# templates

name: Generate & Publish AI Cinematic Videos to YouTube Shorts using VEO3 & Gemini
author_name: Sulieman Said
author_username: sulieman-said
categories: []
created_at: 2025-08-28T20:07:27.635Z
updated_at: 2025-08-28T20:07:27.635Z
url: https://n8n.io/workflows/8004
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  How it Works
  This workflow uses VEO3 to generate surreal cinematic AI videos at a fraction of the cost compared to Google’s standard video generation APIs.  
  With it, you can automatically run a YouTube Shorts channel (and optionally Instagram uploads) that posts new AI videos every day  completely automated.  

  Workflow Overview  
  Schedule Trigger  
     Runs automatically at your chosen times (e.g., twice per day).  

  AI Prompt Generator  
     Creates a detailed video idea based on your chosen niche.  
     You only need to adapt the system prompt to your theme (e.g., Travel Facts, Tech Visuals, Mini-Facts, Impossible Realities, Food Illusions).  
     Output includes:  
       Video Prompt (for VEO3 API)  
       Social Caption with hashtags  
       YouTube Title  
       YouTube Description  

  VEO3 Video Generation  
     Sends the prompt to KIE AI VEO3 (model: veo3_fast).  
     Produces 9:16 vertical short-form videos optimized for YouTube Shorts, TikTok, Instagram Reels.  
     Significantly cheaper than Google’s Video AI while delivering cinematic quality.  

  Publishing  
     Uploads automatically to YouTube Shorts (with AI-generated titles, descriptions, tags).  
     In parallel, posts the same video to a Telegram channel (Instagram upload possible with a small modification).  

  Why Use This Workflow?  
  Cost Advantage:**  
    Google’s video generation is very expensive.  
    VEO3 costs are much lower, making it possible to publish multiple Shorts every day without breaking your budget.  

  Automated Channel Growth:**  
    Build a fully automated YouTube Shorts channel.  
    Post fresh videos daily → more reach, more chances to go viral.  

  Flexible Niches:**  
    Simply edit the system prompt to match your niche.  
    Examples:  
      Mini Facts Channel  
      Surreal Visual Loops  
      Tech Explainers in Visual Form  
      Food or Nature Illusions  
    The AI adapts automatically to your theme.  

  Cross-Platform:**  
    Out of the box: YouTube + Telegram.  
    With small adjustments: Instagram Reels, TikTok uploads possible.  

  Setup Steps  
  Get API Keys:  
     KIE AI VEO3 API key.  
     YouTube API credentials (OAuth2).  
     (Optional) Telegram Bot API or Instagram Graph API.  

  Configure Schedule:  
     Define how often you want new videos (e.g., 1–5 per day).  

  Adapt Prompts:  
     Change the AI Agent system prompt to your target niche.  

  Run & Scale:  
     Let the workflow run automatically.  
     Watch your channel fill with new daily Shorts.  

  Tips & Notes  
  With VEO3 you can experiment with higher volume since costs are predictable and far lower than Google.  
  Start with one niche channel → once it works, clone the workflow to build multiple parallel AI-driven channels.  
  Always respect YouTube/Instagram guidelines when posting automated content.  
  Adding background music layers or captions can further increase virality.  

  ⚡ Summary:  
  With this template you can create an AI-powered YouTube Shorts machine that runs on autopilot.  
  Just choose your niche, adjust the prompt, and let VEO3 + n8n handle video creation, uploading, and scaling — cheaper, faster, and smarter than traditional Google Video AI.


  Questions or custom requests?  
  📩 suliemansaid.business@gmail.com

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.youTube","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.outputParserStructured"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","content-creation","video-generation","social-media","ai"],"complexity":"medium","use_cases":["Automated YouTube Shorts channel (daily posting)","Mass-produce short-form cinematic AI videos for social platforms","Cross-posting shorts to Telegram/Instagram/TikTok","Rapidly test niches and scales of short-video content","Cost-effective alternative to Google Video AI for volume content"],"estimated_setup_minutes":45,"required_services":["n8n (workflow runner)","KIE AI VEO3 (veo3_fast) API key","Google Gemini (optional) for prompt generation / lmChatGoogleGemini node","YouTube Data API (OAuth2) credentials","Telegram Bot API (optional for channel posting)","Instagram Graph API (optional for Reels)"],"key_features":["Automated schedule trigger to publish at chosen intervals","AI prompt generator produces video prompt, title, description, and hashtags","VEO3-based 9:16 cinematic video generation (cost-efficient)","Automatic upload to YouTube Shorts with metadata and tags","Parallel posting to Telegram and easy extension to Instagram/TikTok','Prompt customization per niche for flexible content themes"],"target_audience":["Content creators and YouTube Shorts publishers","Social media managers and growth marketers","Indie creators and small studios looking for low-cost video generation workflows`,`Agencies and automation engineers building scaled short-video channels"]}


name: Automate AI Upwork Proposal Generation with Apify, Google Gemini & Sheets
author_name: Intuz
author_username: intuz
categories: []
created_at: 2025-08-29T07:27:56.439Z
updated_at: 2025-08-29T07:27:56.439Z
url: https://n8n.io/workflows/8015
scraped_at: 2025-09-29 22:37:33
metadata_generated_at: 2025-09-30 08:33:37
description:
  Disclaimer
  Community nodes are used, and template can only be used on self-hosted n8n instances.

  This n8n template from Intuz provides a complete and automated solution for finding relevant Upwork jobs and generating highly-personalized, knowledge-base-driven proposals using AI. 

  This workflow acts as an autonomous agent, handling everything from job discovery to drafting the final proposal text, ready for you to review and submit.

  Who's this workflow for?
  Freelancers & Consultants
  Digital Agencies
  Business Development Teams
  Sales Professionals

  How it works
  1. Scrape Upwork for New Jobs: The workflow starts by running an Apify actor to scrape Upwork based on your defined criteria (keywords, categories, payment verification, etc.).

  2. Log Jobs to Google Sheets: The newly found job opportunities are automatically saved as new rows in a Google Sheet, creating a central dashboard for tracking. A notification is sent confirming the new jobs found.

  3. Trigger AI Proposal Generation: The workflow then reads the new jobs from the sheet and, for each one that hasn't been applied for, triggers the AI.

  4. Craft a Knowledge-Based Proposal: It sends the job details to a Google Gemini AI model. The AI uses a detailed, built-in "Company Knowledge Base" (which you can customize) to write a comprehensive and relevant proposal. It addresses client questions, highlights relevant experience, and suggests a timeline.

  5. Save the Proposal Draft: The AI-generated proposal is saved back into the Google Sheet in the corresponding job row.

  6. Final Notification: A final email is sent to notify you that the proposals are ready, including a link to the sheet for final review and submission on Upwork.

  Setup Instructions
  1. Apify Configuration:
  In the Run Upwork Actor... node, connect your Apify account.
  We have used this apify scrapper- Upwork Extractor
  In the Custom Body field, customize the search parameters (like category, search.any keywords) to match the jobs you are looking for.

  2. Google Gemini AI Configuration:
  In the Google Gemini Chat Model node, connect your Google Gemini (PaLM) API account.
  Crucially: In the Proposal Crafting node, edit the prompt to replace the "Company Knowledge Base" with your own company's details, services, and project examples. This is essential for personalizing the proposals.

  3. Google Sheets Setup:
  Connect your Google Sheets account.
  In all three Google Sheets nodes, select your credentials and update the Document ID and Sheet Name to point to your Upwork tracking sheet.

  4. Gmail Configuration:
  In both Gmail nodes, connect your account and update the sendTo email address to your own.

  5. Execute the Workflow:
  Click "Execute workflow" to run the entire job scraping and proposal generation process.

  Key Requirements to Use This Template
  n8n Instance: An active n8n account (Cloud or self-hosted).
  Apify Account: An active Apify account with an API key and sufficient credits/subscription to run the "Upwork Extractor" actor.
  Google Account & Sheet: A pre-made Google Sheet with columns for Title, URL, Description, Skills, Questions, Applied, and Proposal Template.
  Google Gemini AI Account: A Google Cloud account with the Vertex AI API (for Gemini models) enabled and an associated API Key.
  Gmail Account: A Gmail account to send and receive notifications about the workflow's progress.

  Connect with us
  Website: https://www.intuz.com/services
  Email: getstarted@intuz.com
  LinkedIn: https://www.linkedin.com/company/intuz
  Get Started: https://n8n.partnerlinks.io/intuz

  For Custom Workflow Automation
  Click here- Get Started

nodes_used:
  ["n8n-nodes-base.manualTrigger","@apify/n8n-nodes-apify.apify","@apify/n8n-nodes-apify.apify","n8n-nodes-base.googleSheets","n8n-nodes-base.summarize","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.gmail","n8n-nodes-base.summarize","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","AI-powered content generation","web scraping/job discovery"],"complexity":"complex","use_cases":["Automated discovery of relevant Upwork jobs","Generating personalized, knowledge-base-driven proposals","Logging and tracking proposals in a spreadsheet","Semi-autonomous outreach workflow with human review"],"estimated_setup_minutes":60,"required_services":["n8n (self-hosted)","Apify (job scraping)","Google Gemini (LLM / Vertex AI)","Google Sheets (or compatible spreadsheet service)","Upwork (as the job source - accessed via Apify)"],"key_features":["Autonomous agent for job discovery and proposal drafting","AI-driven, knowledge-base-informed personalized proposals","Apify integration to scrape/monitor Upwork listings","Google Gemini LLM for proposal generation and summarization","Spreadsheet integration for logging/tracking applications and metadata"],"target_audience":["Freelancers and independent consultants","Digital agencies","Technical users running self-hosted n8n instances (admins/automation engineers)"]}


name: LeadChat Booker — conversational lead capture that schedules
author_name: Le Nguyen
author_username: leeseifer
categories: []
created_at: 2025-08-29T08:31:42.598Z
updated_at: 2025-08-29T08:31:42.598Z
url: https://n8n.io/workflows/8018
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:34
description:
  Real Working Demo

  https://crmaiinsight.com/leadbot
  How It Works (High-Level)

  1) Chat &gt; Capture  
     LeadBot greets, collects Full Name → Email → Mobile (optional) → Product interest via friendly chat (no forms).  
     Validates email/phone, confirms inputs, supports corrections.

  2) De-dupe  
     Checks Salesforce for an existing lead by Email.  
     If found → update_lead. If not → create_lead.

  3) Product Selection  
     Pulls your Feature_Product__c list (Name + one-line Description) and lets the user choose by number or name.

  4) Demo Booking (Optional)  
     If the user says Yes:  
     Detect/ask Time Zone (IANA).  
     Reads Salesforce Events for the next 14 days.  
     Computes free 30-min weekday slots (09:00–17:00 UTC) strictly after now.  
     User picks a slot → creates a Salesforce Event (30 min) linked to the Lead.

  5) Notifications & Follow-ups  
     Slack DM to your team (concise summary).  
     Email confirmation to the prospect (local date/time included).  
     Ends with a polite confirmation message.

  Setup at a Glance

  Effort:* Most teams finish the base setup in *~45–90 minutes** (credentials, field mapping, test).  
  What you’ll configure:** Salesforce OAuth, SMTP (or your ESP), Slack, OpenAI key, and the web chat widget.

  &gt; Tip: Start with the provided Feature_Product__c object. You can switch to your own product catalog with a few tweaks (see below).

  Prerequisites

  Salesforce**  
    Connected App + OAuth (API enabled).  
    Lead fields: FirstName, LastName, Email, MobilePhone, and one product lookup/text field (e.g., Interested_Product__c or Feature_Product__c).  
    (Recommended) Custom object Feature_Product__c with fields: Name, Description__c, Features__c, Tags__c.

  n8n Credentials**  
    salesforceOAuth2Api (to read/write Leads & Events).  
    smtp (or use your email provider node).  
    slackApi (for internal notifications).  
    openAiApi (for the chat agent).

  Widget Embed (optional)**  
    A place on your site/app to embed the chat launcher.

  Step-by-Step Setup

  1) Import the flow into n8n  
     Verify nodes: Chat Trigger → AI Agent → check_duplicate_lead → update/create lead → get_products → get_scheduled_events → create_demo_event → Slack/Email.

  2) Add/Bind Credentials
     Salesforce OAuth: authorize org with API scope.  
     SMTP: sender, domain, and authentication (verify SPF/DKIM).  
     Slack: ensure bot can DM users/channels.  
     OpenAI: drop in your API key.

  3) Map Product Field on Lead
     Pick one field to store the selection (e.g., Interested_Product__c).  
     Ensure AI Agent and Salesforce nodes reference the same field.

  4) (Option A) Use Feature_Product__c
     Confirm fields exist: Name, Description__c (used in the numbered list).  
     In get_products, make sure Id is returned; pass it as customFieldsValues0_Value.

  5) (Option B) Use Your Own Catalog
     Swap customObject: Feature_Product__c → Product2 (or your object).  
     Update fields to at least: Id, Name, and a short description field.  
     Keep the variable contract the same (AI expects to store Id, name, description).

  6) Configure Demo Booking
     get_scheduled_events uses a SOQL search window (today → +14 days).  
     Ensure your Event permissions allow read/write.  
     Confirm create_demo_event URL points to your Salesforce domain & API version.

  7) Customize Widget (optional)
     Set title, brand colors, and initial message in the Chat Trigger options.  
     Limit reply length (≤100 words) is already set.

  8) Test End-to-End
     Run a full path: enter name/email/phone, pick a product, select a time slot.  
     Verify: Lead/Update in Salesforce, Event creation, Slack DM, Prospect Email.

  Switching to Your Own Products (Quick Tweaks)

  Replace Data Source:**  
    In get_products:  
      customObject: Product2 (or your object API name).  
      Fields: ensure Id, Name, and a short description are returned.  
  Update Lead Field Mapping:**  
    Set Interested_Product__c (or your chosen field) to the returned Product Id.  
  Copy Text Logic:**  
    Keep the AI’s “numbered list” output; it supports both number and name replies.

  What Users Experience

  No forms. A friendly AI asks one thing at a time, confirms details, and offers a live calendar of the next available 30-minute demo slots.  
  The moment they choose, a Salesforce Event is created and they get a confirmation email.  
  Your team receives a Slack heads-up with who/what/when.

  Troubleshooting Quick Checks

  No product list?* Ensure Id, Name, Description__c (or equivalent) are returned by *get_products**.  
  No free slots shown?** Confirm Event query window (+14 days), timezone handling, and that “current time” filter excludes past times.  
  Lead not updated?* Check the *duplicate search by Email** and that update_lead receives Lead_ID.  
  Event fails to create?** Verify Salesforce API endpoint, OAuth scope, and required Event fields.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.salesforceTool","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.salesforceTool","n8n-nodes-base.salesforceTool","n8n-nodes-base.emailSendTool","n8n-nodes-base.slackTool","n8n-nodes-base.salesforceTool","n8n-nodes-base.salesforceTool","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["lead generation","conversational interface","CRM integration","scheduling","notifications/alerts','automation"],"complexity":"complex","use_cases":["Conversational lead capture (no forms)","Qualifying leads and storing/updating in Salesforce","Interactive product selection from a catalog","Booking demo appointments and creating calendar events in Salesforce","Notifying team via Slack and emailing confirmations"],"estimated_setup_minutes":60,"required_services":["Salesforce (OAuth/API access)","SMTP or email provider (ESP)","Slack (bot/API)","OpenAI API (chat agent)","Web hosting or embed location for chat widget"],"key_features":["AI-driven chat that collects and validates name/email/phone","De-duplication: search and update or create Salesforce Lead","Pull product list (Feature_Product__c or custom object) and accept selection by number or name","Compute available 30-min weekday demo slots (next 14 days) and create Salesforce Event","Timezone detection/handling (IANA) and local-time confirmation in emails/messages','Slack DM notification to team and prospect email confirmation"],"target_audience":["Sales teams / SDRs","Revenue Ops / CRM admins","Marketing teams running demos/lead capture campaigns','Developers implementing chat-to-CRM workflows"]}


name: Auto-Generate Virtual AI Try-On Images for WooCommerce with Gemini Nano Banana
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-08-29T10:05:54.420Z
updated_at: 2025-08-29T10:05:54.420Z
url: https://n8n.io/workflows/8022
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow automates the creation of AI-generated virtual try-on images for fashion eCommerce stores. Instead of relying on expensive and time-consuming photoshoots, the system uses AI to generate realistic images of models wearing selected clothing items.

  This n8n workflow automates the process of generating AI-powered virtual try-on images for a WooCommerce store. It fetches product data from a Google Sheet, uses the Fal.ai Nano Banana model to create an image of a model wearing the clothing item, and then updates both the Google Sheet and the WooCommerce product with the final generated image.

  Advantages

  ✅ Cost Reduction: Eliminates the need for professional photo shoots, saving on models, photographers, and studio expenses.
  ✅ Time Efficiency: Automates the entire workflow—from data input to product update—minimizing manual work.
  ✅ Scalability: Works seamlessly across large product catalogs, making it easy to update hundreds of products quickly.
  ✅ Enhanced eCommerce Experience: Provides shoppers with realistic previews of clothing on models, boosting trust and conversion rates.
  ✅ Marketing Flexibility: The generated images can also be repurposed for ads, social media, and promotional campaigns.
  ✅ Centralized Management: Google Sheets acts as the control center, making it easy to manage inputs and track results.

  How It Works

  The workflow operates in a sequential, loop-based manner to process multiple products from a spreadsheet. Here is the logical flow:

  Manual Trigger & Data Fetch: The workflow starts manually (e.g., by clicking "Test workflow"). It first reads data from a specified Google Sheet, looking for rows where the "IMAGE RESULT" column is empty.

  Loop Processing: It loops over each row of data fetched from the sheet. Each row should contain URLs for a model image and a product image, along with a WooCommerce product ID.

  API Request to Generate Image: For each item in the loop, the workflow sends a POST request to the Fal.ai Nano Banana API. The request includes the two image URLs and a prompt instructing the AI to create a photo of the model wearing the submitted clothing item.

  Polling for Completion: The AI processing is asynchronous. The workflow enters a polling loop: it waits for 60 seconds and then checks the status of the processing request. If the status is not COMPLETED, it waits and checks again. This loop continues until the image is ready.

  Fetching and Storing the Result: Once the status is COMPLETED, the workflow retrieves the URL of the generated image, downloads the image file, and uploads it to a designated folder in Google Drive.

  Updating Systems: The workflow then performs two crucial update steps:
      It updates the original Google Sheet row, writing the URL of the final generated image into the "IMAGE RESULT" column.
      It updates the corresponding product in WooCommerce, adding the generated image to the product's gallery.

  Loop Continuation: After processing one item, the workflow loops back to process the next row in the Google Sheet until all items are complete.

  * Set Up Steps*

  To make this workflow functional, you need to configure three main connections:

  Step 1: Prepare the Google Sheet
  Create a Google Sheet with the following columns: IMAGE MODEL, IMAGE PRODUCT, PRODUCT ID, and IMAGE RESULT.
  Populate the first three columns for each product. The IMAGE RESULT column must be left blank; the workflow will fill it automatically.
  In the n8n workflow, configure the "Google Sheets" node to point to your specific Google Sheet and worksheet.

  Step 2: Configure the Fal.ai API Key
  Create an account at fal.ai and obtain your API key.
  In the n8n workflow, locate the three "HTTP Request" nodes named "Get Url image", "Get status", and "Create Image".
  Edit the credentials for these nodes (named "Fal.run API") and update the Value field in the Header Auth to be Key YOURAPIKEY (replacing YOURAPIKEY with your actual key).

  Step 3: Set Up WooCommerce API
  Ensure you have the API keys (Consumer Key and Consumer Secret) for your WooCommerce store's REST API.
  In the n8n workflow, locate the "WooCommerce" node.
  Edit its credentials and provide the required information: your store's URL and the API keys. This allows the workflow to authenticate and update your products.

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wooCommerce","n8n-nodes-base.googleSheets","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5148 characters]

metadata_json:
  {"categories":["automation","eCommerce","AI-powered image generation","integrations"],"complexity":"complex","use_cases":["Generate virtual try-on images for clothing products","Automate eCommerce product image updates","Scale product photography without photoshoots","Create marketing assets (ads, social, promos)","Centralized product image management via Google Sheets"],"estimated_setup_minutes":30,"required_services":["n8n","Google Sheets","Google Drive","Fal.ai (Nano Banana / Fal.run API)","WooCommerce REST API"],"key_features":["Reads product rows from Google Sheets and filters unprocessed items","Calls Fal.ai Nano Banana model to generate model-wearing-product images","Asynchronous polling for AI job completion","Downloads generated images and uploads to Google Drive","Writes result URL back to Google Sheet and updates WooCommerce product gallery\",\"Loop-based batch processing for large catalogs"],"target_audience":["eCommerce store owners","Fashion retailers and brands","Marketing teams and agencies producing visual assets for ads/social media\",\"Developers or automation engineers building storefront integrations"]}


name: Automate HS Code Lookup & Enrichment with Google Sheets and Customs API (beta)
author_name: Thomas
author_username: thomas-z
categories: []
created_at: 2025-08-29T16:38:21.850Z
updated_at: 2025-08-29T16:38:21.850Z
url: https://n8n.io/workflows/8034
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  "I used to spend hours every week just copy-pasting product descriptions to find the right tariff codes for our international shipments. It was tedious and prone to errors." - Accounting specialist.


  This workflow eliminates that manual work entirely. It automatically finds customs tariff numbers (also known as HS Codes or "Zolltarifnummern") for your products and enriches your data in Google Sheets. It offers two powerful modes: bulk processing for entire product lists and an on-demand chat interface for quick single lookups.

  new features
  added the API score in percentage (80 to 100% is perfect, 70-80% still good)
  added description of the found HS Code to better verify the accuracy
  -please keep in mind, that is still a beta
  https://www.zolltarifnummern.de/services/api 

  What this workflow does
  Bulk Enrichment from Google Sheets:** Reads a list of product descriptions from a specified Google Sheet.
  External API Lookup:** For each product, it queries the zolltarifnummern.de API to find the most relevant customs tariff number.
  Automated Data Update:** Writes the found tariff numbers back into the correct row in your Google Sheet.
  On-Demand Single Lookup:** Use the integrated Chat Trigger to instantly look up a tariff number for a single product description without leaving n8n.
  Completion Notification:** Sends a confirmation email via Gmail once the bulk processing job is finished.

  Nodes Used
  Google Sheets
  HTTP Request
  Loop Over Items (Split in Batches)
  Set
  Gmail
  Chat Trigger
  Manual Trigger

  Preparation
  A Google Sheet prepared with at least two columns: one for your product descriptions (e.g., ProductDescription) and an empty one for the results (e.g., TariffCode).
  How to set up this workflow
  Configure Google Sheets (Read):

  Open the "Read Item Descriptions" node.
  Select your Google Sheets credentials.
  Enter your Spreadsheet ID and the name of the sheet containing your product data.
  Make sure the "Columns to Read" field includes the name of your product description column.
  Configure Google Sheets (Update):

  Open the "Write Customs Tariff to Sheet"  node.
  Select the same Google Sheets credentials.
  Enter the same Spreadsheet ID and Sheet Name.
  Under Columns, set Matching Columns to your product description column name. This is crucial for updating the correct rows.
  Configure Email Notification:

  Open the "Send Completion Email" (Gmail) node.
  Select your Gmail credentials.
  In the Send To field, enter the email address where you want to receive the completion notification.

  Run the Workflow:

  For Bulk Processing: Activate the workflow and execute the "Abfrage starten" (Start Query) Manual Trigger.
  For a Single Lookup: Use the Chat Trigger. Open the chat pane, type a product description, and hit send. The workflow will return the suggested tariff number.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.gmail","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.set"]

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metadata_json:
  {"categories":["automation","integration","data enrichment","logistics & compliance"],"complexity":"medium","use_cases":["Bulk enrichment of product lists with HS/Customs tariff (Zolltarif) codes","On-demand single-product HS code lookup via chat interface","Automating updates to Google Sheets with verified tariff numbers","Reducing manual copy-paste and human error in customs classification","Notifying stakeholders when batch jobs complete"],"estimated_setup_minutes":20,"required_services":["Google Sheets (Google account & credentials)","zolltarifnummern.de Customs API (API key/access)","Gmail (for completion notifications)","n8n (workflow runner with Chat Trigger enabled)"],"key_features":["Bulk processing from Google Sheets with batching","HTTP API lookup against zolltarifnummern.de for HS codes","Writes found tariff numbers and descriptions back to the original sheet","On-demand single lookup via integrated Chat Trigger","Includes API confidence score (percentage) and HS description for verification (beta feature)"],"target_audience":["Accounting specialists","Import/Export and customs compliance teams","Logistics and supply chain operators\nE‑commerce operations teams (product managers, merchandisers, catalog managers)"]}


name: Version Control n8n Workflows in GitLab with Customer Tag Organization
author_name: Omar Kennouche
author_username: kennouche-omar
categories: []
created_at: 2025-08-29T20:58:27.777Z
updated_at: 2025-08-29T20:58:27.777Z
url: https://n8n.io/workflows/8042
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  How it works
  Triggers manually or on schedule (03:00 daily by default)  
  Fetches workflows tagged backup-workflows via n8n API  
  Normalizes workflow names and applies [client: NAME] tag convention  
  Prepares JSON in the same structure as an n8n UI export  
  Checks GitLab repository:  
    Create new file if missing  
    Update file if content differs  
    Skip if unchanged  
  Logs results with recap (created, updated, unchanged, total)  

  Set up steps
  Configure your GitLab credentials in n8n  
  Create a repository and branch for workflow backups  
  Set global variables (owner, project, branch, backup path)  
  Tag workflows to include with backup-workflows  
  Run manually once to test, then enable the schedule  

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.n8n","n8n-nodes-base.gitlab","n8n-nodes-base.gitlab","n8n-nodes-base.gitlab","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.merge"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","backup","devops"],"complexity":"medium","use_cases":["Version-controlling n8n workflows","Automated backups of workflows per customer","Organizing workflows by customer tag convention","Auditing and change tracking of workflows in GitLab","Synchronizing n8n UI export JSON to repository"],"estimated_setup_minutes":20,"required_services":["n8n (API access)","GitLab (repository and API credentials)"],"key_features":["Scheduled or manual trigger (default daily)","Fetch workflows by tag (backup-workflows)","Normalize names and apply [client: NAME] tag convention","Prepare JSON in n8n UI export structure","Create/update/skip files in GitLab based on diffing content (idempotent)」「Logs recap showing created, updated, unchanged, total"],"target_audience":["n8n administrators","DevOps engineers","Developers managing automation workflows」「SaaS consultants and integrators"]}


name: Personalized Evening Wind-Down System with Mood Tracking via Telegram, Notion & Email
author_name: Shelly-Ann Davy
author_username: SheCodesFlow
categories: []
created_at: 2025-08-30T16:30:27.279Z
updated_at: 2025-08-30T16:30:27.279Z
url: https://n8n.io/workflows/8067
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  🌸 The Quiet Evening Ritual — Wind-Down Automation (Telegram + Notion + Email)

  Create a calming 9PM evening routine that runs itself. This n8n template checks in via Telegram with mood buttons, delivers personalized support (meditation when you’re tired, celebration when you’re thriving), logs reflections to a Notion “Evening Reflection Log,” and sends a gentle goodnight email with tomorrow’s affirmation.

  Who it’s for

  Homemakers, moms, and creators who feel “always on” and want a graceful, one-tap transition into rest.

  What it does

  9:00 PM Telegram mood check (I’m Tired 💤 / Felt Great ✨)

  Personalized content (5-min meditation or celebration prompt)

  Automatic Notion journaling (mood, reflection, wins, date, affirmation)

  Goodnight email with a fresh morning affirmation

  Optional: GPT-4o mini for gentle reflection prompts

  Why it’s different

  Not just logging—this is a ritualized, emotionally intelligent handoff from work to rest that protects your peace and builds consistency.

  Stack & Nodes

  Cron → Telegram → IF → Notion → Email (+ optional GPT)

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.cron","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.openAi","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.notion","n8n-nodes-base.emailSend","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.notion","n8n-nodes-base.emailSend"]

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metadata_json:
  {"categories":["automation","wellbeing","notifications","journaling","integration"],"complexity":"medium","use_cases":["Evening routine automation","Mood tracking and check-ins","Automated journaling in Notion","Sending nightly emails with morning affirmations","Delivering context-aware content (meditation or celebration prompts)"],"estimated_setup_minutes":30,"required_services":["n8n","Telegram (bot)","Notion","Email provider (SMTP / Gmail / SendGrid)","OpenAI (optional for GPT-4o mini prompts)"],"key_features":["Scheduled 9:00 PM Telegram mood check with quick-reply buttons","Conditional flow to deliver meditation or celebration prompts","Automatic logging of mood, reflections, wins, date, and affirmation to Notion","Goodnight email with a fresh morning affirmation","Optional GPT-4o mini for personalized reflection prompts"],"target_audience":["homemakers","moms","creators and solopreneurs seeking ritualized downtime"]}


name: Find Valid Vouchers and Promo Codes with SerpAPI, Decodo, and GPT-5 Mini
author_name: Khaisa Studio
author_username: khaisastudio
categories: []
created_at: 2025-08-31T07:30:33.648Z
updated_at: 2025-08-31T07:30:33.648Z
url: https://n8n.io/workflows/8075
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:34
description:
  Promo Seeker finds fresh, working promo codes and vouchers on the web so your team never misses a deal. 

  This n8n workflow uses SerpAPI and Decodo Scrapper for real-time search, an agent powered by GPT-5 Mini for filtering and validation, and Chat Memory to keep context—saving time, reducing manual checks, and helping marketing or customer support teams deliver discounts faster to customers (and yes, it's better at hunting promos than your inbox).

  💡 Why Use Promo Seeker?

  Speed: Saves hours per week by automatically finding and validating current promo codes, so you can publish deals faster.  
  Simplicity: Eliminates manual searching across sites, no more copy-paste scavenger hunts.  
  Accuracy: Reduces false positives by cross-checking results and keeping only working vouchers—fewer embarrassed "expired code" moments.  
  Edge: Combine search APIs with an AI agent to surface hard-to-find, recently-live offers—win over competitors who still rely on manual scraping.

  ⚡ Perfect For

  Marketing teams: Quickly populate newsletters, landing pages, or ads with valid promos.  
  Customer support: Give verified discount codes to users without ping-ponging between tabs.  
  Deal aggregators & affiliates: Discover fresh vouchers faster and boost conversion rates.

  🔧 How It Works

  ⏱ Trigger: A user message via the chat webhook starts the search (Message node).  
  📎 Process: The agent queries SerpAPI and Decodo Scrapper to collect potential promo codes and voucher pages.  
  🤖 Smart Logic: The Promo Seeker Agent uses GPT-5 Mini with Chat Memory to filter for fresh, working promos and to verify validity and relevance.  
  💌 Output: Results are returned to the chat with clear, copy-ready promo codes and source links.  
  🗂 Storage: Chat Memory stores context and recent searches so the agent avoids repeating old results and can follow up with improved queries.

  🔐 Quick Setup

  Import JSON file to your n8n instances  
  Add credentials: SerpAPI, Azure OpenAI (Gpt 5 Mini), Decodo API  
  Customize: Search parameters (brands, regions, validity window), agent system message, and result formatting  
  Update: Azure OpenAI endpoint and API key in the Gpt 5 Mini credentials; add your SerpAPI key and Decodo key  
  Test: Run a few queries like "latest Amazon promo" or "food delivery voucher" and confirm returned codes are valid

  🧩 You'll Need

  Active n8n instances  
  SerpAPI account and API key  
  Azure OpenAI (for GPT-5 Mini) with key and endpoint  
  Decodo account/API key  

  🛠️ Level Up Ideas

  Push verified promos to a Slack channel or email digest for the team.  
  Add scheduled scans to detect newly expired codes and remove them from lists.  
  Integrate with a CMS to auto-post verified deals to landing pages.

  Made by: khaisa Studio  
  Tags: promo, vouchers, discounts  
  Category: Marketing Automation  
  Need custom work? Contact Us

nodes_used:
  ["@n8n/n8n-nodes-langchain.toolSerpApi","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@decodo/n8n-nodes-decodo.decodoTool"]

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metadata_json:
  {"categories":["Marketing Automation","Web Scraping / Data Extraction","AI-powered Workflows","Integrations"],"complexity":"medium","use_cases":["Automatically discover and validate promo codes and vouchers","Populate newsletters, landing pages, or marketing copy with verified discounts","Provide verified discount codes to customer support agents","Power deal aggregator sites or affiliate offers with fresh promos","Send verified promos to Slack/email digests or auto-post to a CMS"],"estimated_setup_minutes":20,"required_services":["n8n instance","SerpAPI (API key)","Decodo Scrapper (Decodo API key)","Azure OpenAI (GPT-5 Mini endpoint and key)"],"key_features":["Real-time web search via SerpAPI and Decodo Scrapper","AI agent (GPT-5 Mini) filters and validates promo codes","Chat Memory to keep context and avoid duplicate results","Returns copy-ready promo codes with source links","Customizable search parameters (brands, regions, validity window)"],"target_audience":["Marketing teams","Customer support teams","Deal aggregators and affiliates/operators of coupon sites/landing pages"]}


name: Generate Student Course Schedules Based on Prerequisites with GPT and Google Sheets
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-31T20:28:14.026Z
updated_at: 2025-08-31T20:28:14.026Z
url: https://n8n.io/workflows/8090
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Create a Fall 2025 course schedule for each student based on what they’ve already completed, catalog prerequisites, and term availability (Fall/Both). Reads students from Google Sheets → asks an AI agent to select exactly 5 courses (target 15–17 credits, no duplicates, prereqs enforced) → appends each student’s schedule to a schedule tab.

  🧠 Summary
  Trigger:* Manual — *“When clicking ‘Execute workflow’”
  I/O:** Google Sheets in → OpenAI decisioning → Google Sheets out
  Ideal for:** Registrars, advisors, degree-planning prototypes

  ✅ What this template does
  Reads: StudentID, Name, Program, Year, CompletedCourses (pipe-separated CourseIDs) from **Sheet1  
  Decides: AI **Scheduling Agent chooses 5 courses per student following catalog rules and prerequisites  
  Writes: Appends StudentID + Schedule strings to **schedule worksheet  
  Credits target**: 15–17 total per term  
  Catalog rules** (enforced in the agent prompt):
    Use Fall or Both courses for Fall 2025
    Enforce AND prereqs (e.g., CS-102|CS-103 means both)
    Priority: Major Core → Major Elective → Gen Ed (include Gen Ed if needed)
    No duplicates or already-completed courses
    Prefer 200-level progression when prereqs allow

  ⚙️ Setup (only 2 steps)

  1) Connect Google Sheets (OAuth2)
  In n8n → Credentials → New → Google Sheets (OAuth2), sign in and grant access  
  In the Google Sheets nodes, select your spreadsheet and these tabs:
    Sheet1 (input students)
    schedule (output)

  &gt; Example spreadsheet (replace with your own):  
  &gt; - Input: .../edit#gid=0  
  &gt; - Output: .../edit#gid=572766543

  2) Connect OpenAI (API Key)
  In n8n → Credentials → New → OpenAI API, paste your key  
  In the OpenAI Chat Model node, select that credential and a chat model (e.g., gpt-4o)

  📥 Required input (Sheet1)
  Columns**: StudentID, Name, Program, Year, CompletedCourses  
  CompletedCourses**: pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101)  
  Program* names should match those referenced in the embedded catalog (e.g., *Computer Science BS, Business Administration BBA, etc.)

  📤 Output (schedule tab)
  Columns**:
    StudentID
    Schedule → a selected course string (written one row per course after splitting)

  🧩 Nodes in this template
  Manual Trigger* → *Get Student Data (Google Sheets)* → *Scheduling Agent (OpenAI)**  
    → Split Schedule → Set Fields → Clear sheet → Append Schedule (Google Sheets)

  🛠 Configuration tips
  If you rename tabs, update both Get Student Data and Append Schedule nodes  
  Keep CompletedCourses consistent (use | as the delimiter)  
  To store rationale as well, add a column to the output and map it from the agent’s JSON

  🧪 Test quickly
  1) Add 2–3 sample student rows with realistic CompletedCourses  
  2) Run the workflow and verify:
     5 course rows per student in schedule
     Course IDs respect prereqs & Fall/Both availability
     Credits sum ~15–17

  🧯 Troubleshooting
  Sheets OAuth error:** Reconnect “Google Sheets (OAuth2)” and re-select the spreadsheet & tabs  
  Empty schedules:** Ensure CompletedCourses uses | and that programs/courses align with the provided catalog names  
  Prereq violations:** Check that students actually have all AND-prereqs in CompletedCourses  
  OpenAI errors (401/429):** Verify API key, billing, and rate-limit → retry with lower concurrency

  🔒 Privacy & data handling
  Student rows are sent to OpenAI for decisioning. Remove or mask any fields you don’t want shared.  
  Google Sheets retains input/output. Use spreadsheet sharing controls to limit access.

  💸 Cost & performance
  OpenAI**: Billed per token; cost scales with student count and prompt size  
  Google Sheets**: Free within normal usage limits  
  Runtime**: Typically seconds to a minute depending on rows and rate limits

  🧱 Limitations & assumptions
  Works for Fall 2025 only (as written). For Spring, update availability rules in the agent prompt  
  Assumes catalog in the agent system message is your source of truth  
  Assumes Program names match catalog variants (case/spacing matter for clarity)

  🧩 Customization ideas
  Add a Max Credits column to cap term credits per student  
  Include Rationale in the sheet for advisor review  
  Add a “Gen Ed needed?” flag per student to force at least one Gen Ed selection  
  Export to PDF or email the schedules to advisors/students

  🧾 Version & maintenance
  n8n version:** Tested on recent n8n Cloud builds (2025)  
  Community nodes:** Not required  
  Maintenance:** Update the embedded catalog and offerings each term; keep prerequisites accurate

  🗂 Tags & category
  Category:** Education / Student Information Systems  
  Tags:** scheduling, registrar, google-sheets, openai, prerequisites, degree-planning, catalog, fall-term

  🗒 Changelog
  v1.0.0** — Initial release: Sheets in/out, Fall 2025 catalog rules, prereq enforcement, 5-course selection, credits target

  📬 Contact
  Need help customizing this (e.g., cohort logic, program-specific rules, adding rationale to the sheet, or emailing PDFs)?

  📧 rbreen@ynteractive.com  
  🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/  
  🌐 ynteractive.com — https://ynteractive.com

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.splitOut","n8n-nodes-base.googleSheets"]

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metadata_json:
  {"categories":["education","automation","integration","decisioning","data processing"],"complexity":"medium","use_cases":["Generate term course schedules for students","Degree planning prototypes and simulations","Batch advising support for registrars/advisors","Enforce catalog prerequisites and term availability","Export schedules to Google Sheets for downstream workflows"],"estimated_setup_minutes":15,"required_services":["n8n (workflow runtime)","Google Sheets (OAuth2)","OpenAI API (chat model, e.g., gpt-4o)"],"key_features":["Reads student rows from Google Sheets and writes schedules back","AI scheduling agent selects exactly 5 courses per student","Enforces AND prerequisites and Fall/Both availability","Targets 15–17 credits per term and avoids duplicates/already completed courses","Priority ordering (Major Core → Major Elective → Gen Ed) and 200-level preference when possible"],"target_audience":["Registrars","Academic advisors","Academic IT / SIS integrators"]}


name: AI-Powered Degree Audit System with Google Sheets and GPT-5
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-31T20:38:34.540Z
updated_at: 2025-08-31T20:38:34.540Z
url: https://n8n.io/workflows/8093
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Run an AI-powered degree audit for each senior student. This template reads student rows from Google Sheets, evaluates completed courses against hard-coded program requirements, and writes back an AI Degree Summary of what's still missing (major core, Gen Eds, major electives, and upper-division credits). It's designed for quick advisor/registrar review and SIS prototypes.

  Trigger: Manual — When clicking "Execute workflow"  
  Core nodes: Google Sheets, OpenAI Chat Model, (optional) Structured Output Parser  
  Programs included: Computer Science BS, Business Administration BBA, Psychology BA, Mechanical Engineering BS, Biology BS (Pre-Med), English Literature BA, Data Science BS, Nursing BSN, Economics BA, Graphic Design BFA

  Who's it for
  Registrars & advisors** who need fast, consistent degree checks  
  Student success teams** building prototype dashboards  
  SIS/EdTech builders** exploring AI-assisted auditing

  How it works
  Read seniors from Google Sheets (Senior_data) with: StudentID, Name, Program, Year, CompletedCourses.  
  AI Agent compares CompletedCourses to built-in requirements (per program) and computes Missing items + a short Summary.  
  Write back to the same sheet using "Append or update" by StudentID (updates AI Degree Summary; you can also map the raw Missing array to a column if desired).

  Example JSON (for one student):
  {
   "StudentID": "S001",
   "Program": "Computer Science BS",
   "Missing": [
     "GEN-REMAIN | General Education credits remaining | 6",
     "CS-EL-REM | CS Major Electives (200+ level) | 6",
     "UPPER-DIV | Additional Upper-Division (200+ level) credits needed | 18",
     "FREE-EL | Free Electives to reach 120 total credits | 54"
   ],
   "Summary": "All core CS courses are complete. Still need 6 Gen Ed credits, 6 CS electives, and 66 total credits overall, including 18 upper-division credits — prioritize 200/300-level CS electives."
  }

  Setup (2 steps)

  1) Connect Google Sheets (OAuth2)
  In n8n → Credentials → New → Google Sheets (OAuth2) and sign in.

  In the Google Sheets nodes, select your spreadsheet and the Senior_data tab.

  Ensure your input sheet has at least: StudentID, Name, Program, Year, CompletedCourses.

  2) Connect OpenAI (API Key)
  In n8n → Credentials → New → OpenAI API, paste your key.

  In the OpenAI Chat Model node, select that credential and a model (e.g., gpt-4o or gpt-5).

  Requirements
  Sheet columns:** StudentID, Name, Program, Year, CompletedCourses
  CompletedCourses format:** pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101).
  Program labels:** should match the built-in list (e.g., Computer Science BS).
  Credits/levels:** Template assumes upper-division ≥ 200-level (adjust the prompt if your policy differs).

  Customization
  Change requirements:** Edit the Agent's system message to update totals, core lists, elective credit rules, or level thresholds.
  Store more output:** Map Missing to a new column (e.g., AI Missing List) or write rows to a separate sheet for dashboards.
  Distribute results:** Email summaries to advisors/students (Gmail/Outlook), or generate PDFs for advising folders.
  Add guardrails:** Extend the prompt to enforce residency, capstone, minor/cognate constraints, or per-college Gen Ed variations.

  Best practices (per n8n guidelines)
  Sticky notes are mandatory:** Include a yellow sticky note that contains this description and quick setup steps; add neutral sticky notes for per-step tips.
  Rename nodes clearly:** e.g., "Get Seniors," "Degree Audit Agent," "Update Summary."
  No hardcoded secrets:** Use credentials—not inline keys in HTTP or Code nodes.
  Sanitize identifiers:** Don't ship personal spreadsheet IDs or private links in the published version.
  Use a Set node for config:** Centralize user-tunable values (e.g., column names, tab names).

  Troubleshooting
  OpenAI 401/429:** Verify API key/billing; slow concurrency if rate-limited.
  Empty summaries:** Check column names and that CompletedCourses uses |.
  Program mismatch:** Align Program labels to those in the prompt (exact naming recommended).
  Sheets auth errors:** Reconnect Google Sheets OAuth2 and re-select spreadsheet/tab.

  Limitations
  Not an official audit:** It infers gaps from the listed completions; registrar rules can be more nuanced.
  Catalog drift:** Requirements are hard-coded in the prompt—update them each term/year.
  Upper-division heuristic:** Adjust the level threshold if your institution defines it differently.

  Tags & category
  Category: Education / Student Information Systems  
  Tags: degree-audit, registrar, google-sheets, openai, electives, upper-division, graduation-readiness

  Changelog
  v1.0.0 — Initial release: Senior_data in/out, 10 programs, AI Degree Summary output, append/update by StudentID.

  Contact
  Need help tailoring this to your catalog (e.g., per-college Gen Eds, capstones, minors, PDFs/email)?

  📧 rbreen@ynteractive.com  
  📧 robert@ynteractive.com  
  🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/  
  🌐 ynteractive.com — https://ynteractive.com

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

workflow_json_compressed:
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metadata_json:
  {"categories":["education","student-information-systems","integration","automation","data-processing"],"complexity":"medium","use_cases":["Quick degree audit checks for senior students","Prototyping SIS/Registrar workflows","Populating advisor dashboards with audit results","Generating advisor/student summaries for review","Building AI-assisted graduation-readiness tools"],"estimated_setup_minutes":15,"required_services":["Google Sheets (OAuth2)","OpenAI API (gpt-5 / gpt-4o or similar)","n8n instance (workflow runner)"],"key_features":["Reads student rows from Google Sheets and identifies seniors","Compares CompletedCourses to built-in program requirements","Generates structured Missing items array and an AI Degree Summary","Writes/updates results back to the sheet by StudentID (append or update)","Supports Structured Output Parser for reliable JSON output (optional)"],"target_audience":["Registrars & academic advisors","Student success teams","SIS and EdTech builders/prototypers"]}


name: Email new leads from Google Sheets via Outlook on a schedule
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-31T21:09:22.082Z
updated_at: 2025-08-31T21:09:22.082Z
url: https://n8n.io/workflows/8095
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Send a templated outreach email to new leads in a Google Sheet on a daily schedule, then mark each lead as contacted so they won’t be emailed twice. Built with: Schedule Trigger → Google Sheets → Filter → Outlook Send Email → Google Sheets (append/update).

  Who’s it for
  Teams that collect leads in Sheets and want automatic, once-per-lead outreach  
  Solo founders/consultants running simple top-of-funnel follow-ups  
  Anyone prototyping CRM-lite flows in n8n

  How it works / What it does
  Schedule Trigger runs daily (e.g., 09:00).
  Get rows (Google Sheets) pulls leads from your sheet.
  Filter keeps only rows where Contacted is empty.
  Outlook – Send a message emails each remaining lead (to = {{$json.Email}}).
  Google Sheets (appendOrUpdate) writes back Contacted = Yes (match on Email) to prevent re-sending.

  How to set up
  1) Google Sheets (OAuth2)
  In n8n → Credentials → New → Google Sheets (OAuth2), sign in and grant access.  
  In Get rows: select your Lead Source sheet (e.g., “New Leads”).  
  In Append/Update: select the sheet you want to mark as contacted (can be the same sheet or a CRM sheet).  
  Make sure your sheet has at least: Email, Contacted (blank for new).

  2) Outlook (Microsoft Graph) OAuth2
  n8n Cloud (quick connect):**  
    In Credentials → New → Microsoft Outlook OAuth2, choose Connect, sign in with your Microsoft account, and accept permissions.
  Self-hosted (Azure App Registration):**  
    1) Azure Portal → App registrations → New registration.  
    2) Add redirect URL: https://YOUR_N8N_URL/rest/oauth2-credential/callback.  
    3) API permissions (Delegated): offline_access, Mail.Send, User.Read. Grant admin consent if required.  
    4) Create a Client secret; copy Application (client) ID and Directory (tenant) ID.  
    5) In n8n, create Microsoft Outlook OAuth2 credential with those values and scopes: offline_access Mail.Send openid email profile.  
  In the Send a message node, select that credential and keep To mapped to {{$json.Email}}.  
  Customize Subject and Body to your brand (default provided).

  Requirements
  A Google Sheet of leads with an Email column (and an optional Contacted column).  
  A Microsoft account with permission to send mail via Microsoft Graph (Outlook).

  How to customize the workflow
  Email content:** Edit subject/body (add variables like {{$json.FirstName}}).  
  Send window:** Change Schedule Trigger time/interval.  
  Idempotency:** Use the same sheet for read+write (match on Email) or separate source/CRM sheets.  
  Logging:** Add a Sheet or Notion append step after send for an audit trail.

  Security & best practices
  No hardcoded secrets:* Always use *OAuth2 credentials** (Sheets & Outlook).  
  Sanitize PII:* If publishing, *remove real spreadsheet IDs/URLs** and personal emails/phone numbers.  
  Sticky notes are mandatory:* Add a *yellow sticky note** in the workflow with this description and a short setup checklist. Use neutral sticky notes for per-node tips.

  Troubleshooting
  No emails sent:** Ensure Contacted is blank for new rows and the Filter checks “is empty.”  
  Auth errors (Outlook):** Reconnect credential; confirm Graph scopes and tenant consent.  
  Sheets errors:** Re-select spreadsheet/tab; verify headers (Email, Contacted).  
  Duplicates:* Confirm *Append/Update* uses *matching column = Email**.

  Tags & category
  Category: Sales & CRM  
  Tags: outreach, follow-up, google-sheets, outlook, schedule, dedupe, cold-email

  Changelog
  v1.0.0 — Initial release: scheduled outreach, Outlook email, de-dupe via Contacted = Yes.

  Contact
  Need help customizing (personalization, rate-limits, CRM sync, bounce checks)?

  📧 rbreen@ynteractive.com  
  🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/  
  🌐 ynteractive.com — https://ynteractive.com

nodes_used:
  ["n8n-nodes-base.microsoftOutlook","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.filter","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","sales & crm"],"complexity":"simple","use_cases":["Automated outreach to new leads","One-time-per-lead follow-ups","Prototyping a lightweight CRM flow","Daily scheduled lead engagement","Preventing duplicate emails via sheet-based dedupe"],"estimated_setup_minutes":20,"required_services":["n8n (Cloud or self-hosted)","Google Sheets (OAuth2)","Microsoft Outlook / Microsoft Graph (OAuth2)","Azure App Registration (optional — for self-hosted Outlook OAuth)"],"key_features":["Daily Schedule Trigger to run outreach","Get rows from Google Sheets to pull leads","Filter to select only rows where Contacted is empty","Outlook – Send a message node to send templated emails (To = {{$json.Email}})","Google Sheets appendOrUpdate to mark Contacted = Yes (idempotency)"],"target_audience":["Sales & CRM teams using Sheets for lead capture","Solo founders and consultants handling outreach","Product builders prototyping CRM-lite automations in n8n"]}


name: Analyze Google Business Reviews & Send Sentiment Reports to Slack with Gemini
author_name: Sayone Technologies
author_username: sayonetech
categories: []
created_at: 2025-09-01T08:17:37.468Z
updated_at: 2025-09-01T08:17:37.468Z
url: https://n8n.io/workflows/8111
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:34
description:
  ⭐ Google Review Sentiment Analysis & Slack Notification Workflow  

  This workflow automates the process of collecting Google Business Profile reviews 🏪, analyzing customer sentiment with Google Gemini 🤖✨, and sending structured reports to Slack 💬.  

  🔑 Key Advantages  
  📥 Fetches Google Business Profile reviews for a given business and time period  
  🧠 Runs sentiment analysis using Gemini AI  
  📊 Consolidates comments, ratings, and trends into a JSON-based summary  
  🧩 Restructures results into Slack Block Kit format for easy readability  
  🚀 Sends automated sentiment reports directly to a Slack channel  

  ⚙️ Set Up Essentials You’ll Need  
  🔑 Google Business Profile API access with project approval  
  ✅ Enabled Google Business Profile API service  
  🔐 Gemini API credentials  
  💬 Slack workspace & channel for receiving reports  

  🚀 How to Get Started  
  🔧 Configure your Google Business Profile API and enable access  
  👤 Set the owner name and 📍 location to fetch reviews  
  ⏳ Define the review time period using the Set Time Period node  
  🔗 Connect your Slack account and select a channel for notifications  
  🕒 Deploy and let the workflow run on schedule for automated insights  

nodes_used:
  ["n8n-nodes-base.googleBusinessProfile","@n8n/n8n-nodes-langchain.sentimentAnalysis","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.filter","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.slack","n8n-nodes-base.slack","n8n-nodes-base.slack"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","sentiment analysis","AI"],"complexity":"medium","use_cases":["Monitor Google Business Profile reviews","Automated sentiment analysis of customer feedback","Send structured sentiment reports to Slack","Reputation management and trend tracking","Alerting support/marketing teams about negative reviews"],"estimated_setup_minutes":45,"required_services":["Google Business Profile API (Google Cloud project & API enabled)","Google Gemini (Gemini API credentials)","Slack workspace & app with channel access","n8n instance (for scheduling/execution)"],"key_features":["Fetches Google Business Profile reviews for a selected location and time period","Performs sentiment analysis using Google Gemini","Aggregates comments, ratings and trends into a JSON summary","Restructures output into Slack Block Kit format for readable reports","Sends automated reports to a Slack channel on a schedule"],"target_audience":["Customer support teams","Marketing and community managers","Business owners handling online reputation management`,`Developers/automation engineers implementing review monitoring workflows"]}


name: Automate Meeting Notes Summaries with Gemini AI & Slack Notifications
author_name: Sayone Technologies
author_username: sayonetech
categories: []
created_at: 2025-09-01T11:12:07.061Z
updated_at: 2025-09-01T11:12:07.061Z
url: https://n8n.io/workflows/8116
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:34
description:
  📝 Meeting Notes Summarizer & Slack Notifier

  Easily keep your team aligned by summarizing meeting notes, extracting action items, and delivering them directly to Slack.

  🚀 What This Workflow Does
  ⏰ Triggers on a schedule to fetch meeting data from your note-taking tool  
  📄 Retrieves meeting summaries and action items using the MeetGeek API  
  🤖 Uses Google Gemini AI to generate concise summaries and action points  
  🎨 Restructures the output into Slack Block Kit format  
  📢 Sends daily Slack notifications with clear summaries and actionable tasks  

  👥 Who Is This For?
  👩‍💼 Teams that want automated daily meeting briefs  
  📌 Project managers who need action items clearly assigned  
  🌍 Remote or hybrid teams using Slack as their main communication hub  
  ⏳ Anyone looking to reduce the time spent reviewing long meeting notes  

  🛠️ Technical Requirements
  🔑 API key & credentials for your meeting note-taking app  
  🤝 Google Gemini AI credentials  
  💬 Slack workspace with proper OAuth setup  

  ⚡ Set Up the Workflow with Ease
  🗂️ Configure your meeting note API in the “Get Meetings List” and “Summary” nodes.  
  🤖 Add Gemini AI credentials for generating summaries.  
  🔗 Connect your Slack channel for notifications.  
  ✅ Activate the workflow so that your team will start receiving daily meeting insights automatically.  

  🎨 Want to Customize It Further?
  🔄 Change the trigger schedule (daily, weekly, or after each meeting).  
  🎭 Modify the Slack Block Kit layout for different formatting styles.  
  📧 Add extra integrations like email, Notion, or Google Docs to save notes.  
  ✍️ Adjust the AI prompt for different summary styles (short/long, formal/casual, etc.).  
  🔍 Filter meetings by specific teams, projects, or keywords.  
  🌐 Customize the API URL in the HTTP Request node to connect with other note-taking tools or different API endpoints.  

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.aiTransform","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.slack","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.dateTime","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5352 characters]

metadata_json:
  {"categories":["automation","integration","notifications","AI","collaboration"],"complexity":"medium","use_cases":["Automated daily meeting briefs","Summarize meeting notes and extract action items","Deliver concise updates to Slack channels","Filter meetings by team/project/keywords","Adaptable formatting for different audiences or storage destinations"],"estimated_setup_minutes":30,"required_services":["MeetGeek or other meeting-notes API (HTTP)","Google Gemini AI (lmChatGoogleGemini)","Slack workspace with OAuth","n8n instance"],"key_features":["Scheduled trigger to fetch meetings","Retrieve meeting summaries and action items via API","Use Google Gemini AI to generate concise summaries and action points","Format output into Slack Block Kit","Send Slack notifications with summaries and tasks (per schedule)"],"target_audience":["Teams that need daily meeting briefs","Project managers tracking action items","Remote or hybrid teams using Slack as primary communication tool"]}


name: Extract Amazon Book Data & Generate Purchase Reports with Decodo Scraper
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-09-02T04:15:58.617Z
updated_at: 2025-09-02T04:15:58.617Z
url: https://n8n.io/workflows/8142
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:34
description:
  Decodo Scraper API Workflow Template (n8n Automation Amazon Book Purchase Report)
  Watch the demo video below:

  &gt; This workflow demos how to use Decodo Scraper API to crawl any public web page (headless JS, device emulation: mobile/desktop/tablet), extract structured product data from the returned HTML, generate a purchase-ready report, and automatically deliver it as a Google Doc + PDF to Slack/Drive.
  Who’s it for
  Creators / Analysts** who need quick product lists (books, gadgets, etc.) with prices/ratings.
  Ops & Marketing teams** building weekly “top picks” reports.
  Engineers** validating the Decodo Scraper API + LLM extraction pattern before scaling.

  How it works / What it does

  Trigger – Manually run the workflow.
  Edit Fields (manual) – Provide inputs:
     targetUrl (e.g., an Amazon category/search/listing page)
     deviceType (desktop | mobile | tablet)
     Optional: maxItems, notes, reportTitle, reportOwner
  Scraper API Request (HTTP Request → POST)  
     Calls Decodo Scraper API with:
     URL to crawl, headless JS enabled
     Device emulation (UA + viewport)
     Optional waitFor / executeJS to ensure late-loading content is captured
  HTML Response Parser (Code/Function or HTML node)  
     Pulls the HTML string from Decodo response and normalizes it (strip scripts/styles, collapse whitespace).
  Product Analyzer Agent (LLM + Structured Output Parser)  
     Prompts an LLM to extract structured “book” objects from the HTML:
     The Structured Output Parser enforces a strict JSON schema and drops malformed items.
  Build 📚 Book Purchase Report (Code/LLM)  
     Converts the JSON array into a Markdown (or HTML) report with:
     Executive summary (top picks, average price/rating)
     Table of items (rank, title, author, price, rating, link)
     “Recommended to buy” shortlist (rules configurable)
     Notes / owner / timestamp
  Configure Google Drive Folder (manual)  
     Choose/create a Drive folder for output artifacts.
  Create Document File (Google Docs API)  
     Creates a Doc from the generated Markdown/HTML.
  Convert Document to PDF (Google Drive export)  
     Exports the Doc to PDF.
  Upload report to Slack  
     Sends the PDF (and/or Doc link) to a chosen Slack channel with a short summary.

  How to set up

  1 Prerequisites
  n8n** (self-hosted or Cloud)
  Decodo Scraper API** key
  OpenAI (or compatible) API key** for the Analyzer Agent
  Google Drive/Docs** credentials (OAuth2)
  Slack** Bot/User token (files:write, chat:write)

  2 Environment variables (recommended)
  DECODO_API_KEY
  OPENAI_API_KEY
  DRIVE_FOLDER_ID (optional default)
  SLACK_CHANNEL_ID

  3 Nodes configuration (high level)
  Edit Fields (Set node)
  Scraper API Request (HTTP Request → POST)
  HTML Response Parser (Code node)
  Product Analyzer Agent
  Build Book Purchase Report (Code/LLM)
  Create Document File
  Convert to PDF
  Upload to Slack

  Requirements

  Decodo**: Active API key and endpoint access. Be mindful of concurrency/rate limits.
  Model**: GPT-4o/4.1-mini or similar for reliable structured extraction.
  Google**: OAuth client (Docs/Drive scopes). Ensure n8n can write to the target folder.
  Slack**: Bot token with files:write + chat:write.

  How to customize the workflow

  Target site: Change targetUrl to any **public page (category, search, or listing).  
    For other domains (not Amazon), tweak the LLM guidance (e.g., price/label patterns).
  Device emulation**: Switch deviceType to mobile to fetch mobile-optimized markup (often simpler DOMs).
  Late-loading pages**: Adjust waitFor.selector or use waitUntil: "networkidle" (if supported) to ensure full content loads.
  Client-side JS**: Extend executeJS if you need to interact (scroll, click “next”, expand sections). You can also loop over pagination by iterating URLs.
  Extraction schema**: Add fields (e.g., discount_percent, bestseller_badge, prime_eligible) and update the Structured Output schema accordingly.
  Filtering rules**: Modify recommendation logic (e.g., min ratings count, price bands, languages).
  Report branding**: Add logo, cover page, footer with company info; switch to HTML + inline CSS for richer Docs formatting.
  Destinations**: Besides Slack & Drive, add Email, Notion, Confluence, or a database sink.
  Scheduling: Add a **Cron trigger for weekly/monthly auto-reports.

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.slack","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@decodo/n8n-nodes-decodo.decodo"]

workflow_json_compressed:
  [encoded data, 13220 characters]

metadata_json:
  {"categories":["automation","web scraping","data extraction","reporting","integrations"],"complexity":"medium","use_cases":["Generate product/book purchase reports from Amazon category/search pages","Create weekly \"top picks\" or curated product lists for marketing/ops","Price and rating monitoring for product research","Validate scraper + LLM extraction patterns before scaling","Deliver structured extraction outputs to Slack/Drive/Docs for stakeholders"],"estimated_setup_minutes":45,"required_services":["n8n (self-hosted or n8n.cloud)","Decodo Scraper API (API key)","OpenAI or compatible LLM API (API key)","Google Drive / Google Docs (OAuth2 credentials)","Slack (bot/user token with files:write and chat:write)"],"key_features":["Headless-JS crawling with device emulation (mobile/desktop/tablet)","HTML normalization and parsing of returned page","LLM-based structured extraction enforced by a Structured Output Parser (strict JSON schema)","Configurable extraction fields (title, author, price, rating, link, etc.)","Automated report generation (Markdown/HTML) with executive summary and shortlist rules</br>(rankings, averages, recommended-to-buy logic)"],"target_audience":["Creators and analysts needing quick product lists","Marketing and Ops teams creating regular product reports","Engineers prototyping scraper+LLM extraction pipelines"]}


name: Generate AI Videos from Telegram Messages with Nano Banana & Veo-3
author_name: Sulieman Said
author_username: sulieman-said
categories: []
created_at: 2025-09-02T20:19:21.131Z
updated_at: 2025-09-02T20:19:21.131Z
url: https://n8n.io/workflows/8189
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  How to use the provided n8n workflow (step‑by‑step), what matters, what it’s good for, and costs per run.

  What this workflow does (in simple terms)
  1) You write (or speak) your idea in Telegram.
  2) The workflow builds two short prompts:
     Image prompt → generates one thumbnail via KIE.ai – Nano Banana (Gemini 2.5 Flash Image).
     Video prompt → starts a Veo‑3 (KIE.ai) video job using the thumbnail as init image.
  3) You receive the thumbnail first, then the short video back in Telegram once rendering completes.

  Typical output: 1 PNG thumbnail + 1 short MP4 video (e.g., 8–12 s, 9:16).

  Why this is useful
  Rapid ideation**: Turn a quick text/voice idea into a ready‑to‑post thumbnail + matching short video.
  Consistent look: The video uses the thumbnail as **init image, keeping colors, objects and mood consistent.
  One chat = full pipeline**: Everything happens directly inside Telegram—no context switches.
  Agency‑ready**: Collect ideas from clients/team chats, and deliver outputs quickly.

  What you need before importing
  1) KIE.ai account & API key
     Sign up/in at KIE.ai, go to Dashboard → API / Keys.
     Copy your KIE_API_KEY (keep it private).

  2) Telegram Bot (BotFather)
     In Telegram, open @BotFather → command /newbot.
     Choose a name and a unique username (must end with bot).
     Copy your Bot Token (keep it private).

  3) Your Telegram Chat ID (browser method)
     Send any message to your bot so you have a active chat
     Open Telegram web and the chat with the bot
     Find the chatid in the URL

  Import & minimal configuration (n8n)
  1) Import the provided workflow JSON in n8n.
  2) Create Credentials:
     Telegram API: paste your Bot Token.
     HTTP (KIE.ai): usually you’ll pass Authorization: Bearer {{ $env.KIE_API_KEY }} directly in the HTTP Request node headers, or make a generic HTTP credential that injects the header.
  3) Replace hardcoded values in the template:
     Chat ID: use an Expression like {{$json.message.chat.id}} from the Telegram Trigger (prefer dynamic over hardcoded IDs).
     Authorization headers: never in query params—always in Headers.
     Content‑Type spelling: Content-Type (no typos).
   `

  How to run it (basic flow)
  1) Start the workflow (activate trigger).
  2) Send a message to your bot, e.g.  
     glass hourglass on a black mirror floor, minimal, elegant
  3) The bot replies with the thumbnail (PNG), then the Veo‑3 video (MP4).

  If you send a voice message, the flow will download & transcribe it first, then proceed as above.

  Pricing (rule of thumb)
  Image (Nano Banana via KIE.ai):* ~ *$0.02–$0.04** per image (plan‑dependent).
  Video (Veo‑3 via KIE.ai):**
    Fast:  $0.40 per 8 seconds ($0.05/s)
    Quality:  $2.00 per 8 seconds ($0.25/s)

  Typical run (1 image + 8 s Fast video) ≈ $0.42–$0.44.

  &gt; These are indicative values. Check your KIE.ai dashboard for the latest pricing/quotas.

  Why KIE.ai over the “classic” Google API?
  Cheaper in practice** for short video clips and image gen in this pipeline.
  One vendor** for both image & video (same auth, similar responses) = less integration hassle.
  Quick start**: Playground/tasks/status endpoints are n8n‑friendly for polling workflows.

  Security & reliability tips
  Never hardcode* API keys or Chat IDs into nodes—use *Credentials* or *Environment variables**.
  Add IF + error paths after each HTTP node:
    If status != 200 → Send friendly Telegram message (“Please try again”) + log to admin.
  If you use callback URLs for video completion, ensure the URL is publicly reachable (n8n Webhook URL). Otherwise, stick to polling.
  For rate limits, add a Wait node and limit concurrency in workflow settings.
  Keep aspect & duration consistent across prompt + API calls to avoid unexpected crops.

  Advanced: voice input (optional)
  The template supports voice via a Switch → Download → Transcribe (Whisper/OpenAI).  
  Ensure your OpenAI credential is set and your n8n instance can fetch the audio file from Telegram.

  Example prompt patterns (keep it short & generic)
  Thumbnail prompt**: “Minimal, elegant, surreal [OBJECT], clean composition, 9:16”
  Video prompt**: “Cinematic [OBJECT]. slow camera move, elegant reflections, minimal & surreal mood, 9:16, 8–12s.”

  You can later replace the simple prompt builder with a dedicated LLM step or a fixed style guide for your brand.

  Final notes
  This template focuses on a solid, reliable pipeline first. You can always refine prompts later.
  Start with Veo‑3 Fast to keep iteration costs low; switch to Quality for final renders.
  Consider saving outputs (S3/Drive) and logging prompts/URLs to a sheet for audit & analytics.


  Questions or custom requests?  
  📩 suliemansaid.business@gmail.com

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.telegramTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4524 characters]

metadata_json:
  {"categories":["automation","integration","ai","media production","social media"],"complexity":"medium","use_cases":["Rapid ideation: turn text/voice ideas into ready-to-post thumbnail + short video","Social media short-video production (9:16 clips)","Agency client deliverables and review loops via chat","Voice-to-video workflows (transcribe voice → generate media)","Automated thumbnail + video generation for campaigns"],"estimated_setup_minutes":30,"required_services":["KIE.ai (Nano Banana image + Veo‑3 video)","Telegram Bot API (Bot token and chat)","n8n instance (self‑hosted or n8n.cloud)","Publicly reachable webhook endpoint (ngrok / n8n.cloud) if using callbacks","Optional: OpenAI/Whisper for transcription","Optional: Storage (S3 / Google Drive) for saving outputs"],"key_features":["Generates one PNG thumbnail via Nano Banana then uses it as init image for Veo‑3 video","Delivers thumbnail and resulting MP4 back to the same Telegram chat","Supports text and voice input (downloads + transcribes before generation)","Polling or webhook-friendly video completion handling","Built-in error paths (IF nodes) and recommendations for credential usage (env vars) and rate limiting (Wait node)"],"target_audience":["Social media managers and creators","Digital agencies and producers","Growth marketers and content strategists collecting client ideas in chat formally or informally at scale (team chats)  - technical users comfortable with n8n setup (developers/automation engineers)"]}


name: Generate Product Mockups with Nano Banana (Gemini 2.5 Flash Image)
author_name: The Growth Bolt
author_username: thegrowthbolt-shivam
categories: []
created_at: 2025-09-02T20:55:51.976Z
updated_at: 2025-09-02T20:55:51.976Z
url: https://n8n.io/workflows/8194
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  This n8n template uses AI to generate product mockups by composing a product image onto a model or template image.

  This workflow provides a powerful solution for creating dynamic marketing assets and e-commerce visuals. Use cases are many: Instantly create virtual try-on images for apparel, place your product into different scenes for advertisements, or generate custom marketing material without needing a physical photoshoot.

  Good to know
  This workflow uses the OpenRouter API to access Google's Gemini model. You will need an OpenRouter account.
  The model used is google/gemini-2.5-flash-image-preview:free. While this specific model may be free, costs can vary depending on the model you choose and your usage on OpenRouter. Always check their latest pricing.
  The workflow is triggered by a form. To use it, you must activate the workflow and use its Production URL.

  How it works
  A user submits a product image, a template/model image, and a text prompt via the n8n form trigger.
  The images are then converted to Base64 strings so they can be used in an API request.
  A multimodal payload is sent to the OpenRouter API. Gemini's image generation model is used, which takes all 3 inputs (the two images and the prompt) to understand how to compose the final image.
  Gemini generates a new image based on the instructions and returns it as a Base64 string.
  The workflow extracts this output string and uses a "Convert to file" node to convert the data back into a binary image file, ready for use.

  How to use
  First, set up your OpenRouter API credential in n8n.
  Activate the workflow.
  Open the Production URL for the form trigger.
  Upload your product image, your template image, and write a descriptive prompt.
  Submit the form to execute the workflow and generate your image.

  Requirements
  An active n8n instance.
  An OpenRouter account and API key.

  Customising this workflow
  You can easily change the AI model by editing the JSON body in the HTTP Request node. OpenRouter provides access to a wide variety of models from different providers.
  Add a final step to automatically save the generated image. You can connect nodes for services like Google Drive, AWS S3, or Dropbox after the "Convert to File" node.
  Replace the Form Trigger with a Webhook Trigger to run this workflow programmatically from another application or service.

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.convertToFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","AI image generation","e-commerce","marketing"],"complexity":"medium","use_cases":["Generate product mockups for e-commerce listings","Virtual try-on or apparel previews","Create marketing/ad visuals without photoshoots","Compose products into different scenes for campaigns","On-demand branded creative generation"],"estimated_setup_minutes":15,"required_services":["n8n instance","OpenRouter API (access to google/gemini-2.5-flash-image-preview)","OpenRouter API key / credential","Optional: cloud storage (Google Drive, AWS S3, Dropbox) for saving outputs"],"key_features":["Multimodal input: accepts product image, template/model image, and textual prompt","Uses Gemini image model via OpenRouter to compose final image","Form trigger with Production URL for easy user uploads","Converts images to/from Base64 and back to binary file","Configurable HTTP request JSON to swap AI model or provider"],"target_audience":["marketers","e-commerce managers","product designers/content creators needing mockups quickly"]}


name: Summarize Content from URLs, Text & PDFs using OpenAI
author_name: Dahiana
author_username: mssporto
categories: []
created_at: 2025-09-03T11:04:17.272Z
updated_at: 2025-09-03T11:04:17.272Z
url: https://n8n.io/workflows/8210
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  AI Content Summarizer Suite

  This n8n template collection demonstrates how to build a comprehensive AI-powered content summarization system that handles multiple input types: URLs, raw text, and PDF files. Built as 4 separate workflows for maximum flexibility.
  Use cases: Research workflows, content curation, document processing, meeting prep, social media content creation, or integrating smart summarization into any app or platform.

  How it works
  Multi-input handling: Separate workflows for URLs (web scraping), direct text input, and PDF file processing
  Smart PDF processing: Attempts text extraction first, falls back to OCR.Space for image-based PDFs
  AI summarization: Uses OpenAI's GPT-4.1-mini with customizable length (brief/standard/detailed) and focus areas (key points/numbers/conclusions/action items)
  Language support: Multi-language summaries with automatic language detection
  Flexible output: Returns clean markdown-formatted summaries via webhook responses
  Unified option: The all-in-one workflow automatically detects input type and routes accordingly

  How to use
  Replace webhook triggers with your preferred method (manual, form, API endpoint)
  Each workflow accepts different parameters: URL, text content, or file upload
  Customize summary length and focus in the AI prompt nodes
  Authentication is optional - switch to "none" if running internally
  Perfect for integration with Bubble, Zapier, or any platform that can make HTTP requests

  Requirements
  OpenAI API key or OpenRouter Keys
  OCR.Space API key (for PDF fallback processing)
  n8n instance (cloud or self-hosted)
  Any platform that can make HTTP requests.

  Setup Steps
  Replace "Dummy OpenAI" with your OpenAI credentials
  Add your OCR.Space API key in the OCR nodes is not mandatory.
  Update webhook authentication as needed
  Test each workflow path individually

nodes_used:
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workflow_json_compressed:
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metadata_json:
  {"categories":["automation","AI","document processing","integration"],"complexity":"complex","use_cases":["Research workflows","Content curation","Document processing","Meeting preparation","Social media content creation / copy generation"],"estimated_setup_minutes":30,"required_services":["OpenAI API (or OpenRouter)","OCR.Space API (for image-based PDFs fallback)","n8n instance (cloud or self-hosted)","Any HTTP/webhook-capable platform (Bubble, Zapier, custom API clients)"],"key_features":["Handles multiple input types: URLs (web scraping), raw text, and PDFs","Smart PDF processing with text extraction and OCR fallback","AI summarization via GPT-4.1-mini with customizable length and focus","Automatic language detection and multi-language summaries","Flexible outputs as clean Markdown via webhook responses or API integration"],"target_audience":["Developers / engineers implementing integrations","Content marketers and social media managers","Researchers and knowledge workers doing literature review or curation"]}


name: Generate AI Videos from Text or Images with Veo 3 API and VietVid.com
author_name: Tran Trung Nghia
author_username: trungnghialk
categories: []
created_at: 2025-09-03T11:32:22.559Z
updated_at: 2025-09-03T11:32:22.559Z
url: https://n8n.io/workflows/8213
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Veo 3 Video Generator via VietVid.com API (n8n)

  Overview
  This workflow leverages the VietVid.com Veo3 model to generate AI videos from simple text descriptions or optional images.  
  Users interact via a form interface, inputting a prompt (e.g., a scene description), choosing aspect ratio and model, then the system automatically submits the request to the VietVid API, monitors the generation status in real time, and retrieves the final video output.  

  It’s ideal for content creators, marketers, and developers exploring text-to-video AI creation, supporting intelligent video generation with minimal setup.

  Prerequisites
  A VietVid.com account and API key: Register at VietVid.com to obtain your free or paid API key.  
  An active n8n instance (cloud or self-hosted) with HTTP Request, Wait, and form submission capabilities.  
  Basic knowledge of AI prompts for video generation to achieve optimal results.  

  Setup Instructions

  1. Obtain API Key
  Register at VietVid.com and generate your API key.  
  Store it securely—do not share publicly.  

  2. Configure the Form
  In the Form Trigger node, ensure the following fields are available:
    text_prompt — video description (e.g., “A serene mountain landscape at sunset with birds flying”)  
    ImageURL [optional] — optional image input for image-to-video  
    api_Token — your VietVid API key  
    aspect_Ratio [16:9,9:16] — dropdown to select ratio  
    model — choose between veo3 and veo3_fast  

  3. Test the Workflow
  Click Execute Workflow in n8n.  
  Access the generated form URL.  
  Submit your prompt, API key, and options.  
  The workflow will poll the VietVid API every 10 seconds until the video is ready.  

  4. Handle Outputs
  The final Set node formats and displays the video links:
    720p_link — always available when ready.  
    1080p_link — available only for 16:9 aspect ratio.  

  Customization Tips
  Enhance prompts*: Add details like style (realistic, cinematic, animated*), duration, actions, and camera/lighting for better results.  
  Stability**: Fix the seeds value (e.g., 50000) for more consistent characters.  
  Webhook Response: Add a **Webhook Response node to return a clean JSON payload for frontend integrations.  
  Adjust polling delay**: Modify Wait node (8–15s) if needed to balance speed vs. API calls.  

nodes_used:
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metadata_json:
  {"categories":["automation","AI content generation","video production","integration"],"complexity":"medium","use_cases":["Text-to-video generation for marketing and social media","Image-to-video creation (optional)","Automated video production for apps or pipelines","Prototyping AI-generated video concepts","Returning video assets to frontends via webhook"],"estimated_setup_minutes":15,"required_services":["VietVid.com (Veo3 API)","n8n (cloud or self-hosted)","Optional: hosting/frontend to present form or receive webhook responses"],"key_features":["Generate videos from text prompts","Optional image-to-video input","Choose aspect ratio (16:9 or 9:16) and model (veo3 / veo3_fast)","Automatic polling of VietVid job status","Outputs 720p link (and 1080p link for 16:9) when ready￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼"],"target_audience":["Content creators","Marketers and social media managers","Developers integrating text-to-video into apps or services￼￼￼￼￼￼"]}


name: Log E-commerce Orders in Google Sheets with Monthly Tabs & Status Tracking
author_name: Ruthwik
author_username: ruthwik
categories: []
created_at: 2025-09-04T08:51:22.229Z
updated_at: 2025-09-04T08:51:22.229Z
url: https://n8n.io/workflows/8244
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  n8n Google Sheets Monthly Order Logger

  This n8n template records incoming e-commerce orders into Google Sheets, auto-creates a monthly sub-sheet, and adds a “Status” dropdown so your team can track fulfillment at a glance.

  Use cases

  Centralize order logs, coordinate shipping across months, trigger customer updates (e.g., WhatsApp/Email) from status changes, and build lightweight ops dashboards.

  Good to know

  The Google Sheet ID is the part in the URL between /d/ and the next slash:  
    https://docs.google.com/spreadsheets/d/&lt;sheetId&gt;/.
  A new sub-sheet is created every month (sheet name = current month, e.g., “September 2025”). If it already exists, the workflow appends to it.
  The Status column uses data validation with these options:  
    Not Shipped, Pickup Scheduled, Shipped, InTransit, Delivered, Cancelled.
  Make sure the Google credential in n8n has edit access to the spreadsheet.
  The Webhook URL must be updated in your Shopify Settings → Notifications → Webhooks page with the required Order events (e.g., Order creation, Order update, Order fulfillment).  
    Reference: Shopify Webhooks Guide

  How it works

  Order created (Webhook/Trigger): Receives a new order payload from your store/stack.  
  Config (set spreadsheetId): Stores the target Google Sheets spreadsheetId (copied from the URL).  
  Get Order Sheets metadata: Lists existing tabs to see if the tab for the current month already exists.  
  Generate Sheet Name: Computes the sheet name like {{ $now.format('MMMM YYYY') }}.  
  If (sheet exists?):  
     True → Google Sheets Row values (existing): Prepares the row for append using the month tab.  
     Append to Existing Orders Sheet: Appends the order as a new row.  
     False → Set Sheet Starting row/col: Sets starting cell (e.g., A1) for a brand-new month tab.  
     Create Month Sheet: Creates a new tab named for the current month.  
     Write Headers (A1:…): Writes the column headers.  
     Google Sheets Row values: Maps payload fields into the header order and applies validation to Status.  
     Append to Orders Sheet: Appends the first row into the newly created month tab.

  How to use

  In Config, paste your spreadsheetId from the sheet URL and confirm your Google credential has edit access.  
  (Optional) Adjust the month-tab naming format to match your preference.  
  In Shopify → Settings → Notifications → Webhooks, add your n8n webhook URL and select the Order events (Order creation, Order update, Order fulfillment, etc.) you want to capture.  
  Deploy the workflow and send a sample order to the trigger; a new month tab will be created automatically on the first order of each month.

  Requirements

  n8n instance with the Google Sheets node credential configured.  
  A Google Spreadsheet you own or can edit.  
  A Shopify store with webhook events enabled (see Shopify Webhooks Guide).

  Customising this workflow

  Add/remove columns (e.g., taxes, discounts, warehouse notes).  
  Change the Status list or add conditional formatting (e.g., green = Delivered).  
  Chain automations: on Status update → send tracking links, COD confirmation, or delivery feedback forms.  

  🚀 Innovate Beyond Boundaries  
  We help ambitious businesses harness the power of AI + automation for growth, efficiency, and customer delight. Contact us at info@zenithworks.ai

nodes_used:
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workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","e-commerce operations"],"complexity":"medium","use_cases":["Centralize and archive incoming e-commerce orders","Auto-create monthly sheets and append orders per month","Track fulfillment status with a dropdown for ops coordination","Trigger customer notifications (email/WhatsApp) from status changes","Build lightweight order/fulfillment dashboards"],"estimated_setup_minutes":20,"required_services":["n8n instance (with Google Sheets credential)","Google Sheets (spreadsheet edit access)","Shopify (webhooks enabled for order events)","Optional: Email/WhatsApp provider or other notification services for follow-ups"],"key_features":["Webhook trigger for Shopify order events","Auto-generate monthly sub-sheets named by month","Append new orders to existing month tab or create new tab with headers","‘Status’ column with data-validation dropdown (Not Shipped, Pickup Scheduled, Shipped, InTransit, Delivered, Cancelled)","Mapping of order payload fields to sheet columns for consistent logging"],"target_audience":["E‑commerce operations teams","Store owners and managers","Fulfillment/warehouse teams and customer support reps implementing tracking workflows」「Automation engineers/developers building integrations"]}


name: Learn Secure Webhook APIs with Authentication and Supabase Integration
author_name: Wayne Simpson
author_username: nocodecreative
categories: []
created_at: 2025-09-04T15:22:04.853Z
updated_at: 2025-09-04T15:22:04.853Z
url: https://n8n.io/workflows/8258
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  This template is a practical introduction to n8n Webhooks with built-in examples for all major HTTP methods and authentication types. It is designed as a learning resource to help you understand how webhooks work in n8n, how to connect them to a data store, and how to secure them properly.

  What’s included:

  Webhook nodes for GET, POST, PUT, PATCH, DELETE, and HEAD
  Demonstrations of Basic Auth, Header Auth, and JWT Auth
  Supabase integration for creating, retrieving, updating, and deleting rows
  Example response handling with Respond to Webhook nodes
  Sticky notes explaining each method, response type, and security option

  Use this template to:

  Learn how to configure and test webhooks in n8n
  Explore different authentication strategies
  Connect webhooks to a simple Supabase table
  Understand best practices for securing webhook endpoints

  This workflow is intended as an educational starting point. It shows you how to receive requests, map data, and return responses securely. For production use, adapt the structure, apply your own security policies, and extend the logic as needed.

  Check out the YouTube video here: https://www.youtube.com/watch?v=o6F36xsiuBk

nodes_used:
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  [encoded data, 4616 characters]

metadata_json:
  {"categories":["integration","education","security","automation"],"complexity":"medium","use_cases":["Learn and test n8n webhook setup for all HTTP methods","Explore and compare authentication strategies (Basic, Header, JWT)","Prototype webhook-driven CRUD workflows using Supabase","Demonstrate secure response handling and webhook best practices"],"estimated_setup_minutes":20,"required_services":["n8n instance","Supabase project (database/table)","JWT provider or secret for JWT examples"],"key_features":["Webhook endpoints for GET, POST, PUT, PATCH, DELETE, HEAD","Examples of Basic Auth, Header Auth, and JWT Auth","Supabase CRUD integration (create, retrieve, update, delete rows)","Respond to Webhook nodes demonstrating response patterns","Inline documentation via sticky notes explaining methods and security"],"target_audience":["developers","integration engineers","QA/learners testing webhooks”, "]}


name: Build a Multichannel Customer Support AI Assistant with Chatwoot & OpenRouter
author_name: George Zargaryan
author_username: zrgrn
categories: []
created_at: 2025-09-04T16:02:13.770Z
updated_at: 2025-09-04T16:02:13.770Z
url: https://n8n.io/workflows/8260
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Multichannel AI Assistant Demo for Chatwoot

  This simple n8n template demonstrates a Chatwoot integration that can:

  Receive new messages via a webhook.
  Retrieve conversation history.
  Process the message history into a format suitable for an LLM.
  Demonstrate an AI Assistant processing a user's query.
  Send the AI Assistant's response back to Chatwoot.

  Use Case:
  If you have multiple communication channels with your clients (e.g., Telegram, Instagram, WhatsApp, Facebook) integrated with Chatwoot, you can use this template as a starting point to build more sophisticated and tailored AI solutions that cover all channels at once.

  How it works
  A webhook receives the message created event from Chatwoot.
  The webhook data is then filtered to keep only the necessary information for a cleaner workflow.
  The workflow checks if the message is "incoming." This is crucial to prevent the assistant from replying to its own messages and creating endless loops.
  The conversation history is retrieved from Chatwoot via an API call using the HTTP Request node. This allows the assistant's interaction to be more natural and continuous without needing to store conversation history locally.
  A simple AI Assistant processes the conversation history and generates a response to the user based on its built-in knowledge base (see the prompt in the assistant node).
  The final HTTP Request node sends the AI-generated response back to the appropriate Chatwoot conversation.

  How to Use
  In Chatwoot, go to Settings → Integrations → Webhooks and add your n8n webhook URL. Be sure to select the message created event.
  In the HTTP Request nodes, replace the placeholder values:
      https://yourchatwooturl.com
      api_access_token
      You can find these values on your Chatwoot super admin page.
  The LLM node is configured to use OpenRouter. Add your OpenRouter credentials, or replace the node with your preferred LLM provider.

  Requirements
  An API key for OpenRouter or credentials for your preferred LLM provider.
  A Chatwoot account with at least one integrated channel and super admin access to obtain the api_access_token.

  Need Help Building Something More?

  Contact me on:
  Telegram:** @ninesfork
  LinkedIn:** George Zargaryan

  Happy Hacking! 🚀

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8404 characters]

metadata_json:
  {"categories":["integration","automation","customer support","AI","multichannel messaging"],"complexity":"simple","use_cases":["Receive customer messages via webhook","Retrieve conversation history from Chatwoot","Format message history for a large language model","Generate AI assistant responses using OpenRouter","Send AI responses back to Chatwoot across channels (Telegram, Instagram, WhatsApp, Facebook)"],"estimated_setup_minutes":15,"required_services":["Chatwoot","OpenRouter (LLM)","Messaging platforms integrated with Chatwoot (Telegram, Instagram, WhatsApp, Facebook)","n8n (cloud or self-hosted)"],"key_features":["Webhook listener for inbound messages","Conversation history retrieval from Chatwoot","Processing/formatting conversation history for LLM input","AI assistant response generation via OpenRouter","Posting generated replies back to Chatwoot to reach original channel (multichannel)"],"target_audience":["Developers","Customer support teams","Support engineers/automation owners"]}


name: Dynamic MCP Server Selection with OpenAI GPT-4.1 and Contextual AI Reranker
author_name: Jinash Rouniyar
author_username: jinash
categories: []
created_at: 2025-09-05T03:48:50.424Z
updated_at: 2025-09-05T03:48:50.424Z
url: https://n8n.io/workflows/8272
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  PROBLEM
  Thousands of MCP Servers exist and many are updated daily, making server selection difficult for LLMs.
  Current approaches require manually downloading and configuring servers, limiting flexibility.
  When multiple servers are pre-configured, LLMs get overwhelmed and confused about which server to use for specific tasks.

  This template enables dynamic server selection from a live PulseMCP directory of 5000+ servers.

  How it works
  A user query goes to an LLM that decides whether to use MCP servers to fulfill a given query and provides reasoning for its decision.
  Next, we fetch MCP Servers from Pulse MCP API and format them as documents for reranking
  Now, we use Contextual AI's Reranker to score and rank all MCP Servers based on our query and instructions

  How to set up
  Sign up for a free trial of Contextual AI here to find CONTEXTUALAI_API_KEY.
  Click on variables option in left panel and add a new environment variable CONTEXTUALAI_API_KEY.
  For the baseline model, we have used GPT 4.1 mini, you can find your OpenAI API key here

  How to customize the workflow
  We use chat trigger to initate the workflow. Feel free to replace it with a webhook or other trigger as required.
  We use OpenAI's GPT 4.1 mini as the baseline model and reranker prompt generator. You can swap out this section to use the LLM of your choice.
  We fetch 5000 MCP Servers from the PulseMCP directory as a baseline number, feel free to adjust this parameter as required.
  We are using Contextual AI's ctxl-rerank-v2-instruct-multilingual reranker model, which can be swapped with any one of the following rerankers: 
    1) ctxl-rerank-v2-instruct-multilingual
    2) ctxl-rerank-v2-instruct-multilingual-mini
    3)  ctxl-rerank-v1-instruct
  You can checkout this blog for more information about rerankers to learn more about them.

  Good to know:
  Contextual AI Reranker (with full MCP docs): ~$0.035/query
  Includes 0.035 for reranking + ~$0.0001 for OpenAI instruction generation.
  OpenAI Baseline: ~$0.017/query

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.if","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.chat","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.chat"]

workflow_json_compressed:
  [encoded data, 5836 characters]

metadata_json:
  {"categories":["automation","integration","AI/ML","orchestration"],"complexity":"complex","use_cases":["Dynamic routing of requests to the most appropriate MCP server","Reducing LLM confusion by selecting contextually relevant servers","Automating server discovery from a live directory (PulseMCP)","Hybrid decision-making using an LLM plus a contextual AI reranker","Scaling multi-server workflows without manual configuration"],"estimated_setup_minutes":30,"required_services":["OpenAI GPT-4.1 (or compatible LLM)","Contextual AI Reranker service","PulseMCP live directory (HTTP API)","n8n instance (with webhook/HTTP access)"],"key_features":["Live directory lookup of 5000+ MCP servers","LLM-based decision to determine whether to use an MCP server","Contextual AI reranker to rank candidate servers for best fit","Conditional logic and fallback handling when no clear server is chosen","Merges and code nodes for custom filtering/formatting and integration"],"target_audience":["AI/ML engineers","Platform/DevOps engineers","Developers building LLM-based apps or retrieval-augmented systems (RAG)"]}


name: AI Recruiting Pipeline: Job to Candidate Shortlist with Apollo & Airtable
author_name: Fabian Herhold
author_username: fabianherh
categories: []
created_at: 2025-09-05T10:28:25.383Z
updated_at: 2025-09-05T10:28:25.383Z
url: https://n8n.io/workflows/8292
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Who’s it for
  Recruiting agencies, executive search firms, and in-house talent teams that want to automate candidate sourcing and prequalification. Instead of spending hours searching, scoring, and writing outreach, this workflow turns any job description into a ready-to-use shortlist with personalized messages.

  Youtube Walkthrough

  What it does (How it works)
  This workflow takes a job description (title, description, and location) and runs a complete recruiting automation pipeline:

  Normalize job titles** and generate variations to widen search coverage.
  Search candidates** in Apollo (or your CRM / database of choice).
  Remove duplicates** to keep clean lists.
  Score candidates** with AI (0–5) and provide concise reasoning across experience, industry, and seniority.
  Enrich LinkedIn profiles** (name, title, image, location, experience).
  Create structured candidate assessments** (summary, alignment, red flags, positives).
  Generate outreach messages** (email + LinkedIn DM) tailored to the candidate.
  Write to Airtable** for job/candidate tracking and downstream automation.

  Everything is plug-and-play, with no manual searching or copy-pasting required.

  Requirements
  n8n (Cloud or self-hosted)  
  Airtable account + API access  
  Apollo API or your preferred candidate source  
  LLM provider: OpenAI or Anthropic  
  LinkedIn enrichment API (RapidAPI, Apify, etc.)  

  &gt; ⚠️ Do not hardcode API keys in HTTP nodes. Always use Credentials in n8n.

  Airtable table specifications
  Create one base (e.g., Candidate Search – From Job Description) with two tables:

  Jobs Table  
  Job Title (text)  
  Job Description (long text)  
  Job Location (text)  
  Candidates (linked to Candidates table)

  Candidates Table  
  Core fields: Name, LinkedIn URL, Job Title, Location, Image URL, Job Searches (linked)  
  Assessment fields: Summary Fit Score, Executive Summary, Title Alignment, Skill Alignment, Industry Alignment, Seniority Alignment, Company Type Alignment, Educational Alignment, Potential Red Flags, Positive Signals, Final Recommendation, Next Steps Suggestion  
  Outreach fields: Email Subject, Email Body, LinkedIn Message

  How to set up
  Connect credentials  
     Add Airtable, Apollo/CRM, and OpenAI/Anthropic credentials under n8n Credentials.

  Create Airtable base/tables  
     Follow the above spec for Jobs and Candidates. Match field names exactly to avoid mapping errors.

  Configure the trigger  
     The workflow starts from a Form/Webhook node. It captures:  
     Job Title (required)  
     Job Description (required)  
     Location (required)  
     Target Companies (optional, comma-separated domains)

  Job title mutation  
     The workflow uses an AI node to normalize the job title and generate up to 5 variations for broader candidate searches.

  Candidate search  
     Apollo (or your CRM API) is queried with the generated titles and location filters. Results are deduped.

  AI scoring & structuring  
     Candidates are scored 0–5 with clear reasoning (experience, industry, seniority, general fit). Profiles are formatted into structured JSON for Airtable.

  LinkedIn enrichment  
     Enrichment API fetches missing data (geo, image, job history).

  Candidate assessment  
     An AI model produces a full recruiter-ready evaluation (fit summary, strengths, red flags).

  Outreach generation  
     The workflow drafts a concise cold email (&lt;75 words) and LinkedIn DM (&lt;60 words), consultative in tone.

  Write to Airtable  
      All jobs and candidates (with assessments and outreach messages) are logged for review and integration.

  How to customize
  Swap Apollo with your CRM** (Greenhouse, Bullhorn, etc.).  
  Adjust scoring prompts** to match your niche (sales, engineering, healthcare).  
  Add custom filters** for target companies or industries.  
  Change outreach tone** to align with your brand voice.  
  Limit by score** (e.g., only push candidates with score ≥4).  

  Security & best practices
  Store all keys in n8n Credentials (never in nodes).  
  Use Set nodes to centralize editable variables (title, location, filters).  
  Always add sticky notes in your workflow explaining steps.  
  Rename nodes clearly for readability.  

  Troubleshooting
  No candidates found?** Loosen title variations or broaden location.  
  Low fit scores?** Refine keywords and required skills in scoring prompts.  
  Airtable errors?** Double-check Base ID, Table ID, and field names.  
  API rate limits?** Enable batching/pagination and increase intervals.  

  SEO title:  
  Build candidate shortlists from a job description to Airtable with Apollo, AI scoring, and personalized outreach  

  Keywords: recruiting automation, Apollo people search, candidate enrichment, AI scoring, Airtable recruiting CRM, LinkedIn outreach, n8n workflow template

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.airtable","n8n-nodes-base.airtable","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.limit","n8n-nodes-base.limit","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.splitOut","n8n-nodes-base.removeDuplicates","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 15880 characters]

metadata_json:
  {"categories":["automation","integration","recruiting","data enrichment","AI"],"complexity":"complex","use_cases":["Automated candidate sourcing from job descriptions","Prequalifying and scoring candidates","Generating personalized outreach messages","Syncing shortlisted candidates to a database/ATS (Airtable)","Creating ready-to-review shortlists for recruiters"],"estimated_setup_minutes":60,"required_services":["Apollo (candidate database/prospecting)","Airtable (storage/ATS)","AI provider (e.g., OpenAI or other n8n-compatible model)","n8n instance with webhook/form access"],"key_features":["Convert job description into candidate search queries","Fetch and enrich candidate data from Apollo","AI-based scoring and prequalification of candidates","Generate personalized outreach messages","Write shortlisted candidates and metadata to Airtable for review"],"target_audience":["Recruiting agencies","Executive search firms","In-house talent acquisition teams / sourcers / recruiters"]}


name: Create an AI-Powered Virtual Receptionist with Google Calendar & Sheets
author_name: Risper
author_username: risper254
categories: []
created_at: 2025-09-06T13:11:50.134Z
updated_at: 2025-09-06T13:11:50.134Z
url: https://n8n.io/workflows/8326
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  🤖AI-Powered Appointment Scheduling with Google Calendar & Sheets Virtual Receptionist 

  Automate customer conversations with an AI-powered virtual receptionist. This workflow can chat naturally with clients, answer general business questions (like services, location, and hours), check availability in Google Calendar, book appointments, and save customer details in Google Sheets. Fully customizable for any business type — salons, clinics, agencies, consultants, and more.  

  📖 How It Works  

  Welcome the customer when the customer says hi  
     AI greets warmly: “Hello! I’m [AI name] from [Business name].”  

  Answer general questions  
     Provides instant replies about services, pricing, business location, hours, and availability.  

  Understand their need  
     Identifies the service requested and preferred time.  

  Check availability  
     Queries Google Calendar for open slots.  

  Gather customer details  
     Collects name, phone, and email (optional).  

  Confirm booking  
     Creates the appointment in Google Calendar.  

  Save records  
     Logs booking and customer info into Google Sheets.  

  ⚙️ Setup Steps (Quick)  
  Connect your Google Calendar and Google Sheets accounts.  
  Add your business details (name, type, services, hours, policies) to the Business Info Sheet.  
  Configure your OpenAI API key (or use n8n free credits).  
  Optional: Connect Twilio WhatsApp for direct chat responses.  

  🏢 Example Business Info (Google Sheet)  

  | business_id | business_name   | business_type       | location                          | phone           | email                     | services | calendar_id           | timezone | currency | working_hours                 | ai_name | ai_personality                   | ai_role                                                                                       | emergency_available | booking_advance_days | cancellation_hours |
  |-------------|-----------------|---------------------|----------------------------------|-----------------|---------------------------|----------|-----------------------|----------|----------|--------------------------------|---------|-----------------------------------|------------------------------------------------------------------------------------------------|----------------------|----------------------|-------------------|
  |001| Luxe Hair Studio | Hair & Beauty Salon | 123 Main Street, New York, NY 10001 | 1 (XXX) XXX-XXXX | yourbusiness@email.com | “Haircut & Styling (60 minutes, $3500…)Hair Coloring (120 minutes, $8000…)…” | calendar-id-here | GMT -3 | USD | Mon–Sat: 9:00 AM – 7:00 PM, Sun: Closed | bella | Friendly, Stylish, Professional | Manages bookings, answers FAQs, recommends services, gives beauty tips, sends reminders, etc. | no | 10 | 24 |

  ✅ Purpose: Supplies context (services, pricing, hours, AI personality, booking policies).  
  💡 The AI uses this sheet to answer general business questions (e.g., “Where are you located?”, “Do you do hair colouring?”, “What are your working hours?”).  

  📊 Appointments Sheet Example  

  | client_number | client_name | event_id  | summary                          | services |
  |----------------|-------------|-----------|----------------------------------|----------|
  | 001            | Sarah Lee   | evt-10293 | Appointment with Sarah Lee – Haircut & Styling | Haircut & Styling |
  | 002            | John Smith  | evt-10294 | Appointment with John Smith – Highlights | Highlights |

  ✅ Purpose: Logs confirmed bookings with service details and links back to Google Calendar.  

  💡 Features  
  ✅ AI receptionist with conversation memory  
  ✅ Answers FAQs – location, services, hours, pricing  
  ✅ Google Calendar integration for real-time availability  
  ✅ Google Sheets integration for customer records & reporting  
  ✅ Customizable AI name, role, and personality  

  🔑 Who It’s For  
  Salons & Spas** – Manage bookings and FAQs  
  Clinics & Health Services** – Automated scheduling + patient info  
  Agencies & Consultants** – Answer inquiries + schedule meetings  
  Any Service Business** – Save time, improve customer experience  

nodes_used:
  ["@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleSheetsTool","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent"]

workflow_json_compressed:
  [encoded data, 4560 characters]

metadata_json:
  {"categories":["automation","integration","customer_support","scheduling","AI"],"complexity":"medium","use_cases":["Automated appointment booking and scheduling","Customer-facing virtual receptionist for FAQs and business info","Calendar availability checks and conflict resolution","Lead capture and customer data logging","Multi-turn conversational booking with context/memory"],"estimated_setup_minutes":30,"required_services":["Google Calendar (Google Workspace account/API)","Google Sheets (Google Workspace account/API)","AI provider (e.g., OpenAI, Anthropic, or other LLM API)"],"key_features":["Natural-language chat interface for clients","Checks Google Calendar availability and creates events","Saves customer details and bookings to Google Sheets","Structured output parsing for reliable data extraction","Memory buffer for multi-turn conversations/context retention"],"target_audience":["Small business owners (salons, clinics, consultants)","Agencies and service providers","Customer support and front-desk teams"]}


name: Automated Forex News Alert System with Forex Factory and Telegram
author_name: Harry Gunadi Permana
author_username: harrygp
categories: []
created_at: 2025-09-07T00:46:26.621Z
updated_at: 2025-09-07T00:46:26.621Z
url: https://n8n.io/workflows/8340
scraped_at: 2025-09-29 22:37:33
metadata_generated_at: 2025-09-30 08:33:37
description:
  Get Forex Factory News Release to Telegram
  This n8n template demonstrates how to capture Actual Data Releases as quickly as possible for trading decisions.

  Use cases:
  Get notified if the actual data release is positive or negative for the relevant currency.
  Use the Telegram chat message about the news release as a trigger to open a trading position in MetaTrader 4.

  How it works
  A news release event acts as the trigger.
  Only news with a numerical Forecast value will be processed. Events that cannot be measured numerically (e.g., speeches) are ignored.
  Extract news details: currency, impact level (high/medium), release date, and news link.
  Wait 10 seconds to ensure the Actual value is available on the news page.
  Scrape the Actual value from the news link using Airtop.
  If the Actual value is not available, wait another 5 seconds and retry scraping.
  Extract both Actual and Forecast values from the scraped content.
  Remove non-numeric characters (%, K, M, B, T) and convert values to numbers.
  Determine the effect:
  If the Actual value is lower than the Forecast value (and lower is better), send it to the True branch.
  Otherwise, send it to the False branch.

  How to use
  Enter all required credentials.
  Run the workflow.

  Requirements
  Google Calendar credentials
  Airtop API key
  Telegram Chat ID
  Telegram Bot API token

  Need Help?
  Join the Discord or ask in the Forum!

  Thank you!

  Update Sept 26, 2025:
  Add new edit node

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.googleCalendarTrigger","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.airtop","n8n-nodes-base.wait","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.set","n8n-nodes-base.noOp"]

workflow_json_compressed:
  [encoded data, 6596 characters]

metadata_json:
  {"categories":["automation","trading","integration","notifications"],"complexity":"medium","use_cases":["Real-time alerts for forex economic data releases","Notify if actual release is positive or negative for the currency","Trigger opening/closing of trading positions (e.g., via Telegram to MetaTrader 4)","Filter and process only events with numeric forecast values","Log or schedule alerts in Google Calendar"],"estimated_setup_minutes":30,"required_services":["Forex Factory (RSS/API or data feed)","Telegram (bot/chat)","MetaTrader 4 or trade execution endpoint (optional)","AI/ML service or n8n AI node for classification","Google Calendar (optional)"],"key_features":["Capture economic news releases as they occur","Process only events with numeric forecast values","Classify release impact (positive/negative) using AI/ML logic","Send instant Telegram alerts with structured message","Use Telegram message as a trigger to open trades in MT4 or other execution systems','Optional calendar logging/scheduling of events"],"target_audience":["Forex traders","Algorithmic trading developers","Quant analysts and trading desks looking for event-driven signals"]}


name: Generate AI Reports for Meta Ads Campaigns with Claude & Pipeboard MCP via Slack
author_name: Yves Junqueira
author_username: yves-pipeboard
categories: []
created_at: 2025-09-09T13:39:33.598Z
updated_at: 2025-09-09T13:39:33.598Z
url: https://n8n.io/workflows/8414
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Who's it for
  Digital marketing agencies and Meta Ads managers who need to generate comprehensive performance reports across multiple client accounts automatically. Perfect for agencies handling 5+ Meta Ads accounts who want to save hours on manual reporting while delivering AI-powered insights to their teams.

  What it does
  Pulls performance data from multiple Meta Ads accounts for a specified time period (last 7, 14, or 30 days)
  Uses Claude AI with Pipeboard's Meta Ads MCP to analyze campaign performance, identify trends, and generate actionable insights
  Generates professional reports with AI-driven recommendations for optimization
  Automatically delivers formatted reports to your Slack channels
  Runs on a schedule (weekly/daily) or triggered manually

  How to set up

  Set up Claude AI integration (requires Anthropic API key)
  Configure Pipeboard's Meta Ads MCP connection
  Connect Slack to n8n via OAuth2
  Create a list of client account IDs in the workflow configuration
  Customize your reporting template and Slack delivery settings

  Requirements
  n8n version 1.109.2 or newer.
  Claude AI API access (Anthropic)
  Pipeboard account
  Slack workspace access

  How to customize the workflow

  Adjust the date range and metrics to track
  Modify the AI prompts for different types of insights
  Configure multiple Slack channels for different clients
  Set up custom scheduling intervals
  Add email delivery as an additional output channel

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatAnthropic","n8n-nodes-base.splitOut","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.mcpClientTool","n8n-nodes-base.slack","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","marketing","reporting","ai","integration"],"complexity":"medium","use_cases":["Automated multi-account Meta Ads reporting","AI-powered campaign performance analysis and insights","Scheduled delivery of performance reports to Slack","Consolidated client reporting for digital agencies","Time-window comparisons (last 7, 14, or 30 days)"],"estimated_setup_minutes":45,"required_services":["Meta Ads API (Facebook/Meta Ads)","Anthropic Claude (lmChatAnthropic)","Pipeboard MCP","Slack"],"key_features":["Aggregates performance data across multiple Meta Ads accounts","Selectable reporting windows (7 / 14 / 30 days)","AI analysis using Claude via Pipeboard MCP","Scheduled automation for periodic reports","Delivers AI-crafted reports to Slack channels/users"],"target_audience":["digital marketing agencies","Meta Ads managers","performance analysts / data analysts for advertising accounts"]}


name: Automated Range Trading with Uniswap V3, Telegram Alerts & MetaMask Delegation
author_name: 1Shot API
author_username: oneshotapi
categories: []
created_at: 2025-09-09T18:08:54.617Z
updated_at: 2025-09-09T18:08:54.617Z
url: https://n8n.io/workflows/8427
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Simple Range Trading w/ Uniswap V3

  This workflow will monitor the price of a token trading pair (default is ETH - USDC) and automatically buy into ETH or sell into USDC based on a price window configured by the user. 

  Additionally, the workflow will notify the user on Telegram before a trade is executed, giving the user 1 minute to cancel the trade before the workflow proceeds. 

  Transaction are executed via MetaMask's Delegation Framework, so trades are fully non-custodial, you retain full control of your assets at all times. 

  Check out the YouTube tutorial for a full walkthrough.

  Maintain Complete Trading Control with MetaMask Delegations

  With the MetaMask Delegation Framework, you never relinquish control of your funds to any 3rd party, not even 1Shot API. Furthermore, with this workflow, you have full control of your trading parameters and the assets you trade against. Lastly, by running your own trading setup, you can bypass fees incurred through centralized exchanges or hosted frontends that reduce your profitability. 

  Human-in-the-Loop with Telegram Notifiactions

  This workflow uses Telegram to send you real-time updates on whats happening with your trades. Specifically, the Telegram human-in-the-loop node is used to give you a change to cancel trades before they happen or immediately approve them. 

  Setup

  Create a free 1Shot API account, and create an API key.
  Import the workflow into your n8n portal.
  Create a credential for the 1Shot API nodes to communicate with your 1Shot API account.
  Trigger the sub-workflow to generate an Arbitrum server wallet and import all required smart contract methods. 
  Point the 1Shot API nodes at the appropriate smart contract methods in you 1Shot API account.
  Create a Telegram credential for notifications & input the chatID of your Telegram bot.
  Set your desired trading price range in the Swap Configs node.
  Start your trading workflow.

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  {"categories":["automation","trading","blockchain","notifications","DeFi"],"complexity":"complex","use_cases":["Automated range trading on Uniswap V3","Price monitoring and threshold-based execution","Non-custodial trade execution via MetaMask delegation","Pre-trade alerts with cancellation window","Integrating Telegram notifications into trading workflows"],"estimated_setup_minutes":45,"required_services":["Uniswap V3 (Ethereum)","MetaMask + MetaMask Delegation Framework","Telegram Bot API","Ethereum RPC/provider (Infura, Alchemy, or similar)","Ethers.js or web3-compatible library","A funded wallet on the target network (ETH/USDC)"],"key_features":["Monitors token pair price (default ETH–USDC)","Automated buy/sell when price exits/enters configured window","Pre-trade Telegram notification giving 1-minute cancel option","Transactions executed non-custodially via MetaMask Delegation","Configurable token pair and price window settings"],"target_audience":["DeFi traders","Crypto developers/engineers","Algorithmic trading hobbyists/enthusiasts who prefer non-custodial flows"]}


name: Create Viral Ads with AI: NanoBanana & publish on socials via upload-post
author_name: Dr. Firas
author_username: drfiras
categories: []
created_at: 2025-09-09T18:30:50.820Z
updated_at: 2025-09-09T18:30:50.820Z
url: https://n8n.io/workflows/8428
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  💥 Create viral Ads with NanoBanana & Seedance, publish on socials via upload-post

  Who is this for?  
  This workflow is designed for marketers, content creators, and small businesses who want to automate the creation of engaging social media ads without spending hours on manual design, video editing, or publishing.

  What problem is this workflow solving? / Use case  
  Manually creating ads for multiple platforms is time-consuming and repetitive. You need to generate visuals, edit videos, add music, and then publish them across social channels.  
  This workflow automates the end-to-end ad production pipeline, saving time while ensuring consistent, professional-quality output.

  What this workflow does  
  Receives ad ideas via Telegram.  
  Uses NanoBanana to generate and edit realistic product images.  
  Transforms images into engaging short videos with Seedance.  
  Generates background music with Suno.  
  Merges video and audio into a polished final ad.  
  Reads brand info and generates ad copy with AI (OpenAI).  
  Publishes ads to Instagram, TikTok, YouTube, Facebook, and X via upload-post.  
  Stores media and campaign data in Google Drive and Google Sheets for tracking.  
  Sends back notifications and previews via Telegram.

  Setup  
  Connect your accounts:  
     Telegram  
     Google Drive  
     Google Sheets  
     OpenAI API  
     NanoBanana API  
     Seedance API  
     Suno API  
     Upload-post  

  Prepare Google Sheets:  
     Add a sheet for brand details (name, category, features, website).  
     Add another sheet for video logs (status, links, captions).  

  Configure upload-post:  
     Ensure your social accounts (TikTok, Instagram, YouTube, Facebook, X) are linked to upload-post.  

  How to customize this workflow to your needs  
  Prompts* → Adjust the *image/video/music prompts** to better reflect your brand’s tone and products.  
  Ad copy* → Modify the AI prompt inside the *Ads Copywriter Generator** to control wording, style, and structure.  
  Publishing scope* → Choose only the platforms you want (TikTok, Instagram, etc.) inside the *upload-post** node.  
  Storage** → Update Google Drive folder IDs and Google Sheets document IDs to match your own workspace.  

  👉 With this template, you get a fully automated viral ad production system powered by AI visuals, video rendering, and auto-publishing across social platforms. Perfect for scaling your content strategy while saving time.


  📄 Documentation: Notion Guide

  Demo Video

  🎥 Watch the full tutorial here: YouTube Demo
  Need help customizing?
  Contact me for consulting and support : Linkedin / Youtube

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name: Monitor Social Media Trends Across Reddit, Instagram & TikTok with Apify
author_name: Growth AI
author_username: growthai
categories: []
created_at: 2025-09-10T13:44:08.027Z
updated_at: 2025-09-10T13:44:08.027Z
url: https://n8n.io/workflows/8450
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Who's it for
  Social media managers, content creators, brand managers, and marketing teams who need to track keyword performance and trending content across TikTok, Instagram, and Reddit for competitive analysis and content inspiration.
  What it does
  This workflow automatically monitors trending content across three major social media platforms using specified keywords. It scrapes posts from TikTok, Instagram, and Reddit, calculates engagement scores using platform-specific metrics, ranks content by performance, and generates a comprehensive HTML email report with the top-performing posts across all platforms.
  How it works
  The workflow follows a sequential multi-platform scraping process:

  Reddit Scraping: Searches for keyword-based posts and comments with engagement metrics
  Instagram Monitoring: Analyzes hashtag-based content with likes and comments data
  TikTok Analysis: Tracks hashtag performance including views, likes, shares, and comments
  Score Calculation: Applies platform-specific scoring algorithms based on engagement metrics
  Unified Ranking: Combines and ranks all content across platforms by engagement score
  Report Generation: Creates a detailed HTML email report with top performers and analytics

  Requirements

  Apify account with API access
  Gmail account for report delivery
  Platform-specific scrapers: Reddit Scraper Lite, Instagram Scraper, TikTok Scraper

  How to set up
  Step 1: Configure Apify credentials

  Set up Apify HTTP header authentication in n8n
  Ensure access to the required scrapers:

  Reddit: trudax~reddit-scraper-lite
  Instagram: apify~instagram-scraper
  TikTok: clockworks~tiktok-scraper

  Step 2: Customize search parameters
  Reddit configuration:

  Search terms: Modify "searches" array with your keywords
  Content type: Posts and comments (searchComments can be enabled)
  Sort method: "top" (alternatives: hot, new, relevance)
  Time period: "month" (alternatives: hour, day, week, year, all)
  Result limits: maxItems: 50, maxPostCount: 25

  Instagram configuration:

  Hashtag URLs: Update directUrls with target hashtags
  Results type: "posts" (alternatives: stories, reels)
  Time filter: "onlyPostsNewerThan": "7 days"
  Result limit: resultsLimit: 15

  TikTok configuration:

  Hashtags: Update hashtags array with target keywords
  Results per page: resultsPerPage: 20
  Time filter: "oldestPostDateUnified": "7 days"

  Step 3: Set up email reporting

  Configure Gmail OAuth2 credentials
  Update recipient email address in "Send a message" node
  Customize email subject and styling as needed

  Step 4: Adjust scoring algorithms
  Current scoring formulas:

  Reddit: (upvotes × 1) + (comments × 2)
  Instagram: (likes × 1) + (comments × 2)
  TikTok: (likes × 1) + (comments × 2) + (shares × 3) + (views ÷ 1000)

  Modify the code nodes to adjust scoring based on your priorities.
  How to customize the workflow
  Keyword and hashtag targeting

  Multiple keywords: Add arrays of search terms for broader monitoring
  Brand-specific terms: Include brand names, product names, competitor analysis
  Seasonal tracking: Adjust keywords based on campaigns or seasonal trends
  Negative filtering: Exclude irrelevant content with filtering logic

  Platform-specific customization
  Reddit enhancements:

  Subreddit targeting: Focus on specific communities
  Comment analysis: Enable comment scraping for deeper insights
  User profiling: Track specific user activity and influence

  Instagram modifications:

  Story monitoring: Track story mentions and hashtag usage
  Influencer tracking: Monitor specific account performance
  Location-based: Add geo-targeted hashtag monitoring

  TikTok optimizations:

  Trend detection: Identify viral sounds and effects
  Creator analysis: Track trending creators in your niche
  Challenge monitoring: Follow hashtag challenge performance

  Scoring and ranking customization

  Weighted metrics: Adjust multipliers based on platform importance
  Recency factors: Give bonus points to newer content
  Quality filters: Exclude low-engagement or spam content
  Sentiment analysis: Integrate sentiment scoring for brand monitoring

  Reporting enhancements

  Multiple recipients: Send reports to different team members
  Scheduled execution: Add scheduling triggers for automated monitoring
  Data export: Save results to spreadsheets or databases
  Alert thresholds: Set up notifications for high-performing content

  Engagement scoring methodology
  Platform-specific algorithms
  Reddit scoring logic:

  Emphasizes community engagement through upvotes and discussion
  Comments weighted higher (×2) as they indicate deeper engagement
  Filters out low-quality posts and spam content

  Instagram scoring approach:

  Balances visual appeal (likes) with engagement depth (comments)
  Focuses on recent content to capture trending moments
  Excludes carousel sub-items to avoid duplicate counting

  TikTok scoring system:

  Multi-factor algorithm considering all engagement types
  Views normalized (÷1000) to balance with other metrics
  Shares heavily weighted (×3) as they indicate viral potential

  Level classification
  Content automatically categorized into performance tiers:

  High: Score ≥ 10,000 (viral or highly engaging content)
  Medium: Score ≥ 1,000 (good engagement, worth monitoring)
  Low: Score &lt; 1,000 (baseline engagement)

  Results interpretation
  Comprehensive analytics dashboard
  The email report includes:

  Cross-platform leaderboard: Top 15 posts ranked by engagement score
  Platform breakdown: Performance summary by social network
  Engagement metrics: Detailed scoring and classification
  Direct links: Clickable access to original content
  Author tracking: Creator identification for influencer outreach

  Actionable insights

  Content inspiration: Identify high-performing content formats and topics
  Competitor analysis: Monitor competitor content performance
  Trend identification: Spot emerging topics before they peak
  Influencer discovery: Find creators driving engagement in your niche

  Use cases
  Brand monitoring and competitive analysis

  Brand mention tracking: Monitor how your brand performs across platforms
  Competitor surveillance: Track competitor content and engagement rates
  Crisis management: Early detection of negative sentiment or issues
  Market positioning: Understand your brand's social media presence

  Content strategy optimization

  Content format analysis: Identify which content types perform best
  Hashtag research: Discover effective hashtags for your niche
  Posting timing: Analyze when high-engagement content is published
  Trend forecasting: Spot emerging trends for proactive content creation

  Influencer and partnership identification

  Creator discovery: Find influential voices in your industry
  Partnership evaluation: Assess potential collaborator engagement rates
  Campaign performance: Track sponsored content and brand partnerships
  Community building: Identify active community members and advocates

  Workflow limitations

  API rate limiting: Subject to Apify scraper limitations and quotas
  Platform restrictions: Some content may be private or restricted
  Real-time delays: 30-second waits between platform scraping prevent rate limiting
  Manual execution: Currently triggered manually (easily schedulable)
  Single keyword focus: Current setup optimized for one keyword at a time
  Platform availability: Dependent on third-party scrapers and their maintenance

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metadata_json:
  {"categories":["automation","social media monitoring","data processing","integration","analytics"],"complexity":"complex","use_cases":["Track keyword performance across TikTok, Instagram, and Reddit","Identify trending posts for content inspiration","Competitive social listening and brand monitoring","Rank and surface high-engagement content for curation","Automate scheduled monitoring and alerting of trends"],"estimated_setup_minutes":60,"required_services":["Apify (scrapers/actors)","TikTok (API or scraping endpoints)","Instagram (API or scraping endpoints)","Reddit API or scraper","AI/ML provider for scoring/insights (e.g., OpenAI or similar)","Notification channel(s) (Slack/email/webhook)","Optional: proxy provider for scraping"],"key_features":["Cross-platform scraping of TikTok, Instagram, and Reddit via Apify","Keyword-based monitoring to capture relevant posts","Platform-specific engagement score calculation","Ranking and sorting of trending content","Scheduled runs and webhook/HTTP integrations for automation/notifications"],"target_audience":["Social media managers","Content creators","Brand managers and marketing teams"]}


name: Automated News Monitoring with Claude 4 AI Analysis for Discord & Google News
author_name: Growth AI
author_username: growthai
categories: []
created_at: 2025-09-10T14:24:51.234Z
updated_at: 2025-09-10T14:24:51.234Z
url: https://n8n.io/workflows/8452
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Who's it for
  Marketing teams, business intelligence professionals, competitive analysts, and executives who need consistent industry monitoring with AI-powered analysis and automated team distribution via Discord.
  What it does
  This intelligent workflow automatically monitors multiple industry topics, scrapes and analyzes relevant news articles using Claude AI, and delivers professionally formatted intelligence reports to your Discord channel. The system provides weekly automated monitoring cycles with personalized bot communication and comprehensive content analysis.
  How it works
  The workflow follows a sophisticated 7-phase automation process:
  Scheduled Activation: Triggers weekly monitoring cycles (default: Mondays at 9 AM)
  Query Management: Retrieves monitoring topics from centralized Google Sheets configuration
  News Discovery: Executes comprehensive Google News searches using SerpAPI for each configured topic
  Content Extraction: Scrapes full article content from top 3 sources per topic using Firecrawl
  AI Analysis: Processes scraped content using Claude 4 Sonnet for intelligent synthesis and formatting
  Discord Optimization: Automatically segments content to comply with Discord's 2000-character message limits
  Automated Delivery: Posts formatted intelligence reports to Discord channel with branded "Claptrap" bot personality
  Requirements

  Google Sheets account for query management
  SerpAPI account for Google News access
  Firecrawl account for article content extraction
  Anthropic API access for Claude 4 Sonnet
  Discord bot with proper channel permissions
  Scheduled execution capability (cron-based trigger)

  How to set up
  Step 1: Configure Google Sheets query management
  Create monitoring sheet: Set up Google Sheets document with "Query" sheet
  Add search topics: Include industry keywords, competitor names, and relevant search terms
  Sheet structure: Simple column format with "Query" header containing search terms
  Access permissions: Ensure n8n has read access to the Google Sheets document
  Step 2: Configure API credentials
  Set up the following credentials in n8n:
  Google Sheets OAuth2: For accessing query configuration sheet
  SerpAPI: For Google News search functionality with proper rate limits
  Firecrawl API: For reliable article content extraction across various websites
  Anthropic API: For Claude 4 Sonnet access with sufficient token limits
  Discord Bot API: With message posting permissions in target channel
  Step 3: Customize scheduling settings
  Cron expression: Default set to "0 9 * * 1" (Mondays at 9 AM)
  Frequency options: Adjust for daily, weekly, or custom monitoring cycles
  Timezone considerations: Configure according to team's working hours
  Execution timing: Ensure adequate processing time for multiple topics
  Step 4: Configure Discord integration
  Set up Discord delivery settings:
  Guild ID: Target Discord server (currently: 919951151888236595)
  Channel ID: Specific monitoring channel (currently: 1334455789284364309)
  Bot permissions: Message posting, embed suppression capabilities
  Brand personality: Customize "Claptrap" bot messaging style and tone
  Step 5: Customize content analysis
  Configure AI analysis parameters:
  Analysis depth: Currently processes top 3 articles per topic
  Content format: Structured markdown format with consistent styling
  Language settings: Currently configured for French output (easily customizable)
  Quality controls: Error handling for inaccessible articles and content
  How to customize the workflow
  Query management expansion
  Topic categories: Organize queries by industry, competitor, or strategic focus areas
  Keyword optimization: Refine search terms based on result quality and relevance
  Dynamic queries: Implement time-based or event-triggered query modifications
  Multi-language support: Add international keyword variations for global monitoring
  Advanced content processing
  Article quantity: Modify from 3 to more articles per topic based on analysis needs
  Content filtering: Add quality scoring and relevance filtering for article selection
  Source preferences: Implement preferred publisher lists or source quality weighting
  Content enrichment: Add sentiment analysis, trend identification, or competitive positioning
  Discord delivery enhancements
  Rich formatting: Implement Discord embeds, reactions, or interactive elements
  Multi-channel distribution: Route different topics to specialized Discord channels
  Alert levels: Add priority-based messaging for urgent industry developments
  Archive functionality: Create searchable message threads or database storage
  Integration expansions
  Slack compatibility: Replace or supplement Discord with Slack notifications
  Email reports: Add formatted email distribution for executive summaries
  Database storage: Implement persistent storage for historical analysis and trending
  API endpoints: Create webhook endpoints for third-party system integration
  AI analysis customization
  Analysis templates: Create topic-specific analysis frameworks and formatting
  Competitive focus: Enhance competitor mention detection and analysis depth
  Trend identification: Implement cross-topic trend analysis and strategic insights
  Summary levels: Create executive summaries alongside detailed technical analysis
  Advanced monitoring features
  Intelligent content curation
  The system provides sophisticated content management:
  Relevance scoring: Automatic ranking of articles by topic relevance and publication authority
  Duplicate detection: Prevents redundant coverage of the same story across different sources
  Content quality assessment: Filters low-quality or promotional content automatically
  Source diversity: Ensures coverage from multiple perspectives and publication types
  Error handling and reliability
  Graceful degradation: Continues processing even if individual articles fail to scrape
  Retry mechanisms: Automatic retry logic for temporary API failures or network issues
  Content fallbacks: Uses article snippets when full content extraction fails
  Notification continuity: Ensures Discord delivery even with partial content processing
  Results interpretation
  Intelligence report structure
  Each monitoring cycle delivers:
  Topic-specific summaries: Individual analysis for each configured search query
  Source attribution: Complete citation with publication date, source, and URL
  Structured formatting: Consistent presentation optimized for quick scanning
  Professional analysis: AI-generated insights maintaining factual accuracy and business context
  Performance analytics
  Monitor system effectiveness through:
  Processing metrics: Track successful article extraction and analysis rates
  Content quality: Assess relevance and usefulness of delivered intelligence
  Team engagement: Monitor Discord channel activity and report utilization
  System reliability: Track execution success rates and error patterns
  Use cases
  Competitive intelligence
  Market monitoring: Track competitor announcements, product launches, and strategic moves
  Industry trends: Identify emerging technologies, regulatory changes, and market shifts
  Partnership tracking: Monitor alliance formations, acquisitions, and strategic partnerships
  Leadership changes: Track executive movements and organizational restructuring
  Strategic planning support
  Market research: Continuous intelligence gathering for strategic decision-making
  Risk assessment: Early warning system for industry disruptions and regulatory changes
  Opportunity identification: Spot emerging markets, technologies, and business opportunities
  Brand monitoring: Track industry perception and competitive positioning
  Team collaboration enhancement
  Knowledge sharing: Centralized distribution of relevant industry intelligence
  Discussion facilitation: Provide common information baseline for strategic discussions
  Decision support: Deliver timely intelligence for business planning and strategy sessions
  Competitive awareness: Keep teams informed about competitive landscape changes
  Workflow limitations
  Language dependency: Currently optimized for French analysis output (easily customizable)
  Processing capacity: Limited to 3 articles per query (configurable based on API limits)
  Platform specificity: Configured for Discord delivery (adaptable to other platforms)
  Scheduling constraints: Fixed weekly schedule (customizable via cron expressions)
  Content access: Dependent on article accessibility and website compatibility with Firecrawl
  API dependencies: Requires active subscriptions and proper rate limit management for all integrated services

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name: Track Forex Factory News Releases with MyFxBook, Telegram & Google Sheets
author_name: Harry Gunadi Permana
author_username: harrygp
categories: []
created_at: 2025-09-12T02:45:00.415Z
updated_at: 2025-09-12T02:45:00.415Z
url: https://n8n.io/workflows/8491
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Get Forex Factory News Release to Telegram, Google Sheets. Record News Data and Live Price from MyFxBook for Affected Currency Pairs.
  This n8n template demonstrates how to capture Actual Data Releases as quickly as possible for trading decisions.

  Use cases:
  Get notified if the actual data release is positive or negative for the relevant currency.
  Use the Telegram chat message about the news release as a trigger to open a trading position in MetaTrader 4.
  Record news data and live price to google sheets for analysis.

  Currency Pairs
  EURUSD, GBPUSD, AUDUSD, NZDUSD, USDJPY, USDCHF, USDCAD, XAUUSD

  How it works
  A news release event acts as the trigger.
  Only news with a numerical Forecast value will be processed. Events that cannot be measured numerically (e.g., speeches) are ignored.
  Extract news details: currency, impact level (high/medium), release date, and news link.
  Wait 10 seconds to ensure the Actual value is available on the news page.
  Scrape the Actual value from the news link using Airtop.
  If the Actual value is not available, wait another 5 seconds and retry scraping.
  Extract both Actual and Forecast values from the scraped content.
  Remove non-numeric characters (%, K, M, B, T) and convert values to numbers.
  Determine the effect:
  If the Actual value is lower than the Forecast value (and lower is better), send it to the True branch.
  Otherwise, send it to the False branch.
  Record news data and live price from MyFxBook to Google Sheets.

  How to use
  Enter all required credentials.
  Create or Download Google Sheets file like this in your Google Drive: https://docs.google.com/spreadsheets/d/1OhrbUQEc_lGegk5pRWWKz5nrnMbTZGT0lxK9aJqqId4/edit?usp=drive_link
  Run the workflow.

  Requirements
  Google Calendar credentials
  Airtop API key
  Telegram Chat ID
  Telegram Bot API token
  Enable Google Drive API in Google Cloud Console
  Google Sheets credentials

  Need Help?
  Join the Discord or ask in the Forum!

  Thank you!

  Update Sept 26, 2025:
  Add new edit node

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metadata_json:
  {"categories":["automation","integration","trading","data-collection"],"complexity":"complex","use_cases":["Real-time alerts on economic data releases that impact currency pairs","Trigger trading actions (e.g., open positions) from Telegram alerts","Record news release details and live prices for audit/backtesting","Monitor multiple currency pairs and their live prices around news events","Log news events to calendar and spreadsheets for reporting"],"estimated_setup_minutes":45,"required_services":["Forex Factory (news feed)","MyFxBook (live price API)","Telegram","Google Sheets","Google Calendar (optional)","MetaTrader 4 (optional for trade execution)","n8n AI/ML or external parsing services (optional)","HTTP/Webhooks endpoints/APIs"],"key_features":["Capture Actual data releases rapidly from Forex Factory","Fetch live price data from MyFxBook for affected currency pairs","Send conditional Telegram alerts (positive/negative impact)","Record news data and live prices to Google Sheets","Use conditional logic to decide alerting and downstream actions (if nodes)」「Use AI/ML nodes for parsing/classification of releases」「Trigger workflows from Telegram messages or webhooks to integrate with trading systems (MT4)」「Log events to Google Calendar and sticky notes for context"],"target_audience":["Forex traders","Algorithmic traders / quant traders","Trading analysts and researchers」「DevOps/Automation engineers managing trading workflows"]}


name: Jarvis: Productivity AI Agent for Tasks, Calendar, Email & Expense using MCPs
author_name: Jitesh Dugar
author_username: jiteshdugar
categories: []
created_at: 2025-09-12T06:41:03.347Z
updated_at: 2025-09-12T06:41:03.347Z
url: https://n8n.io/workflows/8500
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-30 08:33:37
description:
  Who’s it for
  This template is designed for anyone who wants to use Telegram as a personal AI assistant hub.  
  If you often juggle tasks, emails, calendars, and expenses across multiple tools, this workflow consolidates everything into one seamless AI-powered agent.

  What it does
  Jarvis listens to your Telegram messages (text or audio) and processes them with OpenAI.  
  Based on your request, it can:
  ✅ Manage tasks (create, complete, or delete)  
  📅 Handle calendar events (schedule, reschedule, or check availability)  
  📧 Send, draft, or fetch emails with Gmail  
  👥 Retrieve Google Contacts  
  💵 Log and track expenses  

  All responses are returned directly to Telegram, giving you a unified command center.

  How to set up
  Clone this template into your n8n workspace.  
  Connect your accounts (Telegram, Gmail, Google Calendar, Contacts, etc.).  
  Add your OpenAI API key in the Credentials section.  
  Test by sending a Telegram message like “Create a meeting tomorrow at 3pm” or “Add expense $50 for lunch.”  or "Draft a reply with a project proposal to that email from Steve"

  Requirements
  n8n instance (cloud or self-hosted)  
  Telegram Bot API credentials  
  Gmail, Google Calendar, and Google Contacts credentials (optional, if using those features)  
  OpenAI API key  
  ElevenLabs API Key (optional, if you need audio note support)

  How to customize
  Swap Gmail with another email provider by replacing the Gmail MCP node.  
  Add additional MCP integrations (e.g., Notion, Slack, CRM tools).  
  Adjust memory length to control how much context Jarvis remembers.  

  With this template, you can transform Telegram into your all-in-one AI assistant, simplifying workflows and saving hours every week.

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name: Nano Banana AI Product Image Creator via WhatsApp
author_name: Roshan Ramani
author_username: rawsun007
categories: []
created_at: 2025-09-13T07:15:44.824Z
updated_at: 2025-09-13T07:15:44.824Z
url: https://n8n.io/workflows/8549
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Nano Banana AI Product Image Creator via WhatsApp

  Transform ordinary product photos into premium marketing visuals instantly using Gemini AI for prompt enhancement and Nano Banana AI for image generation through WhatsApp.

  Who's it for
  Small business owners
  E-commerce sellers
  Social media managers
  Anyone selling products online

  What it does
  • Takes your normal product photo
  • Gets your text/caption as input
  • Gemini AI improves your basic prompt into professional instructions
  • Nano Banana AI generates new premium ad image using enhanced prompt
  • Keeps your original product exactly the same
  • Returns social media-ready marketing image

  Key Benefits
  Smart Prompt Enhancement - Gemini AI makes your simple text into professional prompts  
  Superior Image Generation - Nano Banana AI creates premium visuals
  Original Product Protected - Your product stays 100% unchanged  
  Fast Results - Get enhanced image in under 60 seconds  
  Easy to Use - Just send photo via WhatsApp  
  Social Media Ready - Perfect for Instagram, Facebook, ads  

  How it works
  Send Photo + Caption → Upload product image with your text
  AI Prompt Magic → Gemini AI turns your caption into professional prompt
  Image Generation → Nano Banana AI creates new premium ad using improved prompt
  Receive Result → Get marketing-ready image back instantly

  The Magic Process
  Your Input: "Make this look premium for Instagram"  
  Gemini AI Enhanced Prompt: "Create luxury product advertisement with professional studio lighting, marble background, elegant typography, commercial photography style, high-end visual appeal..."  
  Nano Banana AI Generated Result: Professional marketing image created with your improved prompt

  What you get
  • Better Prompts - Gemini AI turns simple text into detailed instructions
  • Professional Images - Studio-quality marketing visuals generated by Nano Banana AI
  • Same Product - Your original item stays unchanged
  • Quick Results - Ready in under 60 seconds

  Perfect for
  Instagram posts
  Facebook ads  
  Online store images
  Social media marketing

  Why This Combo Works Best
  Gemini AI** - Expert at understanding and enhancing text prompts
  Nano Banana AI** - Specialized for high-quality product image generation
  Best of Both** - Combines prompt expertise with image generation power
  Faster Results** - Optimized dual-AI workflow

  Perfect solution for creating professional product ads from simple WhatsApp messages using the power of both Gemini AI and Nano Banana AI.

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name: AI Shopify Product Descriptions: GPT-4o Vision + Claude + Analytics
author_name: Kumar Shivam
author_username: shivam840708
categories: []
created_at: 2025-09-13T20:07:15.240Z
updated_at: 2025-09-13T20:07:15.240Z
url: https://n8n.io/workflows/8562
scraped_at: 2025-09-29 22:37:32
metadata_generated_at: 2025-09-30 08:33:37
description:
  Complete AI Product Description Generator
  Transforms product images into high-converting copy with GPT-4o Vision + Claude 3.5
  The Shopify AI Product Description Factory is a production-grade n8n workflow that converts product images and metadata into refined, SEO-aware descriptions—fully automated and region-agnostic. It blends GPT-4o vision for visible attribute extraction, Claude 3.5 Sonnet for premium copy, Perplexity research for verified brand context, Google Sheets for orchestration and audit trails, plus automated daily sales analytics enrichment. Link-header pagination and structured output enforcement ensure reliable scale.



  To refine according to your usecase connect via my profile
  @connect

  Key Advantages

  Vision-first copywriting
  Uses gpt-4o to identify only visible physical attributes (closure, heel, materials, sole) from product images—no guesses.

  Premium copy generation
  anthropic/claude-3.5-sonnet crafts concise, benefit-led descriptions with consistent tone, length control, and clean formatting.

  Research-assisted accuracy
  perplexityTool verifies vendor/brand context from official sources to avoid speculation or fabricated claims.

  Pagination you can trust
  Automates Shopify REST pagination via Link headers and persists page_info for resumable runs.

  Google Sheets orchestration
  Centralized staging, status tracking, and QA in Products, with ProcessingState for batch/page markers, and Error_log for diagnostics.

  Bulletproof error feedback
  errorTrigger + AI diagnosis logs clear, non-technical and technical explanations to Error_log for fast recovery.

  Automated sales analytics
  Daily sales tracking automatically captures and enriches total sales data for comprehensive business intelligence and performance monitoring.

  How It Works

  Intake and filtering
  httpRequest fetches /admin/api/2024-04/products.json?limit=200&{page_info}
  code filters only items with:
    Image present
    Empty body_html
    The currSeas:SS2025 tag
  Extracts tag metadata such as x-styleCode, country_of_origin, and gender when available

  Pagination controller
  code parses Link headers for rel="next" and extracts page_info
  googleSheets updates ProcessingState with page_info_next and increments the batch number for resumable polling

  Generation pipeline
  googleSheets pulls rows with Status = Ready for AI Description; limit throttles batch size
  openAi Analyze image (model gpt-4o) returns strictly visible features
  lmChatOpenRouter (Claude 3.5) composes the SEO description, optionally blending verified vendor context from perplexityTool
  outputParserStructured guarantees strict JSON: product_id, product_title (normalized), generated_description, status
  googleSheets writes results back to Products for review/publish

  Sales analytics enrichment
  Schedule Trigger** runs daily at 2:01 PM to capture previous day's sales
  httpRequest fetches paid orders from Shopify REST API with date range filtering
  splitOut and summarize nodes calculate total daily sales
  Automatic Google Sheets logging with date stamps and totals
  Zero-sale days are properly recorded for complete analytics continuity

  Reliability and insight
  errorTrigger routes failures to an AI agent that explains the root cause and appends a concise note to Error_log.

  What's Inside (Node Map)

  Data + API
  httpRequest (Shopify REST 2024-04 for products and orders)
  googleSheets (multiple sheet operations)
  googleSheetsTool (error logging)

  AI models
  openAi (gpt-4o vision analysis)
  lmChatOpenRouter (anthropic/claude-3.5-sonnet for content generation)
  AI Agent** (intelligent error diagnosis)

  Analytics & Processing
  splitOut (order data processing)
  summarize (sales totals calculation)
  set nodes (data field mapping)

  Tools and guards
  perplexityTool (brand research)
  outputParserStructured (JSON validation)
  memoryBufferWindow (conversation context)

  Control & Scheduling
  scheduleTrigger (multiple time-based triggers)
  cron (periodic execution)
  limit (batch size control)
  if (conditional logic)
  code (custom filtering and pagination logic)

  Observability
  errorTrigger + AI diagnosis to Error_log
  Processing state tracking
  Sales analytics logging

  Content & Compliance Rules

  Locale-agnostic copy**; brand voice is configurable per store
  Only image-verifiable attributes** (no guesses); clean HTML suitable for Shopify themes
  Optional normalization rules (e.g., color/branding cleanup, title sanitization)
  Style code inclusion supported when x-styleCode is present
  Gender-aware content generation when gender tag is present
  Strict JSON output** and schema consistency for safe downstream publishing

  Setup Steps

  Core integrations
  Shopify Access Token** — Products read + Orders read (REST 2024-04)
  OpenAI API** — gpt-4o vision
  OpenRouter API** — Claude Sonnet (3.5)
  Perplexity API** — vendor/market verification via perplexityTool
  Google Sheets OAuth** — Products, ProcessingState, Error_log, Sales analytics

  Configure sheets
  ProcessingState** with fields:
    batch number
    page_info_next
  Products** with:
    Product ID
    Product Title
    Product Type
    Vendor
    Image url
    Status
    country of origin
    x_style_code
    gender
    Generated Description
  Error_log** with:
    timestamp
    Reason of Error
  Sales Analytics Sheet** with:
    Date
    Total Sales

  Workflow Capabilities

  Discovery and staging
  Auto-paginate Shopify; stage eligible products in Sheets with reasons and timestamps.

  Vision-grounded copywriting
  Descriptions reflect only visible attributes plus verified brand context; concise, mobile-friendly structure with gender-aware tone.

  Metadata awareness
  Auto-injects x-styleCode, country_of_origin, and gender when present; natural SEO for brand and product type.

  Sales intelligence
  Automated daily sales tracking with Melbourne timezone support, handles zero-sale days, and maintains complete historical records.

  Error analytics
  Layman + technical diagnosis logged to Error_log to shorten MTTR.

  Safe output
  Structured JSON via outputParserStructured for predictable row updates.

  Credentials Required

  Shopify Access Token** (Products + Orders read permissions)
  OpenAI API Key** (GPT-4o vision)
  OpenRouter API Key** (Claude Sonnet)
  Perplexity API Key**
  Google Sheets OAuth**

  Ideal For

  E-commerce teams** scaling compliant, on-brand product copy with comprehensive sales insights
  Agencies and SEO specialists** standardizing image-grounded descriptions with performance tracking and analytics
  Stores** needing resumable pagination, auditable content operations, and automated daily sales reporting in Sheets

  Advanced Features

  Dual-workflow architecture**: Content generation + Sales analytics in one system
  Link-header pagination with page_info persistence in ProcessingState
  Title/content normalization (e.g., color removal) configurable per brand
  Gender-aware copywriting** based on product tags
  Memory windows (memoryBufferWindow) to keep multi-step prompts consistent
  Melbourne timezone support** for accurate daily sales cutoffs
  Zero-sales handling** ensures complete analytics continuity
  Structured Output enforcement for downstream safety
  AI-powered error diagnosis** with technical and layman explanations

  Time & Scheduling (Universal)

  The workflow includes two independent schedules:
  Content Generation**: Every 5 minutes (configurable) for product processing
  Sales Analytics**: Daily at 2:01 PM Melbourne time for previous day's sales

  For globally distributed teams, schedule triggers and timestamps can be standardized on UTC to avoid regional drift.

  Pro Tip

  Start with small batches (limit set to 10 or fewer) to validate both copy generation and sales tracking flows. The workflow handles dual operations independently - content generation failures won't affect sales analytics and vice versa. Monitor the Error_log sheet for any issues and use the ProcessingState sheet to track pagination progress.

nodes_used:
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metadata_json:
  {"categories":["automation","e-commerce","content generation","data processing"],"complexity":"complex","use_cases":["Bulk product description generation from images","SEO-aware product copywriting","Localisation / region-agnostic descriptions","Automated product content pipeline for Shopify","Brand-context verification for accuracy"],"estimated_setup_minutes":90,"required_services":["OpenAI GPT-4o Vision (or equivalent multimodal LLM)","Anthropic Claude 3.5 Sonnet","Perplexity API (research/verification)","Google Sheets API (or spreadsheet service)","Shopify API (or product import endpoint)","HTTP/Webhook endpoint or integration router (OpenRouter or similar)"],"key_features":["Image-to-attribute extraction using multimodal LLM","Multi-model orchestration (GPT-4o + Claude) for draft + polish","Perplexity-backed brand/context verification","Google Sheets orchestration and bulk processing","SEO-aware, localized copy generation rules/templates and heuristics (region-agnostic) ￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼,"],"target_audience":["e-commerce merchants and store owners","growth/marketing teams and copywriters","content operations teams handling bulk listings and localization engineers/developers"]}


