26T03:10:39.207Z
url: https://n8n.io/workflows/5361
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Storyblok Tool MCP Server

  Complete MCP server exposing all Storyblok Tool operations to AI agents. Zero configuration needed - all 7 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Storyblok Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Storyblok Tool tool with full error handling

  📋 Available Operations (7 total)

  Every possible Storyblok Tool operation is included:

  🔧 Story (7 operations)

  • Get a story
  • Get many stories
  • Delete a story
  • Get a story
  • Get many stories
  • Publish a story
  • Unpublish a story

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Storyblok Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Storyblok Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
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name: 🛠️ Strapi Tool MCP Server 💪 5 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T03:11:13.545Z
updated_at: 2025-06-26T03:11:13.545Z
url: https://n8n.io/workflows/5362
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Strapi Tool MCP Server

  Complete MCP server exposing all Strapi Tool operations to AI agents. Zero configuration needed - all 5 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Strapi Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Strapi Tool tool with full error handling

  📋 Available Operations (5 total)

  Every possible Strapi Tool operation is included:

  🔧 Entry (5 operations)

  • Create an entry
  • Delete an entry
  • Get an entry
  • Get many entries
  • Update an entry

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Strapi Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Strapi Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

workflow_json:
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name: 🛠️ Strava Tool MCP Server 💪 all 9 operations
author_name: David Ashby
author_username: cfomodz
nodes_used: []
categories: []
created_at: 2025-06-26T03:11:45.068Z
updated_at: 2025-06-26T03:11:45.068Z
url: https://n8n.io/workflows/5363
scraped_at: 2025-07-06 21:16:30
description:
  🛠️ Strava Tool MCP Server

  Complete MCP server exposing all Strava Tool operations to AI agents. Zero configuration needed - all 9 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Strava Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Strava Tool tool with full error handling

  📋 Available Operations (9 total)

  Every possible Strava Tool operation is included:

  🔧 Activity (9 operations)

  • Create an activity
  • Get an activity
  • Get all activity comments
  • Get all activity kudos
  • Get all activity laps
  • Get many activities
  • Get all activity streams
  • Get all activity zones
  • Update an activity

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Strava Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Strava Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  🆓 Free for community use! Ready to deploy in under 2 minutes.

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