# templates

name: Automate Gmail Inbox Organization with Rule-based Categorization and Smart Actions
author_name: Solido AI
author_username: solidoai
categories: []
created_at: 2025-07-01T14:25:20.168Z
updated_at: 2025-07-01T14:25:20.168Z
url: https://n8n.io/workflows/5518
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  How it works:
  The organizer continuously monitors your Gmail inbox. It analyzes sender and subject to categorize emails (Work, Purchases, Newsletter) and automatically applies labels. Based on the category, it performs specific actions, such as marking important emails or archiving newsletters.

  Set up steps:
  The initial setup requires Gmail access permission and defining the categorization rules and desired actions for each email type. This process can be configured in approximately 5 to 10 minutes, depending on the complexity of the rules you wish to establish.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","n8n-nodes-base.switch","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","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","email management","productivity","integration"],"complexity":"simple","use_cases":["Automatically categorize incoming emails (Work, Purchases, Newsletter)","Apply labels and folder organization","Archive or mark emails as important based on category","Reduce inbox clutter and improve prioritization","Automate repetitive email triage tasks"],"estimated_setup_minutes":10,"required_services":["Gmail (Google account) / Gmail API"],"key_features":["Continuous inbox monitoring","Rule-based sender and subject analysis","Automatic labeling and categorization","Category-specific actions (archive, mark important, etc.)","Customizable rules and actions"],"target_audience":["individuals","professionals","small business owners / teams looking to streamline email workflow"]}


name: Process Documents with Recursive Chunking using Google Drive, OpenAI & Gemini RAG
author_name: Mohsin Ali
author_username: binbakhsh
categories: []
created_at: 2025-07-01T15:06:26.131Z
updated_at: 2025-07-01T15:06:26.131Z
url: https://n8n.io/workflows/5521
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  1. Document Ingestion & Processing

  Google Drive Trigger monitors for new files → Loop Over Items processes each file → File Info extracts metadata → Google Drive downloads the actual content → Switch routes to appropriate extractors (PDF or TEXT) based on file type

  2. Content Transformation & Chunking

  Document Data node processes extracted text → Recursive Splitter breaks content into contextual chunks → Chunk Splitting applies intelligent segmentation while preserving document context and relationships between chunks

  3. Embedding & Storage

  Basic LLM Chain processes chunks → OpenAI Chat Model generates contextual understanding → Summarize creates document summaries → Supabase Vector Store saves embeddings with metadata → Embeddings OpenAI creates vector representations → Default Data Loader handles storage operations

  4. Query Processing & Retrieval

  When Clicking Execute triggers user queries → OpenAI processes and understands the question → AI Agent orchestrates hybrid search (combining vector similarity + keyword matching) → Google Gemini Chat Model generates final responses using retrieved context → HTTP Request handles additional external data sources

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleDrive","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.summarize","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStoreSupabase","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  [encoded data, 8772 characters]

metadata_json:
  {"categories":["automation","integration","data processing","knowledge management"],"complexity":"complex","use_cases":["Build RAG-enabled document search/QA systems","Automated document ingestion and indexing","Enterprise knowledge base creation","Document summarization and metadata extraction","Customer support and contract analysis"],"estimated_setup_minutes":60,"required_services":["Google Drive API","OpenAI (Chat + Embeddings)","Google Gemini (or Vertex AI)","Supabase (vector store)","Optional external HTTP APIs"],"key_features":["Automatic file monitoring and ingestion from Google Drive","File-type routing and extractor selection (PDF / text)","Recursive contextual chunking that preserves document relationships","Embedding generation and storage in Supabase vector DB","Hybrid retrieval (vector similarity + keyword matching) with AI agent orchestration\",\"LLM-based summarization and contextual understanding\",\"Query processing pipeline with multi-model responses (OpenAI + Gemini)"],"target_audience":["Developers","Data engineers","ML engineers / ML Ops practitioners\",\"Knowledge managers and product teams"]}


name: Convert and Manipulate PDFs with Api2Pdf and AWS Lambda
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T17:11:54.298Z
updated_at: 2025-07-01T17:11:54.298Z
url: https://n8n.io/workflows/5522
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 9 Api2Pdf - PDF Generation, Powered by AWS Lambda API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community
  Import this workflow into your n8n instance
  Credentials Add Api2Pdf - PDF Generation, Powered by AWS Lambda credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the Api2Pdf - PDF Generation, Powered by AWS Lambda API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://v2018.api2pdf.com
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (9 total)

  🔧 Chrome (3 endpoints)

  • POST /chrome/html: Convert raw HTML to PDF
  • GET /chrome/url: Convert URL to PDF
  • POST /chrome/url: Convert URL to PDF

  🔧 Libreoffice (1 endpoints)

  • POST /libreoffice/convert: Convert office document or image to PDF

  🔧 Merge (1 endpoints)

  • POST /merge: Merge multiple PDFs together

  🔧 Wkhtmltopdf (3 endpoints)

  • POST /wkhtmltopdf/html: Convert raw HTML to PDF
  • GET /wkhtmltopdf/url: Convert URL to PDF
  • POST /wkhtmltopdf/url: Convert URL to PDF

  🔧 Zebra (1 endpoints)

  • GET /zebra: Generate bar codes and QR codes with ZXING.

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Api2Pdf - PDF Generation, Powered by AWS Lambda API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  [encoded data, 5240 characters]

metadata_json:
  {"categories":["automation","integration","document processing","serverless","AI integration"],"complexity":"medium","use_cases":["Convert HTML/URL/documents/images to PDF","Merge multiple PDFs","Generate barcodes/QR codes (Zebra)","Expose PDF generation API as an MCP tool for AI agents","Automate document generation from AI-driven parameters"],"estimated_setup_minutes":200,"required_services":["Api2Pdf (PDF Generation API)","n8n instance with MCP/webhook support","Api2Pdf AWS Lambda backend (managed by Api2Pdf)","AI agents or clients (e.g., Claude, Cursor) for consumption"],"key_features":["Maps 9 Api2Pdf endpoints (Chrome, Wkhtmltopdf, LibreOffice, Merge, Zebra) to MCP endpoints","AI-aware parameter injection via $fromAI() expressions","Native n8n HTTP request handling and error management","Returns original Api2Pdf responses to agents","Quick deploy: add credentials, activate workflow, copy webhook URL"],"target_audience":["Developers and integration engineers","AI builders/agents integrators","Automation and DevOps teams handling document workflows"]}


name: Evaluate tool usage accuracy in multi-agent AI workflows using Evaluation nodes
author_name: Angel Menendez
author_username: djangelic
categories: []
created_at: 2025-07-01T17:12:40.342Z
updated_at: 2025-07-01T17:12:40.342Z
url: https://n8n.io/workflows/5523
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who's it for
  This workflow is ideal for AI developers running multi-agent systems in n8n who need to quantitatively evaluate tool usage behavior. If you're building autonomous agents and want to verify their decisions against ground-truth expectations, this workflow gives you plug-and-play observability.

  What it does
  This template uses n8n's built-in Evaluation Trigger and Evaluation nodes to assess whether an AI agent correctly used all the expected tools. It supports:

  Dataset-driven testing of agent behavior

  Logging actual tools to compare them with the expected tools

  Assigning performance metrics (tool_called = true/false)

  Persisting output back to Google Sheets for further debugging

  The workflow can be triggered by either the chat input or the dataset row evaluation. It routes through a multi-tool agent node powered by the best LLMs. The agent has access to tools such as web search, calculator, vector search, and summarizer tools. The workflow then aims to validate tool use decisions by extracting the intermediate steps from the agent (i.e., action + observation) and comparing the tools that were called with the expected tools. If the tools that were called during the workflow execution match, then it's a pass; otherwise, it's documented as a fail. The evaluation nodes take care of that process. 

  How to set it up
  Connect your Google Sheets OAuth2 credential. Replace the document with your own test dataset.

  Set your desired models and configure the different agent tools, such as the summarizer and vector store. The default vector store used is Qdrant, so the user must create this vector store with a few samples of queries + web search results.

  Run from either the chat trigger or the evaluation trigger to test.

  Requirements
  Google Sheets OAuth2 credential

  OpenRouter / OpenAI credentials for AI agents and embeddings

  Firecrawl and Qdrant credentials for web + vector search

  How to customize
  Edit the Search Agent system message to define tool selection behavior

  Add more metric columns in the Evaluation node for complex scoring

  Add new tool nodes and link them to the agent block

  Swap in your own summarizer

nodes_used:
  ["@n8n/n8n-nodes-langchain.toolCalculator","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.noOp","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStoreQdrant"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","AI evaluation","integration"],"complexity":"complex","use_cases":["Dataset-driven testing of multi-agent behavior","Validating whether agents invoked expected tools","Logging and persisting evaluation results for debugging","Quantitative scoring of agent tool-usage (pass/fail)","Observability for autonomous agent decision-making"],"estimated_setup_minutes":45,"required_services":["Google Sheets (OAuth2)","OpenRouter / OpenAI (LLM + embeddings)","Firecrawl (web search)","Qdrant (vector store)"],"key_features":["Uses n8n Evaluation Trigger and Evaluation nodes for automated scoring","Extracts agent intermediate steps (action + observation) to identify called tools","Compares actual vs expected tools and assigns tool_called true/false metrics","Dataset-driven runs with Google Sheets persistence","Multi-tool agent (web search, calculator, vector search, summarizer) integration supportable via LLMs/agents block','Configurable system message and metric columns for custom scoring"],"target_audience":["AI developers building autonomous/multi-agent systems","ML engineers and QA focused on agent behavior testing","Automation engineers integrating LLM agents with external tools"]}


name: Generate & Email Personalized Jokes with GPT-4o-mini and Gmail
author_name: Oriol Seguí
author_username: oxsr11
categories: []
created_at: 2025-07-01T17:55:38.306Z
updated_at: 2025-07-01T17:55:38.306Z
url: https://n8n.io/workflows/5525
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  This fun workflow automates the generation and delivery of personalized jokes by email based on the names or objects entered in the form. The process works as follows:

  On form submission
  The workflow starts when someone submits a form with the required names or objects to create the joke.
  You can modify the form fields to make the jokes more creative.

  Set the output language
  Manually define the language in which you want to receive the joke.

  OpenAI Message Model
  Uses the OpenAI model to generate the joke based on the prompt and in the chosen language.
  (The response is limited to around 200 tokens.)

  Gmail: send message
  The generated joke is automatically sent to the specified email address via Gmail.

nodes_used:
  ["n8n-nodes-base.formTrigger","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","communication","entertainment"],"complexity":"simple","use_cases":["Automated personalized birthday or celebration emails","Team icebreakers or internal morale boosters","Marketing engagement with humorous outreach","Event follow-ups and attendee engagement","Demo or prototype for GPT-powered email content"],"estimated_setup_minutes":10,"required_services":["OpenAI (GPT-4o-mini)","Gmail (Google account / Gmail API)","n8n (form node or external form provider like Typeform/Webhook)"],"key_features":["Generate personalized jokes from form inputs","Manual selection of output language","Limits model response length (~200 tokens)","Automatically sends joke via Gmail","Customizable prompt and form fields for creativity"],"target_audience":["community managers","HR teams","marketers and growth teams doing outreach experiments or fun campaigns  — [concise: marketers]  (edited)"]}


name: Create a WHOIS API Interface for AI Agents with 8 Domain Management Operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T19:19:26.667Z
updated_at: 2025-07-01T19:19:26.667Z
url: https://n8n.io/workflows/5528
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 8 Bulk WHOIS API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add Bulk WHOIS API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the Bulk WHOIS API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to http://localhost:5000
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (8 total)

  🔧 Batch (4 endpoints)

  • GET /batch: Get your batches
  • POST /batch: Create batch. Batch is then being processed until all provided items have been completed. At any time it can be get to provide current status with results optionally.
  • DELETE /batch/{id}: Delete batch
  • GET /batch/{id}: Get batch

  🔧 Db (1 endpoints)

  • GET /db: Query domain database

  🔧 Domains (3 endpoints)

  • GET /domains/{domain}/check: Check domain availability
  • GET /domains/{domain}/rank: Check domain rank (authority).
  • GET /domains/{domain}/whois: WHOIS query for a domain

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Bulk WHOIS API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  [encoded data, 4100 characters]

metadata_json:
  {"categories":["integration","automation","API","AI integration","domain management"],"complexity":"medium","use_cases":["Expose Bulk WHOIS API to AI agents via an MCP server","Batch WHOIS processing and status tracking","Domain availability and WHOIS lookups for automation","Domain authority/rank checks","Query a local domain database for analytics or enrichment"],"estimated_setup_minutes":20,"required_services":["n8n instance (with MCP trigger support)","Bulk WHOIS API backend (service reachable, example: http://localhost:5000)","Bulk WHOIS API credentials","AI agents or clients (Claude Desktop, Cursor, custom AI apps) — to connect via MCP URL"],"key_features":["MCP trigger exposes 8 WHOIS-related endpoints to AI agents","Batch endpoints: create, list, get, delete and monitor processing status","Domain endpoints: availability check, rank (authority), and WHOIS lookup","Database query endpoint for domain datastore","$fromAI() expressions auto-populate parameters from AI agent requests (path, query, body, headers, auth)"],"target_audience":["developers building AI tools and integrations","AI engineers and researchers integrating tool use","DevOps / SREs deploying agent-accessible endpoints in n8n workflows"]}


name: Monitor Software Compliance with Jamf Patch Summaries in Slack
author_name: Jean-Marie Rizkallah
author_username: mrrobot
categories: []
created_at: 2025-07-01T19:28:28.897Z
updated_at: 2025-07-01T19:28:28.897Z
url: https://n8n.io/workflows/5529
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  🧩 Jamf Patch Summary to Slack
  Stay on top of software patch compliance by automatically posting Jamf patch summaries to Slack.
  This helps IT and security teams quickly identify outdated installs and take action—without logging into Jamf.

  ✅ Prerequisites
  • A Jamf Pro API key with permissions to read software titles and patch summary
  • A Slack app or incoming webhook URL with permission to post messages to your desired channel

  🔍 How it works
  • Manually trigger the flow or Add a webhook
  • Fetch a list of software titles from Jamf Pro
  • Filter to select the software you're tracking (e.g. Chrome, Edge)
  • Retrieve the patch summary for that software (latest version, up-to-date, out-of-date counts)
  • Format the summary into Slack Block Kit
  • Post the formatted summary into a Slack channel

  ⚙️ Set up steps
  • Takes ~5–10 minutes to configure
  • Set your server BaseURL variable in the Set Node
  • Add your Jamf Pro API credentials in the HTTP Request nodes (Get & Retrieve)
  • Set the target software ID in the Filter node
  • Add your Slack webhook URL or token in the final HTTP node
  • Optional: Adjust Slack formatting inside the Function node

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.slack"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","IT management","security","notifications"],"complexity":"medium","use_cases":["Monitor software patch compliance","Notify IT/security teams of out-of-date installs","Automated reporting of patch summary to Slack","Track specific applications (e.g., Chrome, Edge)"],"estimated_setup_minutes":10,"required_services":["Jamf Pro API (with read permissions for software titles and patch summaries)","Slack app or Incoming Webhook (permission to post to channel)","n8n instance / reachable BaseURL"],"key_features":["Fetch software titles from Jamf Pro","Filter to target specific software","Retrieve patch summary (latest version, up-to-date/out-of-date counts)","Format message using Slack Block Kit","Post formatted summary to Slack channel (webhook or token)"],"target_audience":["IT administrators","Security teams","Desktop engineers/endpoint teams (Sysadmins)"]}


name: Auto Generate & Post LinkedIn Content for Amazon Sellers with GPT-4o & Apify
author_name: Usman Liaqat
author_username: usmanliaqat
categories: []
created_at: 2025-07-01T20:30:56.580Z
updated_at: 2025-07-01T20:30:56.580Z
url: https://n8n.io/workflows/5531
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  How it works

  This powerful automation turns LinkedIn influencer activity into high performing Amazon seller content, fully hands-off. It runs in two phases:

  AI Content Generator
     Retrieves influencer usernames from Airtable
     Scrapes their most recent LinkedIn post via Apify
     Uses OpenAI (GPT-4o) to generate original Amazon focused post content
     Generates a branded LinkedIn image using AI (WeSpark visual identity)
     Saves content & image link to Google Drive
     Creates a record in Airtable with Status = In review

  Scheduled Publisher

     Every day at 4 PM, one post from Airtable with Status = Approved is:

       Downloaded from Drive
       Published on LinkedIn
       Marked as Posted in Airtable

  ⚙️ Set Up Steps

  Time to set up:** 15–20 minutes
  Create two Airtable tables:

    influencers with UserName (LinkedIn usernames only)
    posts with fields:

      Description (text)
      Image (Drive link)
      InfluencerUsername
      InfluencerPost
      InfluencerPostCreatedAt
      Status (In review, Approved, Posted, Rejected)
  Add Google Drive OAuth2 credentials for saving & downloading images
  Configure OpenAI GPT-4o key (for text + image generation)
  Set up Apify LinkedIn scraper and add header credentials
  Link your LinkedIn account (company or personal profile)

  Workflow Phases

  1. AI Generator (Triggered manually)

  Loops over influencer usernames
  Scrapes latest LinkedIn post
  Skips if already stored
  Uses GPT-4o to:

    Rewrite the post uniquely for Amazon sellers
    Generate JSON with text + image prompt
  Saves AI-generated image to Google Drive
  Logs post to Airtable with In review status

  2. Daily Publisher (Scheduled)

  Runs every day at 4 PM
  Filters Airtable for Status = Approved
  Picks 1 record, downloads image from Drive
  Publishes to LinkedIn
  Updates Airtable status to Posted

  Airtable Setup Example

  influencers Table:

  | UserName    |
  | ----------- |
  | jon-derkits |

  posts Table:

  | Description                    | Image         | InfluencerUsername | InfluencerPost  | InfluencerPostCreatedAt | Status    |
  | ------------------------------ | ------------- | ------------------ | --------------- | ----------------------- | --------- |
  | Amazon Listing Optimization... | \[Drive Link] | jon-derkits        | \[LinkedIn URL] | 2025-06-18 19:30:01     | In review |

  Status field options:

  In review
  Approved
  Posted
  Rejected

  Example LinkedIn Visuals

  | Caption                                                                                            | Image                                                                                               |
  | -------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------- |
  | Boost Your Amazon ROI!  Data-driven strategies are your secret weapon...                    | View Image |
  | Boost Sales with 5–10% Higher Conversions!  Utilize Enhanced Brand Content and Smart PPC... | View Image |
  | Grow Your Amazon Business  WeSpark – Amazon Consulting Agency...                            | View Image |
  | Amazon Growth Strategies  Embrace the power of smart optimization...                     | View Image |

  ✅ Best For:

  Amazon agencies and FBA consultants
  B2B SaaS tools targeting eCommerce
  LinkedIn ghostwriters and creators
  Content marketing teams for Amazon sellers

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.airtable","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.limit","n8n-nodes-base.googleDrive","n8n-nodes-base.linkedIn","n8n-nodes-base.airtable","n8n-nodes-base.scheduleTrigger"]

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metadata_json:
  {"categories":["automation","integration","content generation","social media"],"complexity":"medium","use_cases":["Automatically generate LinkedIn posts for Amazon sellers by repurposing influencer content","Hands-off scheduled LinkedIn publishing for marketing teams","Content ideation and branded image creation for ecommerce agencies","Ghostwriting LinkedIn posts at scale for clients"],"estimated_setup_minutes":20,"required_services":["Airtable","Apify (LinkedIn scraper)","OpenAI (GPT-4o)","Google Drive (OAuth2)","LinkedIn account (company or personal)","n8n"],"key_features":["Scrapes latest influencer LinkedIn posts","Uses GPT-4o to rewrite content tailored to Amazon sellers","Generates branded LinkedIn images via AI and saves to Google Drive","Stores and tracks posts in Airtable with workflow statuses","Daily scheduled publisher that posts approved items to LinkedIn and updates status to Posted」「Duplicate detection/skip if post already stored」「Configurable influencer list in Airtable and single-post-per-day publishing policy"],"target_audience":["Amazon agencies and FBA consultants","B2B SaaS companies targeting eCommerce","LinkedIn ghostwriters and creators for Amazon niche clients」「Content marketing teams for Amazon sellers"]}


name: Real-time PulsePoint Emergency Alerts to iMessage with AI Summaries
author_name: David Harvey
author_username: xtgy
categories: []
created_at: 2025-07-01T20:58:26.415Z
updated_at: 2025-07-01T20:58:26.415Z
url: https://n8n.io/workflows/5533
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  🚨 Emergency Alerts Reporter to iMessage

  This n8n template fetches real-time emergency incident alerts from PulsePoint for a specific agency and delivers them directly to any phone number via iMessage using the Blooio API. It's designed to keep users informed with clear, AI-summarized reports of emergency activity near them—automatically and reliably.

  Use cases are powerful and immediate:  
  Get real-time fire/medical alerts for your neighborhood.  
  Use it for family, local safety groups, or even emergency response teams.  
  Convert technical dispatch data into readable updates with emojis and plain English.

  🧠 Good to Know

  You’ll need a PulsePoint agency ID (see instructions below).  
  iMessages are sent using Blooio’s API (which supports Apple’s iMessage and fallback RCS/SMS).  
  Messages are AI-enhanced using OpenAI's o4-mini model to summarize incident reports with context and urgency.  
  The workflow runs every hour, but this can be configured to match your needs.  
  Each report is sent only once, thanks to persistent tracking of seen incident IDs in workflow static memory.

  ⚙️ How it Works

  Trigger: A Schedule Trigger (every hour) or manual start kicks off the flow.  
  Get Alerts: A code node fetches the latest PulsePoint incidents for a specified agency and decrypts the data.  
  Filter New Incidents: We store previously seen incident IDs to prevent duplicate alerts.  
  Merge Incidents: All new incident details are merged into a single payload.  
  Condition Check: If there are no new incidents, nothing is sent.  
  AI Summary: The incident data is passed to an AI agent for summarization with human-friendly emojis and formatting.  
  Send Message: The final summary is sent via Blooio’s API to your phone using iMessage.

  📝 How to Use

  Get Your PulsePoint Agency ID:  
     Visit https://web.pulsepoint.org.  
     Find your agency by location or name.  
     Inspect the API call or browser network log to get the agencyid (e.g. 19100 from a URL like ?agencyid=19100).  

  Set Up Blooio for Messaging:  
     Sign up at https://blooio.com.  
     Go to your account and retrieve your Bearer API Key.  
     Pricing details available on their pricing page.  
     Add your key to the HTTP Request node as a Bearer Token.  

  OpenAI API:  
     Create or use an existing OpenAI account.  
     Use the o4-mini model for efficient, readable summaries.  
     Get your OpenAI API key from https://platform.openai.com/account/api-keys.  

  Add Your Phone Number:  
     Replace +1111112222 with your actual number (international format).  
     You can also modify the message content or prepend special tags/emojis.

  ✅ Requirements

  PulsePoint agency ID** – See usage instructions above  
  OpenAI API Key** – Get API Key  
  Blooio Account & Bearer Token** – Get Started  
  Phone number** for iMessage delivery  

  🔧 Customizing This Workflow

  Change the schedule** to get alerts more or less frequently  
  Add filters** to only get alerts for specific incident types (e.g. fires, traffic accidents)  
  Send to groups**: Expand to send alerts to multiple recipients or use Slack instead of iMessage  
  Use different AI prompts** to get detailed, humorous, or abbreviated alerts depending on your audience  

  With just a few credentials and a phone number, you’ll have real-time incident alerts with human-friendly summaries at your fingertips.

  🛠️ Stay informed. Stay safe.

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

workflow_json_compressed:
  [encoded data, 5804 characters]

metadata_json:
  {"categories":["automation","integration","notifications","public safety"],"complexity":"medium","use_cases":["Receive real-time neighborhood fire/medical alerts","Notify family or local safety groups of nearby incidents","Provide readable summaries for emergency response teams","Convert technical dispatch data into plain-English notifications","Send group or multi-channel alerts (iMessage with SMS/RCS fallback)"],"estimated_setup_minutes":25,"required_services":["PulsePoint (agency ID)","Blooio (iMessage/RCS/SMS API & Bearer token)","OpenAI (o4-mini API key)","n8n instance"],"key_features":["Fetches real-time PulsePoint incidents for a specified agency","Persistent deduplication of incident IDs (static workflow memory)","AI-generated human-friendly summaries (OpenAI o4-mini) with emojis/urgency context","Delivers messages via Blooio to iMessage with SMS/RCS fallback","Configurable schedule trigger and optional incident-type filters"],"target_audience":["individuals/homeowners concerned about local safety","families and neighborhood watch groups","community safety organizers and volunteers (EMS/Fire liaison) means to receive concise alerts) ) ) )"]}


name: eBay Finances Data Access for AI Agents with MCP Server Integration
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T21:05:51.006Z
updated_at: 2025-07-01T21:05:51.006Z
url: https://n8n.io/workflows/5534
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 7 eBay Finances API operations to AI agents.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add eBay Finances API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the eBay Finances API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://apiz.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (7 total)

  🔧 Payout

  • GET /payout: List seller payouts with filters
  • GET /payout/{payout_Id}: Get single payout details
  🔧 Payout_Summary

  • GET /payout_summary: Show payout totals by status
  🔧 Seller_Funds_Summary

  • GET /seller_funds_summary: View pending/unreleased funds
  🔧 Transaction

  • GET /transaction: Search monetary transactions
  🔧 Transaction_Summary

  • GET /transaction_summary: Get transaction totals + holds
  🔧 Transfer

  • GET /transfer/{transfer_Id}: Retrieve eBay reimbursement details

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native eBay Finances API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","AI integration","e-commerce"],"complexity":"medium","use_cases":["Expose eBay Finances API to AI agents","Retrieve seller payouts, transactions and transfers","Build AI tools that query eBay financial data","Rapidly prototype AI assistants that need payment/transaction data","Bridge n8n workflows with Claude/Cursor/custom AI via MCP"],"estimated_setup_minutes":20,"required_services":["eBay Finances API (developer credentials)","n8n instance with MCP trigger node (self‑hosted or cloud)","AI agent/client (e.g., Claude Desktop, Cursor, custom AI)","Publicly reachable webhook/SSE endpoint or tunneling if self‑hosted"],"key_features":["MCP-compatible server exposing 7 eBay Finances endpoints (payout, payout_summary, seller_funds_summary, transaction, transaction_summary, transfer)","Automatic parameter population via $fromAI() expressions","Native eBay API request/response passthrough","Built-in n8n HTTP error handling and logging","Supports path, query, body and header parameters for AI calls','Easy to extend or add custom logic"],"target_audience":["n8n users and integrators","Developers building AI agents/tools","E-commerce/marketplace operators needing finance data access for automation or analysis','Fintech analysts wanting programmatic access to seller financials"]}


name: Internet Archive Search API Integration for AI Agents (3 Operations)
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T21:17:27.764Z
updated_at: 2025-07-01T21:17:27.764Z
url: https://n8n.io/workflows/5535
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 3 Search Services API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the Search Services API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.archive.org
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (3 total)

  🔧 Search (3 endpoints)

  • GET /search/v1/fields: Fields that can be requested
  • GET /search/v1/organic: Return relevance-based results from search queries

  • GET /search/v1/scrape: Scrape search results from Internet Archive, allowing a scrolling cursor

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Search Services API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","AI","web API","automation"],"complexity":"medium","use_cases":["Expose Internet Archive Search API to AI agents via MCP","Provide relevance-based search and scraping endpoints with cursor pagination","Connect AI clients (Claude, Cursor, custom apps) to archival search","Rapid prototyping of AI-enabled search tools"],"estimated_setup_minutes":20,"required_services":["n8n instance (with MCP capability)","Internet Archive Search API (https://api.archive.org) and Search Services credentials","AI agent or MCP-compatible client (e.g., Claude Desktop, Cursor, custom AI app)"],"key_features":["MCP trigger exposing 3 Search Services endpoints (fields, organic, scrape)","HTTP Request nodes proxying to api.archive.org","AI-driven parameter population via $fromAI() expressions","Supports scrolling cursor pagination for scrapes","Built-in n8n HTTP request error handling and logging"],"target_audience":["developers","AI builders/engineers","automation/ops engineers integrating AI tools with web APIs"]}


name: Internet Archive Wayback Machine API for AI Assistants
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T21:18:56.407Z
updated_at: 2025-07-01T21:18:56.407Z
url: https://n8n.io/workflows/5536
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 Wayback API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community
  Import this workflow into your n8n instance
  Credentials Add Wayback API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the Wayback API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.archive.org
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Wayback (2 endpoints)

  • GET /wayback/v1/available: GET /wayback/v1/available
  • POST /wayback/v1/available: POST /wayback/v1/available

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Wayback API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","ai-assistants","web-archiving"],"complexity":"simple","use_cases":["Allow AI agents to query Wayback Machine availability endpoints","Enable AI tools to fetch archived page metadata and timestamps","Embed Wayback API as a tool in custom AI apps or agent workflows","Research and content verification using archived snapshots","Rapid prototyping of AI integrations with external HTTP APIs"],"estimated_setup_minutes":20,"required_services":["n8n instance with public webhook access","Internet Archive Wayback Machine API (api.archive.org) credentials or access","MCP-compatible AI agent or client (e.g., Claude Desktop, Cursor) — optional for testing"],"key_features":["Exposes Wayback /wayback/v1/available via MCP-compatible endpoints (GET and POST)","MCP Trigger node serves as server endpoint for AI agents","HTTP Request nodes proxy calls to api.archive.org","AI expressions ($fromAI()) auto-populate parameters from agent requests","Returns native Wayback API responses directly to agents (no extra mapping needed)"],"target_audience":["developers building AI agent integrations","no-code/low-code automation builders","AI/ML engineers adding external tool access to agents"]}


name: IP Geolocation Lookup with BigDataCloud API for AI Agents
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T21:27:24.500Z
updated_at: 2025-07-01T21:27:24.500Z
url: https://n8n.io/workflows/5539
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 IP Geolocation API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community
  Import this workflow into your n8n instance
  Credentials Add IP Geolocation API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the IP Geolocation API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.bigdatacloud.net
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Data (2 endpoints)

  • GET /data/ip-geolocation-full: IP Geolocation with Confidence Area and Hazard Report API
  • GET /data/ip-geolocation-with-confidence: IP Geolocation with Confidence Area API

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native IP Geolocation API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","api","data enrichment","automation","geolocation"],"complexity":"simple","use_cases":["Enrich IP addresses with geolocation data for AI agents","Personalization and geotargeting in apps","Security and fraud detection (location-based checks)","Analytics and reporting on user locations","Providing geolocation lookups to custom AI tools or assistants"],"estimated_setup_minutes":200,"required_services":["BigDataCloud IP Geolocation API (api.bigdatacloud.net) — API credentials required","n8n instance (to import and run the workflow / MCP trigger)","AI agent or platform to connect to the MCP endpoints (e.g., Claude, Cursor) — optional"],"key_features":["Exposes two MCP-compatible endpoints for IP geolocation","Direct HTTP request nodes calling BigDataCloud API","AI-friendly $fromAI() expressions for automatic parameter population","Native API responses returned to calling AI agents","Built-in n8n HTTP error handling and logging, easy extensibility"],"target_audience":["Developers","AI engineers and integrators","Data engineers / analysts needing IP enrichment data"]}


name: Query Bicycle Incident Data with BikeWise API through MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T21:28:34.770Z
updated_at: 2025-07-01T21:28:34.770Z
url: https://n8n.io/workflows/5540
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:34
description:
  Complete MCP server exposing 4 BikeWise API v2 API operations to AI agents.

  ⚡ Quick Setup
  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add BikeWise API v2 credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the BikeWise API v2 API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://bikewise.org/api
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (4 total)

  🔧 V2 (4 endpoints)

  • GET /v2/incidents: Paginated incidents matching parameters
  • GET /v2/incidents/{id}: GET /v2/incidents/{id}
  • GET /v2/locations: Unpaginated geojson response
  • GET /v2/locations/markers: Unpaginated geojson response with simplestyled markers

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native BikeWise API v2 API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4120 characters]

metadata_json:
  {"categories":["integration","API","automation","AI integration"],"complexity":"medium","use_cases":["Expose BikeWise API v2 to AI agents via MCP","Query bicycle incident data (paginated)","Retrieve geojson location data and markers","Integrate BikeWise data into custom AI apps or agent workflows"],"estimated_setup_minutes":20,"required_services":["BikeWise API v2 (https://bikewise.org/api)","n8n instance (self‑hosted or cloud)","AI agents or clients supporting MCP (e.g., Claude, Cursor)"],"key_features":["MCP server endpoint exposing 4 BikeWise API v2 operations","Automatic parameter population via $fromAI() expressions","Native n8n HTTP request handling with built‑in error management","Returns native BikeWise API responses (incidents, locations, markers)","Supports path/query parameters, headers, and auth credentials (BikeWise API v2)"],"target_audience":["Developers","AI integrators/engineers","Data analysts working with civic/bike incident data"]}


name: Track AI Agent token usage and estimate costs in Google Sheets
author_name: Solomon
author_username: solomon
categories: []
created_at: 2025-07-01T21:30:24.313Z
updated_at: 2025-07-01T21:30:24.313Z
url: https://n8n.io/workflows/5541
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  This n8n template demonstrates how to obtain token usage from AI Agents and places the data into a spreadsheet that calculates the estimated cost of the execution.

  Obtaining the token usage from AI Agents is tricky, because it doesn't provide all the data from tool calls. This workflow taps into the workflow execution metadata to extract token usage information.

  Works well with OpenAI, Google and Anthropic. Other LLM providers might need small tweaks.

  How it works
  The AI Agent executes and then calls a subworkflow to calculate the token usage.
  The data is stored in Google Sheets
  The spreadsheet has formulas to calculate the estimated cost of the execution.

  How to use
  The AI Agent is used as an example. Feel free to replace this with other agents you have.
  Call the subworkflow AFTER all the other branches have finished executing.

  Requirements
  LLM account (OpenAI, Gemini...) for API usage.
  Google Drive and Sheets credentials
  n8n API key of your instance

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.executeWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.set","n8n-nodes-base.n8n","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.splitOut","n8n-nodes-base.summarize","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatAnthropic","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6520 characters]

metadata_json:
  {"categories":["automation","cost monitoring","AI / LLM integration","reporting","spreadsheets"],"complexity":"medium","use_cases":["Track token usage of AI Agents across executions","Estimate and report LLM API costs","Audit and reconcile tool/agent call usage","Centralize usage data into Google Sheets for analysis","Trigger cost calculations after agent workflows finish"],"estimated_setup_minutes":30,"required_services":["LLM provider account (OpenAI, Anthropic, Google Gemini or other LLM API)","Google Drive & Google Sheets credentials","n8n instance with API key"],"key_features":["Extracts token usage from n8n workflow execution metadata","Stores usage records in Google Sheets","Spreadsheet contains formulas to calculate estimated costs","Subworkflow designed to run after all agent branches complete","Compatible with multiple LLM providers (may need tweaks)"],"target_audience":["n8n users / automation engineers","Developers integrating LLMs","ML engineers and SREs monitoring model usage and cost"]}


name: BIN Card Information Lookup API Connector for AI Agents with Balance Check
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T21:39:31.341Z
updated_at: 2025-07-01T21:39:31.341Z
url: https://n8n.io/workflows/5542
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 BIN Lookup API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add BIN Lookup API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the BIN Lookup API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.bintable.com/v1
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Balance (1 endpoints)

  • GET /balance: Check Balance

  🔧 {Bin} (1 endpoints)

  • GET /{bin}: Lookup for bin

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native BIN Lookup API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["integration","api","data lookup","ai-integration"],"complexity":"simple","use_cases":["Card BIN lookup (card brand, issuer, country)","Check account/card balance","Payment validation and pre-authorization checks","Fraud detection and risk scoring","Expose BIN lookup as a tool for AI agents / chatbots"],"estimated_setup_minutes":200,"required_services":["Bintable BIN Lookup API (https://api.bintable.com)","n8n instance (self-hosted or n8n.cloud)","AI agents or clients that support MCP (e.g., Claude, Cursor, custom AI apps)","Public webhook endpoint or accessible n8n webhook"],"key_features":["MCP server endpoint for AI agents","Two exposed endpoints: GET /balance and GET /{bin}","Automatic parameter population via $fromAI() expressions","Native n8n HTTP request nodes calling the BIN Lookup API","Built-in HTTP error handling and logging in n8n workflows (retry/response) `,`Easily extensible to add custom logic or extra endpoints"],"target_audience":["Developers building AI tools or integrations","Fintech engineers and payment teams","Fraud/risk analysts and security teams integrating BIN data workflows\",\"AI/ML engineers integrating external tools for agents"]}


name: Create Evergreen Content with GitHub Dynamic Images & URL Redirects
author_name: Eduard
author_username: eduard
categories: []
created_at: 2025-07-01T23:04:05.588Z
updated_at: 2025-07-01T23:04:05.588Z
url: https://n8n.io/workflows/5546
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  Transform static digital assets into dynamic, self-updating powerhouses that stay relevant for years to come!

  This workflow solves a common problem: once you publish forms, emails, or templates, their content becomes frozen in time. Users discovering them months later see outdated information, missed opportunities, and stale offers.

  Stop losing opportunities to stale content – make your digital assets work harder and stay fresher, automatically!

  Here's how it works:
  🔗 Stable embed links mean your original assets never need updating
  🔄 Dynamic URL redirects that automatically point to the latest pages
  🖼️ Auto-updating images that showcase fresh offers or content
  📅 Scheduled updates keep everything current without manual intervention

  Perfect for:
  Workflow sticky notes that become evergreen marketing billboards
  Registration forms with current promotions
  Email signatures with latest offers  
  Website banners that stay seasonally relevant
  Any digital asset you want to "future-proof"

  The magic: Set it up once, embed the stable URLs/images in your content, then forget about it. Years later, users will still see fresh, as current information automatically pulled from your workflow.

  Requirements: Free accounts with GitHub (image storage) and shorten.rest  (URL redirects).

  Both can be swapped for your preferred services.

  Follow me on LinkedIn for more tips on AI automation and n8n workflows!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.editImage","n8n-nodes-base.github","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.github","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5928 characters]

metadata_json:
  {"categories":["automation","content management","marketing","integration"],"complexity":"medium","use_cases":["Make embedded assets evergreen (forms, banners, signatures)","Auto-updating marketing images (seasonal offers, promotions)","Maintain stable embed URLs that redirect to latest pages","Keep registration or landing page links current without republishing","Turn static templates into self-updating assets"],"estimated_setup_minutes":30,"required_services":["GitHub (for image storage)","shorten.rest (for URL redirects)"],"key_features":["Stable embed links that never need changing in published content","Dynamic URL redirects pointing to latest target pages","Auto-updating images hosted on GitHub","Scheduled updates to refresh content automatically","Webhook/HTTP endpoints for manual or external triggers"],"target_audience":["marketers","content creators","web developers / frontend engineers embedding assets on sites/emails/forms or templates creators"]}


name: Connect Buffer Social Media Management API to AI Agents via MCP Protocol
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T23:39:54.843Z
updated_at: 2025-07-01T23:39:54.843Z
url: https://n8n.io/workflows/5547
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 18 Bufferapp API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the Bufferapp API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.bufferapp.com/1/
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (18 total)

  🔧 Info (1 endpoints)

  • GET /info/configuration{mediaTypeExtension}: Get Configuration

  🔧 Links (1 endpoints)

  • GET /links/shares{mediaTypeExtension}: Get Link Shares

  🔧 Profiles (7 endpoints)

  • POST /profiles/{id}/schedules/update{mediaTypeExtension}: Update Profile Schedules
  • GET /profiles/{id}/schedules{mediaTypeExtension}: Get Profile Schedules
  • GET /profiles/{id}/updates/pending{mediaTypeExtension}: Get Pending Updates
  • POST /profiles/{id}/updates/reorder{mediaTypeExtension}: Reorder Profile Updates
  • GET /profiles/{id}/updates/sent{mediaTypeExtension}: Get Sent Updates
  • POST /profiles/{id}/updates/shuffle{mediaTypeExtension}: Shuffle Profile Updates
  • GET /profiles/{id}{mediaTypeExtension}: Get Profile Details

  🔧 Profiles{Mediatypeextension} (1 endpoints)

  • GET /profiles{mediaTypeExtension}: List Profiles

  🔧 Updates (7 endpoints)

  • POST /updates/create{mediaTypeExtension}: Create Status Update
  • POST /updates/{id}/destroy{mediaTypeExtension}: Delete Status Update
  • GET /updates/{id}/interactions{mediaTypeExtension}: Get Update Interactions
  • POST /updates/{id}/move_to_top{mediaTypeExtension}: Move Update to Top
  • POST /updates/{id}/share{mediaTypeExtension}: Share Update Now
  • POST /updates/{id}/update{mediaTypeExtension}: Edit Status Update
  • GET /updates/{id}{mediaTypeExtension}: Get Update Details

  🔧 User{Mediatypeextension} (1 endpoints)

  • GET /user{mediaTypeExtension}: Get User Details

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Bufferapp API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  [encoded data, 6108 characters]

metadata_json:
  {"categories":["integration","automation","social media","AI-integration"],"complexity":"medium","use_cases":["Enable AI agents to read and manage Buffer posts and schedules","Automate social media publishing and updates via AI","Expose Buffer API as MCP-compatible tool for AI apps","Fetch profile, update, link and user data for analytics or moderation workflows"],"estimated_setup_minutes":293,"required_services":["Buffer (Bufferapp) API credentials","n8n instance (self-hosted or n8n cloud)","AI agent or app that supports the MCP protocol (e.g., Claude Desktop, Cursor, custom MCP clients)"],"key_features":["MCP trigger exposing 18 Buffer API endpoints","Automatic parameter population via $fromAI() expressions","Direct passthrough of native Buffer API responses","Built-in HTTP error handling and logging via n8n","Operations include creating/updating/deleting/sharing updates, managing profiles/schedules, links, and user info"],"target_audience":["Developers building AI-agent integrations","AI/ML engineers wanting tool-access to social accounts","Social media managers who want automated AI workflows to control Buffer accounts (with developer help)"]}


name: SMS Messaging API Integration for AI Agents with BulkSMS
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T23:46:43.610Z
updated_at: 2025-07-01T23:46:43.610Z
url: https://n8n.io/workflows/5548
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 15 BulkSMS JSON REST API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add BulkSMS JSON REST API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the BulkSMS JSON REST API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.bulksms.com/v1
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (15 total)

  🔧 Blocked-Numbers (2 endpoints)

  • GET /blocked-numbers: Block Phone Number
  • POST /blocked-numbers: Create a blocked number

  🔧 Credit (1 endpoints)

  • POST /credit/transfer: Transfer Account Credits

  🔧 Messages (5 endpoints)

  • GET /messages: List Related Messages
  • POST /messages: Send Messages
  • GET /messages/send: Send message by simple GET or POST
  • GET /messages/{id}: Show Message
  • GET /messages/{id}/relatedReceivedMessages: List Related Messages

  🔧 Profile (1 endpoints)

  • GET /profile: Retrieve User Profile

  🔧 Rmm (1 endpoints)

  • POST /rmm/pre-sign-attachment: Generate Attachment Upload URL

  🔧 Webhooks (5 endpoints)

  • GET /webhooks: Update Webhook Settings
  • POST /webhooks: Create a webhook
  • DELETE /webhooks/{id}: Delete a webhook
  • GET /webhooks/{id}: Read a webhook
  • POST /webhooks/{id}: Update a webhook

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native BulkSMS JSON REST API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  [encoded data, 7404 characters]

metadata_json:
  {"categories":["integration","communication","automation","ai-agent-integration","webhook-management"],"complexity":"medium","use_cases":["Allow AI agents to send SMS messages via BulkSMS","Expose BulkSMS API operations as MCP endpoints for AI tools","Manage webhooks and blocked numbers programmatically","Transfer account credits and retrieve account/profile data","Generate pre-signed upload URLs for attachments"],"estimated_setup_minutes":200,"required_services":["BulkSMS account / BulkSMS JSON REST API","n8n instance with MCP trigger support","Publicly reachable webhook URL (or tunnel like ngrok) for agent callbacks","AI agent or platform that can call MCP endpoints (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["Exposes 15 BulkSMS JSON REST API operations via MCP","MCP Trigger acts as server endpoint for AI agents","Automatic parameter population using $fromAI() expressions","Native n8n HTTP Request nodes with built-in error handling","Full passthrough of BulkSMS JSON responses to AI agents (no mapping required)」「Webhook create/read/update/delete and blocked-number management」「Attachment pre-sign URL generation for uploads"],"target_audience":["developers","AI engineers","automation engineers / integrators"]}


name: Access CO2 Measurement Data with CarbonDoomsDay API for AI Agents
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-01T23:49:13.065Z
updated_at: 2025-07-01T23:49:13.065Z
url: https://n8n.io/workflows/5550
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 CarbonDoomsDay API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the CarbonDoomsDay API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.carbondoomsday.com/api
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Co2 (2 endpoints)

  • GET /co2/: Get CO2 Measurement by Date
  • GET /co2/{date}/: CO2 measurements from the Mauna Loa observatory.

  This data is made available through the good work of the people at the
  Mauna Loa observatory. Their release notes say:

      These data are made freely available to the public and the scientific
      community in the belief that their wide dissemination will lead to greater
      understanding and new scientific insights.

  We currently scrape the following sources:

    [co2_mlo_weekly.csv]
    [co2_mlo_surface-insitu_1_ccgg_DailyData.txt]
    [weekly_mlo.csv]

  We have daily CO2 measurements as far back as 1958.

  Learn about using pagination via [the 3rd party documentation].

  [co2_mlo_weekly.csv]: https://www.esrl.noaa.gov/gmd/webdata/ccgg/trends/co2_mlo_weekly.csv
  [co2_mlo_surface-insitu_1_ccgg_DailyData.txt]: ftp://aftp.cmdl.noaa.gov/data/trace_gases/co2/in-situ/surface/mlo/co2_mlo_surface-insitu_1_ccgg_DailyData.txt
  [weekly_mlo.csv]: http://scrippsco2.ucsd.edu/sites/default/files/data/in_situ_co2/weekly_mlo.csv
  [the 3rd party documentation]: http://www.django-rest-framework.org/api-guide/pagination/#pagenumberpagination

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native CarbonDoomsDay API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","data access","AI agent tooling","environmental data"],"complexity":"simple","use_cases":["Expose CO2 measurement endpoints to AI agents","Fetch historical Mauna Loa CO2 data for analysis or dashboards","Integrate CO2 data into chatbots or AI workflows","Rapid prototyping of AI tools that need environmental data","Education and research access to CO2 time series"],"estimated_setup_minutes":200,"required_services":["n8n (self-hosted or cloud)","CarbonDoomsDay API (https://api.carbondoomsday.com)","Mauna Loa / NOAA / Scripps data sources (used by the API)","MCP-compatible AI agents or clients (e.g., Claude Desktop, Cursor, custom agents)"],"key_features":["MCP trigger exposes API endpoints to AI agents","Two GET endpoints for CO2 measurements (general and date-specific)","Automatic parameter population via $fromAI() expressions","Native n8n HTTP request handling with built-in error management","Returns native CarbonDoomsDay API responses (full data structures)"],"target_audience":["Developers building AI agents and integrations","Data scientists and analysts needing CO2 time series","Climate researchers and educators needing quick API access to Mauna Loa data」「Integrators and automation engineers looking to expose APIs to AI tools"]}


name: AI Personal Assistant with GPT-4o: Email, Calendar, Search & CRM Integration
author_name: Jordan Lee
author_username: jordanlee
categories: []
created_at: 2025-07-01T23:56:27.537Z
updated_at: 2025-07-01T23:56:27.537Z
url: https://n8n.io/workflows/5552
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  This n8n template demonstrates how to use AI as a comprehensive personal assistant with multiple specialized agents.

  Use cases include email management, scheduling, web search, calculations, and more - all automated through AI coordination.

  Good to know
  This template integrates multiple AI services through OpenRouter

  Each agent specializes in different tasks (Gmail, Calendar, Search, etc.)

  Memory persistence maintains context across interactions

  How it works

  The workflow is triggered by Telegram messages (can be replaced with other triggers)

  A router node directs requests to the appropriate specialized agent

  Agents include:

  Gmail for email management

  Calculator for math operations

  Google Search for information retrieval

  Calendar for scheduling

  Contacts for CRM functions

  The OpenRouter Chat Model coordinates responses

  Final responses are sent back through Telegram

  How to use
  Connect your Telegram bot credentials

  Configure each service with appropriate API keys

  The system will automatically route requests to the right agent

  Requirements

  OpenRouter account for AI services

  Telegram bot token

  Google API credentials for relevant services

  Customising this workflow
  Add more specialized agents as needed

  Replace Telegram with other communication channels

  Adjust routing logic for different use cases

nodes_used:
  ["@n8n/n8n-nodes-langchain.toolCalculator","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolSerpApi","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.perplexityTool"]

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metadata_json:
  {"categories":["automation","integration","ai","productivity","communication"],"complexity":"complex","use_cases":["Email management and drafting","Scheduling and calendar management","Web research and information retrieval","CRM/contact lookups and updates","On-the-fly calculations and utilities via chat interface"],"estimated_setup_minutes":60,"required_services":["OpenRouter (GPT-4o) account / API key","Telegram bot token","Google APIs (Gmail, Calendar, Contacts/People) and credentials","SerpApi key (Google Search integration)","Perplexity API key"],"key_features":["Multi-agent router that directs requests to specialized agents (Gmail, Calendar, Search, Contacts, Calculator)","OpenRouter chat model to coordinate agent responses","Memory persistence (buffer window) to maintain context across interactions","Telegram trigger and response channel (replaceable with other channels)","Integrated web search using SerpApi and Perplexity for information retrieval and fact-checking"],"target_audience":["Developers building conversational automations","Productivity-focused professionals and executive assistants","Small business owners and sales reps needing CRM/email automation workflows','Automation engineers and IT admins"]}


name: Automate ASMR Video Creation and Distribution with FalAI and Social Media Integration
author_name: Harrison P
author_username: purhar
categories: []
created_at: 2025-07-02T00:02:39.571Z
updated_at: 2025-07-02T00:02:39.571Z
url: https://n8n.io/workflows/5553
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  🎬 Create Unlimited Viral ASMR Videos — Fully Automated!
  Tired of spending hours brainstorming viral content, writing prompts, and juggling video uploads?

  This powerful n8n workflow automates your entire short-form ASMR video creation process, turning you into a content powerhouse — without burnout or repetitive manual work.

  ✅ No coding required
  ✅ Connects with cutting-edge AI video generation (FalAI)
  ✅ Publishes videos to TikTok, Instagram, YouTube, and more
  ✅ Tracks everything neatly in Google Sheets
  ✅ Ready for customization!

  ✨ How It Works
  Here’s how this workflow becomes your virtual content assistant:

  Brainstorm New Viral ASMR Objects
  Generates a creative, unused idea like:

  Glass Kiwi
  Crystal Banana
  Frozen Watermelon
  Ensures fresh content by checking your Google Sheet for duplicates.

  Generate a Detailed Video Prompt
  Transforms your object idea into a sensory-rich ASMR video script:


  “Imagine a crystal-clear kiwi sliced open, glistening under neon lights…”
  This prompt is crafted to produce hyper-realistic AI visuals perfect for short-form platforms.

  Create the ASMR Video with FalAI
  Sends the prompt to FalAI, an advanced video-generation API.

  Supports vertical aspect ratio for social reels.

  Automatically waits for video processing to complete.

  Save Video Details to Google Sheets
  Adds each new object and video URL to a Google Sheet.

  Maintains a running archive of all your generated videos.

  No more manual tracking or losing track of which videos you’ve already created!

  Upload to Blotato and Publish Across Platforms
  Uploads the video to Blotato’s media hosting service.

  Optionally posts the video automatically to:

  TikTok

  Instagram

  YouTube

  And easily extendable to Facebook, Pinterest, and more!

  Posts your captions, hashtags, and links seamlessly.

  🎯 Why You’ll Love This Workflow
  ✅ Saves hours of creative work and publishing time
  ✅ Eliminates manual uploads and spreadsheets
  ✅ Keeps your content fresh and consistent
  ✅ Highly customizable for new platforms or personal style
  ✅ Includes clear instructions and sticky notes for easy setup

  💬 Need Help?
  If you get stuck:

  Check the included sticky notes in the workflow canvas

  Or search for “N8N Assistant by Nskha” on ChatGPT, and upload your JSON file for personalized support.

  🎉 Supercharge Your Content Creation
  This isn’t just a workflow — it’s a full-scale ASMR content machine ready to scale your viral video production effortlessly. Automate your creativity and free up your time to focus on what matters most!

  ✅ Ready to impress your audience and grow your brand?
  Import this workflow today and start creating viral ASMR magic!

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metadata_json:
  {"categories":["automation","content-creation","social-media","ai-video-generation","integration"],"complexity":"complex","use_cases":["Automated ASMR short-form video generation","Batch-producing and publishing social reels (TikTok, Instagram, YouTube)","Maintaining a content inventory and preventing duplicate ideas","Generating sensory-rich video prompts for AI video generation","Hosting media and cross-posting with automated captions/hashtags"],"estimated_setup_minutes":60,"required_services":["FalAI (AI video generation API)","Blotato (media hosting)","TikTok API","Instagram Graph API / Creator API","YouTube Data API","Google Sheets API","OpenAI or compatible LM API (lmChatOpenAi)"],"key_features":["Automated brainstorming of unique ASMR objects","Duplicate-check against Google Sheets","Transforms ideas into detailed sensory ASMR video prompts","Creates vertical videos via FalAI and polls for processing completion","Saves video metadata and URLs to Google Sheets archive"],"target_audience":["Content creators and ASMR artists","Social media managers and marketers","Small agencies and solopreneurs focused on short-form video growth"]}


name: File Hash Verification for AI Agents with hashlookup CIRCL API
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T00:05:28.154Z
updated_at: 2025-07-02T00:05:28.154Z
url: https://n8n.io/workflows/5554
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 11 hashlookup CIRCL API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community
  Import this workflow into your n8n instance
  Credentials Add hashlookup CIRCL API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the hashlookup CIRCL API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://hashlookup.circl.lu
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (11 total)

  🔧 Bulk (2 endpoints)

  • POST /bulk/md5: Bulk Search MD5 Hashes
  • POST /bulk/sha1: Bulk Search SHA1 Hashes

  🔧 Children (1 endpoints)

  • GET /children/{sha1}/{count}/{cursor}: Return children from a given SHA1.  A number of element to return and an offset must be given. If not set it will be the 100 first elements. A cursor must be given to paginate over. The starting cursor is 0.

  🔧 Info (1 endpoints)

  • GET /info: Get Database Info

  🔧 Lookup (3 endpoints)

  • GET /lookup/md5/{md5}: Lookup MD5.
  • GET /lookup/sha1/{sha1}: Lookup SHA-1.
  • GET /lookup/sha256/{sha256}: Lookup SHA-256.

  🔧 Parents (1 endpoints)

  • GET /parents/{sha1}/{count}/{cursor}: Return parents from a given SHA1. A number of element to return and an offset must be given. If not set it will be the 100 first elements. A cursor must be given to paginate over. The starting cursor is 0.

  🔧 Session (2 endpoints)

  • GET /session/create/{name}: Create a session key to keep search context. The session is attached to a name. After the session is created, the header hashlookup_session can be set to the session name.
  • GET /session/get/{name}: Return set of matching and non-matching hashes from a session.

  🔧 Stats (1 endpoints)

  • GET /stats/top: Get Top Queries

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native hashlookup CIRCL API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

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name: Business Lead Generation with Apify Web Scraping and Google Sheets Storage
author_name: Jordan Lee
author_username: jordanlee
categories: []
created_at: 2025-07-02T00:06:32.693Z
updated_at: 2025-07-02T00:06:32.693Z
url: https://n8n.io/workflows/5555
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  This flexible template scrapes business listings for any industry and location, perfect for sales teams, marketers, and researchers.

  Good to know
  Works with any business category (restaurants, contractors, retailers, etc.)
  Fully customizable search parameters
  Results automatically organized in Google Sheets
  Built-in delay ensures scraping completes before data collection

  How it works

  Trigger: Manual or scheduled start
  Apify Configuration: Sets scraping parameters (industry, location, data fields)
  Scraping Execution: Runs the web scraping job
  Data Processing: Cleans and structures the raw data
  Storage: Saves results to your Google Sheets

  What is Apify?
  Apify is a webscraping tool, in this workflow the data is scraped from a google maps scraper:

  https://apify.com/compass/crawler-google-places

  How to use

  Apify Small # Lead Generation (Purple)

  https://apify.com/compass/crawler-google-places


  Add location and industry to scrape (Apify)
  Add the number of leads to output (Apify)
  Copy over the JSON file into N8N
  Copy & paste API endpoint "Get Run URL" in N8N

  Apify Large # Lead Generation (Grey)

  Configure the Manual Trigger

  When clicking 'Execute workflow' node is ready to use as-is
  This triggers the entire lead generation process

  Setup "Start Results (Apify)" Node
  Get Your Apify API Information

  Go to Apify.com and create a free account
  Navigate to Settings → Integrations → API tokens
  Copy your API token
  Find the Google Maps scraper actor ID:

  Configure the HTTP Request (start results)

  Method: POST
  URL: Replace "enter apify (get run)" with:
  https://api.apify.com/v2/acts/nwua9Gu5YrADL7ZDj/runs?token=YOUR_API_TOKEN


  C. Customize the JSON Body Parameters
  In the JSON body, modify these key fields:
  Location & Search:

  "locationQuery": Change "Toronto" to your target city
  "searchStringsArray": Change ["barber"] to your business type

  Examples: ["restaurants"], ["dentists"], ["contractors"]

  Configure the HTTP Request (start results)
  Method : Get
  Url: enter the get dataset URL from Apify

  Split Out Node
  Select fields to append in the google sheet

  Test the Configuration

  Click Execute workflow to test
  Check that the Apify job starts successfully
  Note the job ID returned for the next section

  This section initiates the scraping process and should complete in 30-60 seconds depending on your lead count.

  Setup Google Sheets

  Create a new Google Sheet with these columns:

  title (business name)
  address (full address)
  state (state/province)
  neighborhood (area/district)
  phone (contact number)
  emails (email addresses)


  Copy your Google Sheets document ID for workflow configuration

  Requirements
  Apify account
  Google Sheets document
  Google OAuth credentials

  Customization Options
  For different use cases:

  Lead Gen: Get business leads
  Local SEO: Collect competitor data
  Market Research: Analyze industry trends

  Advanced mofications:
  Add email enrichment
  Integrate with CRM systems
  Set up automatic daily runs

nodes_used:
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metadata_json:
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name: Audio & Video Data Search and Analysis with Clarify API and AI Agent Integration
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T00:13:52.614Z
updated_at: 2025-07-02T00:13:52.614Z
url: https://n8n.io/workflows/5557
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 21 api.clarify.io API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add api.clarify.io credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the api.clarify.io API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.clarify.io/
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (21 total)

  🔧 V1 (21 endpoints)

  • GET /v1/bundles: Add Media to Track
  • POST /v1/bundles: Create a bundle
  • DELETE /v1/bundles/{bundle_id}: Delete a bundle
  • GET /v1/bundles/{bundle_id}: Get a bundle
  • PUT /v1/bundles/{bundle_id}: Update a bundle
  • GET /v1/bundles/{bundle_id}/insights: Get bundle insights
  • POST /v1/bundles/{bundle_id}/insights: Request an insight to be run
  • GET /v1/bundles/{bundle_id}/insights/{insight_id}: Get bundle insight
  • DELETE /v1/bundles/{bundle_id}/metadata: Delete bundle metadata
  • GET /v1/bundles/{bundle_id}/metadata: Get bundle metadata
  • PUT /v1/bundles/{bundle_id}/metadata: Update bundle metadata
  • DELETE /v1/bundles/{bundle_id}/tracks: Delete bundle tracks
  • GET /v1/bundles/{bundle_id}/tracks: Get bundle tracks
  • POST /v1/bundles/{bundle_id}/tracks: Add a track for a bundle
  • PUT /v1/bundles/{bundle_id}/tracks: Update a tracks for a bundle
  • DELETE /v1/bundles/{bundle_id}/tracks/{track_id}: Delete a bundle track
  • GET /v1/bundles/{bundle_id}/tracks/{track_id}: Get bundle track
  • PUT /v1/bundles/{bundle_id}/tracks/{track_id}: Add media to a track
  • GET /v1/reports/scores: Generate Group Report
  • GET /v1/reports/trends: Generate Trends Report
  • GET /v1/search: Search Bundles

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native api.clarify.io API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

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metadata_json:
  {"categories":["integration","automation","data processing","AI","media"],"complexity":"medium","use_cases":["Expose Clarify API as an MCP tool for AI agents","Search and analyze audio/video bundles","Generate group and trends reports from media data","Automate ingestion and management of media tracks and metadata","Integrate AI agents (Claude, Cursor, custom apps) with Clarify operations"],"estimated_setup_minutes":20,"required_services":["Clarify API (api.clarify.io) - API key/credentials","n8n instance (hosted or self-hosted)","AI agent or client that supports MCP/webhook tool integration (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["MCP trigger exposing 21 Clarify API endpoints (v1 bundles, tracks, insights, reports, search)","Automatic parameter population via $fromAI() expressions","Native n8n HTTP Request nodes returning Clarify responses","Built-in HTTP error handling and logging","Zero/low configuration required to connect AI agents via MCP webhook URL (SSE support where applicable)"],"target_audience":["developers","AI engineers","data analysts / media analysts"]}


name: Team Knowledge Management with Google Docs, Discord, and AI Assistant
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T01:10:26.154Z
updated_at: 2025-07-02T01:10:26.154Z
url: https://n8n.io/workflows/5560
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Let’s activate your org’s memory:

  📝 Set Storage

  Open "Edit Fields" → Replace sheet_id with your Google Doc URL.

  🤖 Connect Discord

  Update discord_server_id, channel_id, and user_id (for DMs).

  🧠 Route Commands
  Call these from other workflows:
  save_memory: Log new data.
  retrieve_memory: Fetch history.
  send_memories_to_gmail: Discord summaries.

  🤖 Custom Formatting
  Edit the AI Agent prompt to style Discord messages.

  💡 Pro Tip: Pair this with an MCP Server for full issue→memory→action automation!

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

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nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.googleDocs","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.googleDocs","n8n-nodes-base.switch","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.mcpTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleDocs","n8n-nodes-base.discordTool","n8n-nodes-base.discordTool"]

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metadata_json:
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name: Expose eBay Browse API for AI Agents with MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T01:25:43.233Z
updated_at: 2025-07-02T01:25:43.233Z
url: https://n8n.io/workflows/5563
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 11 Browse API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Browse API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com/buy/browse/v1
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (11 total)

  🔧 Item (5 endpoints)

  • GET /item/: Check Item Compatibility
  • GET /item/get_item_by_legacy_id: Get Get Item By Legacy Id
  • GET /item/get_items_by_item_group: This method retrieves the details of the individual items in an item group
  • GET /item/{item_id}: Get {Item Id}
  • POST /item/{item_id}/check_compatibility: This method checks if a product is compatible with the specified item

  🔧 Item_Summary (2 endpoints)

  • GET /item_summary/search: Search Items by Image
  • POST /item_summary/search_by_image: This is an Experimental method

  🔧 Shopping_Cart (4 endpoints)

  • GET /shopping_cart/: Update Cart Item Quantity
  • POST /shopping_cart/add_item: This is an Experimental method
  • POST /shopping_cart/remove_item: This is an experimental method
  • POST /shopping_cart/update_quantity: This is an experimental method

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Browse API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","e-commerce","AI integration"],"complexity":"medium","use_cases":["Allow AI agents to query eBay item/catalog data","Enable AI-driven shopping cart operations","Expose eBay Browse API as a tool endpoint for agent frameworks (MCP)","Image-based item search for agents","Rapidly prototype AI-to-eBay interactions for apps or assistants"],"estimated_setup_minutes":20,"required_services":["n8n instance with MCP trigger available","eBay Buy API (Browse API) credentials / eBay developer account","AI agent or client that supports MCP (e.g., Claude Desktop, Cursor, custom agents)"],"key_features":["Exposes 11 eBay Browse API operations via an MCP server endpoint","Automatic parameter population using $fromAI() expressions","Returns native Browse API responses directly to agents","Supports item lookups, image search, and shopping cart operations (including experimental endpoints)","Built-in n8n HTTP request error handling and logging for production use"],"target_audience":["developers","AI engineers","automation engineers, integration specialists"]}


name: Connect AI Agents to eBay Deal API with MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T02:30:35.403Z
updated_at: 2025-07-02T02:30:35.403Z
url: https://n8n.io/workflows/5564
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 4 Deal API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Deal API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (4 total)

  🔧 Deal_Item (1 endpoints)

  • GET /deal_item: List Deal Items

  🔧 Event (2 endpoints)

  • GET /event: List Event Items
  • GET /event/{event_id}: This method retrieves the details for an eBay event

  🔧 Event_Item (1 endpoints)

  • GET /event_item: This method returns a paginated set of event items

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Deal API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","AI agents","e-commerce","API gateway","automation"],"complexity":"medium","use_cases":["Expose eBay Deal API endpoints to AI agents via an MCP server","Allow AI agents to list deal items, events and event items","Rapidly prototype AI tools that call eBay Deal endpoints (Claude, Cursor, custom apps)","Provide a managed webhook/MCP endpoint for AI-driven workflows","Extend or customize Deal API behavior with n8n logic"],"estimated_setup_minutes":20,"required_services":["n8n instance (cloud or self-hosted)","eBay Deal API credentials (api.ebay.com)","AI agent(s) that support MCP (e.g., Claude Desktop, Cursor, custom MCP clients)"],"key_features":["MCP Trigger acting as server endpoint for AI agents","Four exposed Deal API operations (deal_item, event list/detail, event_item)","HTTP Request nodes calling https://api.ebay.com{basePath}","AI-driven parameter population via $fromAI() expressions","Native Deal API responses returned to agents (no extra mapping required)"],"target_audience":["developers building AI integrations","automation / integration engineers","AI builders creating agent tools for e-commerce data access (eBay deals/events)"]}


name: Expose eBay Taxonomy API to AI Agents for Category Management
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T02:36:20.986Z
updated_at: 2025-07-02T02:36:20.986Z
url: https://n8n.io/workflows/5565
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 8 Taxonomy API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Taxonomy API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com/commerce/taxonomy/v1
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (8 total)

  🔧 Category_Tree (7 endpoints)

  • GET /category_tree/{category_tree_id}: Get a Category Tree
  • GET /category_tree/{category_tree_id}/fetch_item_aspects: Get Aspects for All Leaf Categories in a Marketplace
  • GET /category_tree/{category_tree_id}/get_category_subtree: Get a Category Subtree
  • GET /category_tree/{category_tree_id}/get_category_suggestions: Get Suggested Categories
  • GET /category_tree/{category_tree_id}/get_compatibility_properties: Get Compatibility Properties
  • GET /category_tree/{category_tree_id}/get_compatibility_property_values: Get Compatibility Property Values
  • GET /category_tree/{category_tree_id}/get_item_aspects_for_category: Get Get Item Aspects For Category

  🔧 Get_Default_Category_Tree_Id (1 endpoints)

  • GET /get_default_category_tree_id: Fetch Default Category Tree ID

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Taxonomy API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","e-commerce","AI agent integration","API gateway"],"complexity":"medium","use_cases":["Expose eBay Taxonomy endpoints to AI agents","Automate category lookup and suggestions for listings","Retrieve category trees, item aspects and compatibility properties","Integrate AI assistants (Claude, Cursor, custom) for category management","Build tooling for marketplace listing classification"],"estimated_setup_minutes":200,"required_services":["eBay Taxonomy API (api.ebay.com)","n8n instance with MCP support","AI agents or clients that support MCP (e.g., Claude, Cursor, custom agents)","Valid eBay API credentials (OAuth)"],"key_features":["MCP trigger exposing 8 Taxonomy API operations via webhook","Supports GET endpoints for category trees, suggestions, item aspects and compatibility data","AI-ready parameter binding using $fromAI() expressions","Native n8n HTTP Request nodes with built-in error handling and logging","Returns native eBay Taxonomy API responses to agents (no extra mapping)`,`Easily extensible workflow for adding custom logic or endpoints"],"target_audience":["Developers and integration engineers","Marketplace/product managers and e‑commerce teams","AI/ML engineers building agent tools for commerce workflows"]}


name: Search and Retrieve eBay Product Data with Catalog API for AI Agents
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T02:43:42.731Z
updated_at: 2025-07-02T02:43:42.731Z
url: https://n8n.io/workflows/5566
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 Catalog API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the Catalog API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Product (1 endpoints)

  • GET /product/{epid}: Get {Epid}

  🔧 Product_Summary (1 endpoints)

  • GET /product_summary/search: Search Product Summaries

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Catalog API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","data retrieval","AI integration","API server"],"complexity":"simple","use_cases":["Allow AI agents to fetch eBay product details by EPID","Search eBay product summaries for discovery or matching","Expose eBay Catalog API as an MCP tool for LLM/agent integrations","Prototype AI tools that need live product data from eBay"],"estimated_setup_minutes":298,"required_services":["eBay Catalog API (api.ebay.com)","n8n instance (self-hosted or n8n cloud)","AI agent or client that supports MCP (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["MCP trigger exposes Catalog API operations as agent-accessible endpoints","Two ready endpoints: GET /product/{epid} and GET /product_summary/search","AI-ready parameter binding via $fromAI() expressions","Native HTTP request nodes return full Catalog API responses","Built-in HTTP error handling and n8n logging for requests/responses (production-ready)"],"target_audience":["developers","AI/agent integrators","e-commerce engineers/analysts experimenting with product data integrations"]}


name: AI Agent Integration with eBay Buy Marketing API
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T02:46:16.330Z
updated_at: 2025-07-02T02:46:16.330Z
url: https://n8n.io/workflows/5567
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 1 Buy Marketing API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add Buy Marketing API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the Buy Marketing API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com/buy/marketing/v1_beta
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (1 total)

  🔧 Merchandised_Product (1 endpoints)

  • GET /merchandised_product: Fetch Merchandised Products

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Buy Marketing API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","AI integration","e-commerce"],"complexity":"simple","use_cases":["Expose eBay Buy Marketing API to AI agents as a tool endpoint","Fetch merchandised product data for AI-driven workflows","Prototype AI-to-API integrations quickly","Integrate AI agents (Claude, Cursor, custom) with eBay marketing data","Provide a webhook/MCP server for custom AI apps to call eBay"],"estimated_setup_minutes":20,"required_services":["n8n instance (hosted or self-hosted)","eBay Buy Marketing API credentials (api.ebay.com)","Publicly reachable webhook endpoint (for MCP trigger) or tunneling service","AI agent or platform (e.g., Claude, Cursor, custom AI apps) to consume the MCP URL"],"key_features":["MCP trigger exposes a server endpoint that AI agents can call","HTTP Request nodes proxy calls to https://api.ebay.com/buy/marketing/v1_beta","AI-driven parameter population via $fromAI() expressions","Returns native Buy Marketing API responses directly to agents","Built-in HTTP request error handling and n8n logging/tracing supportable in workflows/activations/edits for extensibility"],"target_audience":["developers","AI integrators / ML engineers","e-commerce engineers and platform teams (marketing/ops specialists who need product lists/data accessible to AI tools)"]}


name: Create an eBay Item Feed Service API Gateway for AI Agents
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T02:55:10.989Z
updated_at: 2025-07-02T02:55:10.989Z
url: https://n8n.io/workflows/5568
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 4 Item Feed Service API operations to AI agents.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add Item Feed Service credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the Item Feed Service API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com/buy/feed/v1_beta
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (4 total)

  🔧 Item (1 endpoints)

  • GET /item: Download Hourly Snapshot Feed

  🔧 Item_Group (1 endpoints)

  • GET /item_group: Get Item Group

  🔧 Item_Priority (1 endpoints)

  • GET /item_priority: Get Item Priority

  🔧 Item_Snapshot (1 endpoints)

  • GET /item_snapshot: Get Item Snapshot

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Item Feed Service API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["integration","API gateway","automation","AI agent tooling","e-commerce"],"complexity":"medium","use_cases":["Expose eBay Item Feed endpoints to AI agents via MCP","Allow AI assistants (Claude, Cursor, custom apps) to query item feeds and snapshots","Fetch hourly snapshot feeds for inventory synchronization or analytics","Proxy and log eBay Feed API calls with built-in error handling","Extend or customize feed-related logic inside n8n workflows"],"estimated_setup_minutes":20,"required_services":["n8n instance (with MCP trigger capability)","eBay Buy Feed API (https://api.ebay.com/buy/feed/v1_beta) and credentials","AI agent or platform to consume MCP endpoints (e.g., Claude, Cursor, custom agents)"],"key_features":["MCP server endpoint to serve AI agents","4 exposed GET operations: /item, /item_group, /item_priority, /item_snapshot","HTTP Request nodes calling eBay Feed API","AI-ready $fromAI() expressions to auto-populate parameters","Native response passthrough and built-in HTTP error handling/logging in n8n"],"target_audience":["developers building AI tools","AI engineers integrating external APIs","n8n users and workflow builders familiar with MCP triggers and webhooks"]}


name: eBay Analytics API Rate Limit Monitoring for AI Agents
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T03:41:47.580Z
updated_at: 2025-07-02T03:41:47.580Z
url: https://n8n.io/workflows/5570
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 Analytics API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the Analytics API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Rate_Limit (1 endpoints)

  • GET /rate_limit/: Retrieve Application Rate Limits

  🔧 User_Rate_Limit (1 endpoints)

  • GET /user_rate_limit/: Retrieve User Rate Limits

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Analytics API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  [encoded data, 4244 characters]

metadata_json:
  {"categories":["integration","monitoring","ai-integration","developer-tools"],"complexity":"medium","use_cases":["Expose eBay Analytics API rate limits to AI agents","Realtime rate-limit checks for agent orchestration","Integrate eBay rate-limit info into AI apps or workflows","Build observability/usage tooling for eBay API consumption"],"estimated_setup_minutes":200,"required_services":["eBay Analytics API (developer account / credentials)","n8n instance (with MCP trigger node)","Publicly reachable webhook or tunneling service (if self-hosted)","MCP-capable AI agents or clients (e.g., Claude Desktop, Cursor)"],"key_features":["MCP server endpoint for AI agents (MCP trigger)","Two Analytics API operations: GET /rate_limit and GET /user_rate_limit","Automatic parameter population via $fromAI() expressions","Native n8n HTTP Request nodes with built-in error handling and logging","Returns native Analytics API responses to agents unchanged (no mapping)"],"target_audience":["developers","AI engineers","automation engineers/platform engineers who integrate AI agents with APIs"]}


name: eBay Seller Account Management with AI Agent Integration (36 operations)
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T03:46:37.835Z
updated_at: 2025-07-02T03:46:37.835Z
url: https://n8n.io/workflows/5571
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  ⚠️ ADVANCED USE ONLY - Account MCP Server (36 operations)

  🚨 This workflow is for advanced users only!

  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  This MCP server contains 36 operations which is significantly more than the recommended maximum of tools for most AI clients.

  🔍 Recommended Alternative for basic use cases
  Seek a simplified MCP server that utilizes the official n8n tool implementation for Account if available, or an MCP server with only common operations as it will be more efficient and easier to manage.

  🛠️ Advanced Usage Requirements

  BEFORE adding this MCP server to your client:
  Disable or delete unused nodes - Review sections and disable/delete those you don't need

  AFTER adding the MCP server to your client:
  1.Selective tool enabling - Instead of enabling all tools (default), manually select only the specific tools you need for that Workflow's MCP client.
  Monitor performance - Too many tools can slow down AI responses

  💡 Pro Tips
  Keep maximum 40 enabled tools - Most AI clients perform better with fewer tools
  Group related operations and only enable one group at a time
  Use the overview note to understand what each operation group does

  Ping me on discord if your business needs this implemented professionally
  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Account API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (36 total)

  🔧 Advertising_Eligibility (1 endpoints)

  • GET /advertising_eligibility: Check Advertising Eligibility

  🔧 Custom_Policy (4 endpoints)

  • GET /custom_policy/: Update Custom Policy
  • POST /custom_policy/: Create/Search Custom Policy
  • GET /custom_policy/{custom_policy_id}: Get {Custom Policy Id}
  • PUT /custom_policy/{custom_policy_id}: Update {Custom Policy Id}

  🔧 Fulfillment_Policy (6 endpoints)

  • GET /fulfillment_policy: Update Fulfillment Policy
  • POST /fulfillment_policy/: Create/Search Fulfillment Policy
  • GET /fulfillment_policy/get_by_policy_name: This method retrieves the details for a specific fulfillment policy
  • DELETE /fulfillment_policy/{fulfillmentPolicyId}: This method deletes a fulfillment policy
  • GET /fulfillment_policy/{fulfillmentPolicyId}: This method retrieves the complete details of a fulfillment policy
  • PUT /fulfillment_policy/{fulfillmentPolicyId}: This method updates an existing fulfillment policy

  🔧 Kyc (1 endpoints)

  • GET /kyc: Check KYC Status

  🔧 Payment_Policy (6 endpoints)

  • GET /payment_policy: Update Payment Policy
  • POST /payment_policy: Create/Search Payment Policy
  • GET /payment_policy/get_by_policy_name: This method retrieves the details of a specific payment policy
  • DELETE /payment_policy/{payment_policy_id}: This method deletes a payment policy
  • GET /payment_policy/{payment_policy_id}: This method retrieves the complete details of a payment policy
  • PUT /payment_policy/{payment_policy_id}: This method updates an existing payment policy

  🔧 Payments_Program (2 endpoints)

  • GET /payments_program/{marketplace_id}/{payments_program_type}: Get {Payments Program Type}
  • GET /payments_program/{marketplace_id}/{payments_program_type}/onboarding: Get Onboarding

  🔧 Privilege (1 endpoints)

  • GET /privilege: Get Seller Privileges

  🔧 Program (3 endpoints)

  • GET /program/get_opted_in_programs: List Opted-In Programs
  • POST /program/opt_in: Opt In to Program
  • POST /program/opt_out: Opt Out of Program

  🔧 Rate_Table (1 endpoints)

  • GET /rate_table: List Shipping Rate Tables

  🔧 Return_Policy (6 endpoints)

  • GET /return_policy: Update Return Policy
  • POST /return_policy: Create/Search Return Policy
  • GET /return_policy/get_by_policy_name: This method retrieves the details of a specific return policy
  • DELETE /return_policy/{return_policy_id}: This method deletes a return policy
  • GET /return_policy/{return_policy_id}: Get {Return Policy Id}
  • PUT /return_policy/{return_policy_id}: This method updates an existing return policy

  🔧 Sales_Tax (4 endpoints)

  • GET /sales_tax: Update Sales Tax Rate
  • DELETE /sales_tax/{countryCode}/{jurisdictionId}: This call deletes a sales tax table entry for a jurisdiction
  • GET /sales_tax/{countryCode}/{jurisdictionId}: This call gets the current sales tax table entry for a specific tax jurisdiction
  • PUT /sales_tax/{countryCode}/{jurisdictionId}: This method creates or updates a sales tax table entry for a jurisdiction

  🔧 Subscription (1 endpoints)

  • GET /subscription: List Subscriptions

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Account API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","e-commerce","AI agent","API management"],"complexity":"complex","use_cases":["Automate eBay seller account management (policies, returns, payments, fulfillment)","Expose eBay Account API as an MCP toolset for AI agents","Manage sales tax, rate tables and seller privileges programmatically","Check KYC and advertising eligibility and handle onboarding/program opt-in/out","Enable AI-driven parameter population and native response passthrough for agents"],"estimated_setup_minutes":20,"required_services":["eBay Account API (api.ebay.com)","n8n instance with webhook access","eBay developer credentials / OAuth tokens","MCP-compatible AI agent or client (e.g., Claude, Cursor, custom AI)","Internet access for API calls"],"key_features":["36 exposed Account API operations (policies, tax, programs, KYC, etc.)","MCP trigger acting as server endpoint for AI agents","HTTP Request nodes to call eBay endpoints with native responses","AI expressions ($fromAI()) to auto-populate parameters","Selective tool enabling recommended to limit enabled operations for performance\nBuilt-in n8n HTTP error handling and logging\nQuick import/activate flow with webhook URL for agent connections"],"target_audience":["Advanced users and developers","System integrators managing eBay seller accounts","E-commerce operations teams and sellers with technical support teams involved in automation implementations\",\"AI engineers building agent integrations for marketplace management"]}


name: Connect AI Agents to eBay Seller Metrics API via MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T03:55:13.693Z
updated_at: 2025-07-02T03:55:13.693Z
url: https://n8n.io/workflows/5572
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 4  Seller Service Metrics API  API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add  Seller Service Metrics API  credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the  Seller Service Metrics API  API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (4 total)

  🔧 Customer_Service_Metric (1 endpoints)

  • GET /customer_service_metric/{customer_service_metric_type}/{evaluation_type}: Get {Evaluation Type}

  🔧 Seller_Standards_Profile (2 endpoints)

  • GET /seller_standards_profile: Get Seller Standards Profile
  • GET /seller_standards_profile/{program}/{cycle}: This call retrieves a single standards profile for the associated seller

  🔧 Traffic_Report (1 endpoints)

  • GET /traffic_report: Retrieve Listing Traffic Report

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native  Seller Service Metrics API  API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","AI integration","API gateway"],"complexity":"medium","use_cases":["Allow AI agents to query eBay seller metrics (standards, traffic, customer service)","Automated reporting and monitoring of seller performance","Enable conversational AI tools to fetch real-time seller data","Prototype or extend custom agent tools using eBay metrics endpoints"],"estimated_setup_minutes":20,"required_services":["n8n instance (hosted or self-managed)","eBay Seller Service Metrics API credentials (eBay developer account, OAuth tokens)","AI agents or platforms that support MCP (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["MCP server endpoint (MCP Trigger) exposing 4 Seller Service Metrics API operations","GET endpoints for customer service metric, seller standards profile, and traffic report","Automatic parameter population via $fromAI() expressions for AI-driven requests","Native n8n HTTP request handling and built-in error management","Returns native API responses directly to calling AI agents (no extra mapping needed)"],"target_audience":["developers building AI agent integrations","AI engineers and prompt engineers","e-commerce operators and seller analysts wanting programmatic access to metrics"]}


name: Connect AI Agents to eBay Compliance API for Listing Violation Management
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T03:57:05.409Z
updated_at: 2025-07-02T03:57:05.409Z
url: https://n8n.io/workflows/5573
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 3 Compliance API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the Compliance API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (3 total)

  🔧 Listing_Violation (1 endpoints)

  • GET /listing_violation: Get Violation Summary Counts

  🔧 Listing_Violation_Summary (1 endpoints)

  • GET /listing_violation_summary: This call returns listing violation counts for a seller

  🔧 Suppress_Listing_Violation (1 endpoints)

  • POST /suppress_listing_violation: Suppress Listing Violation

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Compliance API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","compliance","AI integration"],"complexity":"medium","use_cases":["Automate eBay listing violation retrieval and suppression","Provide an MCP-compatible API endpoint for AI agents","Integrate AI agents (Claude, Cursor, custom) to manage seller compliance workflows","Expose Compliance API operations to other apps or bots"],"estimated_setup_minutes":20,"required_services":["eBay Compliance API (api.ebay.com)","n8n instance with public webhook access","AI agents or platforms (e.g., Claude, Cursor, custom AI apps)","Valid eBay Compliance API credentials"],"key_features":["MCP server endpoint (MCP Trigger) to accept AI agent requests","Three exposed Compliance API operations: GET /listing_violation, GET /listing_violation_summary, POST /suppress_listing_violation","Automatic parameter population via $fromAI() AI expressions","Native n8n HTTP Request handling with built-in error management and logging","Returns full, native Compliance API responses to the invoking agent','Easily extensible to add custom logic or additional endpoints"],"target_audience":["Developers integrating eBay APIs","Platform engineers building AI-enabled tools","Marketplace compliance teams automating violation management workflows」「AI application builders wanting a tool endpoint for agents"]}


name: AI Agent Integration for eBay Logistics API with MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:00:00.239Z
updated_at: 2025-07-02T04:00:00.239Z
url: https://n8n.io/workflows/5574
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 6 Logistics API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Logistics API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (6 total)

  🔧 Shipment (4 endpoints)

  • POST /shipment/create_from_shipping_quote: Create Shipment from Quote
  • GET /shipment/{shipmentId}: This method retrieves the shipment details for the specified shipment ID
  • POST /shipment/{shipmentId}/cancel: Create/Search Cancel
  • GET /shipment/{shipmentId}/download_label_file: Get Download Label File

  🔧 Shipping_Quote (2 endpoints)

  • POST /shipping_quote: Retrieve Shipping Quote
  • GET /shipping_quote/{shippingQuoteId}: Get {Shippingquoteid}

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Logistics API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","e-commerce","ai-integration"],"complexity":"medium","use_cases":["Expose eBay Logistics API endpoints to AI agents","Create shipments from shipping quotes via AI","Retrieve shipment and shipping quote details","Download shipping label files programmatically","Cancel shipments through AI-driven workflows"],"estimated_setup_minutes":20,"required_services":["n8n instance (self-hosted or n8n cloud)","eBay Developer account with Logistics API credentials","Publicly reachable webhook endpoint (or n8n cloud webhook)","MCP-compatible AI agents or clients (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["MCP trigger exposes 6 Logistics API operations to AI agents","HTTP Request nodes perform calls to https://api.ebay.com{basePath}","AI parameter binding via $fromAI() expressions for path, query, body, headers","Returns native Logistics API responses directly to the agent","Built-in HTTP error handling and n8n logging/monitoring support"],"target_audience":["Developers integrating AI with eBay shipping","AI app builders and bot authors","E-commerce operations and logistics teams automating fulfillment tasks"]}


name: Create eBay Listing Drafts with AI Agents via MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:15:32.678Z
updated_at: 2025-07-02T04:15:32.678Z
url: https://n8n.io/workflows/5575
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 1 Listing API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the Listing API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (1 total)

  🔧 Item_Draft (1 endpoints)

  • POST /item_draft/: Create eBay Listing Draft

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Listing API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","e-commerce","AI-integration"],"complexity":"medium","use_cases":["Create eBay listing drafts via AI agents","Expose eBay Listing API as an MCP tool for agent-driven workflows","Rapid prototyping of AI-driven seller assistants","Automated marketplace listing generation from AI prompts"],"estimated_setup_minutes":20,"required_services":["eBay Listing API (api.ebay.com) — Listing API credentials","n8n instance with MCP trigger enabled","MCP-capable AI agent or client (e.g., Claude Desktop, Cursor, custom AI apps)","Public webhook access (or tunnel) for the MCP trigger"],"key_features":["MCP trigger exposes POST /item_draft endpoint to AI agents","Automatically populated parameters using $fromAI() expressions","Direct HTTP requests to eBay Listing API with native responses","Built-in HTTP error handling and n8n logging","Extensible workflow for adding custom logic or endpoints"],"target_audience":["Developers building AI integrations","e-commerce operators and marketplace sellers","Automation engineers and DevOps implementing agent tools"]}


name: eBay Fulfillment API Operations for AI Agents with MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:16:43.968Z
updated_at: 2025-07-02T04:16:43.968Z
url: https://n8n.io/workflows/5576
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:34
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 15 Fulfillment API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Fulfillment API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (15 total)

  🔧 Order (6 endpoints)

  • GET /order: Retrieve Fulfillment Details
  • GET /order/{orderId}: Get {Orderid}
  • GET /order/{orderId}/shipping_fulfillment: Get Shipping Fulfillment
  • POST /order/{orderId}/shipping_fulfillment: Create/Search Shipping Fulfillment
  • GET /order/{orderId}/shipping_fulfillment/{fulfillmentId}: Get {Fulfillmentid}
  • POST /order/{order_id}/issue_refund: Issue Refund

  🔧 Payment_Dispute (8 endpoints)

  • GET /payment_dispute/{payment_dispute_id}: Get Payment Dispute Details
  • POST /payment_dispute/{payment_dispute_id}/accept: Accept Payment Dispute
  • GET /payment_dispute/{payment_dispute_id}/activity: Get Payment Dispute Activity
  • POST /payment_dispute/{payment_dispute_id}/add_evidence: Add an Evidence File
  • POST /payment_dispute/{payment_dispute_id}/contest: Contest Payment Dispute
  • GET /payment_dispute/{payment_dispute_id}/fetch_evidence_content: Get Payment Dispute Evidence File
  • POST /payment_dispute/{payment_dispute_id}/update_evidence: Update evidence
  • POST /payment_dispute/{payment_dispute_id}/upload_evidence_file: Upload an Evidence File

  🔧 Payment_Dispute_Summary (1 endpoints)

  • GET /payment_dispute_summary: Search Payment Disputes

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Fulfillment API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","AI","e-commerce","api-gateway"],"complexity":"medium","use_cases":["Expose eBay Fulfillment API to AI agents","Automate order retrieval and shipping fulfillment","Manage payment disputes and evidence uploads","Allow AI agents to issue refunds and contest disputes","Provide a tool endpoint/MCP server for AI tool integrations"],"estimated_setup_minutes":200,"required_services":["eBay Fulfillment API (api.ebay.com)","n8n instance with MCP trigger enabled","Publicly reachable webhook/host for the MCP endpoint","AI agent/platform (e.g., Claude, Cursor, custom AI apps)","eBay API credentials (OAuth/API keys)"],"key_features":["Implements 15 Fulfillment API endpoints (orders, shipping fulfillments, refunds, payment disputes)","MCP-compatible trigger to serve AI agents as a tool endpoint","Automatic parameter population via $fromAI() expressions","Native n8n HTTP Request nodes with built-in error handling and logging","Returns native Fulfillment API responses to AI agents unchanged (full data structure)"],"target_audience":["Developers integrating eBay with AI agents","AI integrators building agent tool endpoints","E-commerce engineers/operators handling orders and disputes by automation teams"]}


name: [eBay] Recommendation API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:19:02.212Z
updated_at: 2025-07-02T04:19:02.212Z
url: https://n8n.io/workflows/5577
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 1 Recommendation API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the Recommendation API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (1 total)

  🔧 Find (1 endpoints)

  • POST /find: Get Promoted Listings Recommendations

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Recommendation API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
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metadata_json:
  {"categories":["integration","automation","AI integration","ecommerce","API proxy"],"complexity":"simple","use_cases":["Expose eBay Recommendation API to AI agents","Provide Promoted Listings recommendations via MCP","Enable AI agents (Claude, Cursor, custom apps) to call eBay endpoints","Rapid prototyping of agent-accessible ecommerce recommendations","Integrate recommendation responses into downstream workflows"],"estimated_setup_minutes":200,"required_services":["n8n instance","eBay Developer account (Recommendation API credentials)","AI agent or client supporting MCP (e.g., Claude Desktop, Cursor)"],"key_features":["MCP trigger serving as AI agent endpoint","HTTP Request nodes calling https://api.ebay.com{basePath}","Automatic parameter population via $fromAI() expressions","Native Recommendation API response passthrough","Built-in HTTP error handling and n8n logging"],"target_audience":["developers","AI integrators","automation engineers」「ecommerce product/marketing managers"]}


name: Complete eBay Feed API Integration for AI Agents with MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:21:53.760Z
updated_at: 2025-07-02T04:21:53.760Z
url: https://n8n.io/workflows/5578
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 23 Feed API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Feed API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (23 total)

  🔧 Customer_Service_Metric_Task (3 endpoints)

  • GET /customer_service_metric_task: Get Customer Service Metric Task
  • POST /customer_service_metric_task: Create/Search Customer Service Metric Task
  • GET /customer_service_metric_task/{task_id}: Get {Task Id}

  🔧 Inventory_Task (3 endpoints)

  • GET /inventory_task: Get Inventory Task
  • POST /inventory_task: Create/Search Inventory Task
  • GET /inventory_task/{task_id}: Get {Task Id}

  🔧 Order_Task (3 endpoints)

  • GET /order_task: Get Order Task
  • POST /order_task: Create/Search Order Task
  • GET /order_task/{task_id}: This method retrieves the task details and status of the specified task

  🔧 Schedule (6 endpoints)

  • GET /schedule: Get Schedule Template
  • POST /schedule: Create/Search Schedule
  • DELETE /schedule/{schedule_id}: This method deletes an existing schedule
  • GET /schedule/{schedule_id}: This method retrieves schedule details and status of the specified schedule
  • PUT /schedule/{schedule_id}: This method updates an existing schedule
  • GET /schedule/{schedule_id}/download_result_file: This method downloads the latest result file generated by the schedule

  🔧 Schedule_Template (2 endpoints)

  • GET /schedule_template: Get Schedule Template
  • GET /schedule_template/{schedule_template_id}: This method retrieves the details of the specified template

  🔧 Task (6 endpoints)

  • GET /task: Upload Task File
  • POST /task: This method creates an upload task or a download task without filter criteria
  • GET /task/{task_id}: This method retrieves the details and status of the specified task
  • GET /task/{task_id}/download_input_file: Get Download Input File
  • GET /task/{task_id}/download_result_file: Get Download Result File
  • POST /task/{task_id}/upload_file: Create/Search Upload File

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Feed API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

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metadata_json:
  {"categories":["integration","automation","AI integration","API gateway"],"complexity":"complex","use_cases":["Expose eBay Feed API to AI agents (MCP)","Automate creation and monitoring of eBay feed tasks and schedules","Enable AI-driven parameter population for Feed API calls","Upload/download task files and retrieve result files","Integrate eBay Feed operations into custom AI apps or assistants"],"estimated_setup_minutes":20,"required_services":["eBay Developer account (Feed API credentials)","n8n instance (self-hosted or n8n cloud)","Publicly reachable endpoint or tunnel for MCP webhook","AI agents/clients (e.g., Claude, Cursor, custom apps)"],"key_features":["MCP trigger acting as server endpoint for AI agents","Implements 23 Feed API operations across tasks, schedules, templates, and metrics","Automatic $fromAI() expressions for parameter population","Native n8n HTTP Request nodes returning Feed API responses","File upload/download endpoints for tasks and schedules result files"],"target_audience":["Developers","AI engineers building agent integrations","Integration/automation engineers for e-commerce platforms','E-commerce managers who need automated feed processing"]}


name: [eBay] Metadata API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:45:32.537Z
updated_at: 2025-07-02T04:45:32.537Z
url: https://n8n.io/workflows/5579
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 8 Metadata API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Metadata API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (8 total)

  🔧 Country (1 endpoints)

  • GET /country/{countryCode}/sales_tax_jurisdiction: Get Sales Tax Jurisdiction

  🔧 Marketplace (7 endpoints)

  • GET /marketplace/{marketplace_id}/get_automotive_parts_compatibility_policies: Get Get Automotive Parts Compatibility Policies
  • GET /marketplace/{marketplace_id}/get_extended_producer_responsibility_policies: Get Get Extended Producer Responsibility Policies
  • GET /marketplace/{marketplace_id}/get_hazardous_materials_labels: Get Get Hazardous Materials Labels
  • GET /marketplace/{marketplace_id}/get_item_condition_policies: Get Get Item Condition Policies
  • GET /marketplace/{marketplace_id}/get_listing_structure_policies: Get Get Listing Structure Policies
  • GET /marketplace/{marketplace_id}/get_negotiated_price_policies: Get Get Negotiated Price Policies
  • GET /marketplace/{marketplace_id}/get_return_policies: Get Get Return Policies

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Metadata API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

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metadata_json:
  {"categories":["integration","automation","AI agent tooling","e-commerce"],"complexity":"medium","use_cases":["Expose eBay Metadata API to AI agents (MCP)","Allow AI agents to query marketplace/country metadata","Build custom AI tools that need eBay policy/condition/return info","Prototype or productionize agent-accessible API endpoints"],"estimated_setup_minutes":20,"required_services":["eBay Metadata API (api.ebay.com)","n8n instance with public webhook access","eBay API credentials (OAuth)","AI agent/platforms that support MCP (e.g., Claude, Cursor, custom agents)"],"key_features":["MCP-compatible server exposing 8 Metadata API endpoints","Automatic $fromAI() parameter population for path/query/body/headers","Native n8n HTTP Request nodes for direct API calls and error handling","Returns native Metadata API responses to AI agents","Supports SSE/webhook-style agent connections (MCP) and is easily extensible"],"target_audience":["n8n users and workflow builders","Developers building AI agents and integrations","E-commerce engineers and marketplace integrators working with eBay APIs"]}


name: [eBay] Negotiation API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:49:07.801Z
updated_at: 2025-07-02T04:49:07.801Z
url: https://n8n.io/workflows/5580
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 Negotiation API operations to AI agents.

  ⚡ Quick Setup
  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community
  Import this workflow into your n8n instance
  Credentials Add Negotiation API credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the Negotiation API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath}
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Find_Eligible_Items (1 endpoints)

  • GET /find_eligible_items: Find Eligible Listings

  🔧 Send_Offer_To_Interested_Buyers (1 endpoints)

  • POST /send_offer_to_interested_buyers: Send Discount Offer

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Negotiation API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
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metadata_json:
  {"categories":["integration","e-commerce","automation","AI integration"],"complexity":"medium","use_cases":["Expose eBay Negotiation API as a tool endpoint for AI agents","Automatically find eligible listings for offers","Send discount offers to interested buyers via AI-driven workflows","Prototype or deploy AI agents that interact with marketplace negotiation flows","Extend or embed custom logic around eBay negotiation operations"],"estimated_setup_minutes":20,"required_services":["eBay Negotiation API credentials (api.ebay.com)","n8n instance with webhook access","Publicly reachable webhook URL or tunnel (ngrok, Cloudflare Tunnel) for MCP trigger","AI agent or client that supports MCP (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["MCP trigger serving as server endpoint for AI agents","Exposes two Negotiation API operations: Find Eligible Items (GET) and Send Offer to Interested Buyers (POST)","HTTP Request nodes configured to call https://api.ebay.com{basePath}","AI Expressions ($fromAI()) to auto-populate parameters from agent input","Returns native Negotiation API responses directly to AI agents (no extra mapping required)"],"target_audience":["developers integrating AI with e-commerce platforms","AI builders creating agent tool endpoints","marketplace operators or seller automation engineers testing negotiation flows"]}


name: Full Instagram API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:53:52.112Z
updated_at: 2025-07-02T04:53:52.112Z
url: https://n8n.io/workflows/5581
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 27 Instagram API operations to AI agents.

  ⚡ Quick Setup

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

  🔧 How it Works

  This workflow converts the Instagram API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.instagram.com/v1
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (27 total)

  🔧 Geographies (1 endpoints)

  • GET /geographies/{geo-id}/media/recent: Get recent media from a custom geo-id.

  🔧 Locations (3 endpoints)

  • GET /locations/search: Search Locations by Coordinates
  • GET /locations/{location-id}: Get information about a location.
  • GET /locations/{location-id}/media/recent: Get a list of recent media objects from a given location.

  🔧 Media (10 endpoints)

  • GET /media/popular: Get Popular Media
  • GET /media/search: Search Media by Area
  • GET /media/shortcode/{shortcode}: Get information about a media object.
  • GET /media/{media-id}: Get information about a media object.
  • GET /media/{media-id}/comments: Get a list of recent comments on a media object.
  • POST /media/{media-id}/comments: Create a comment on a media object.
  • DELETE /media/{media-id}/comments/{comment-id}: Remove a comment.
  • DELETE /media/{media-id}/likes: Remove a like on this media by the current user.
  • GET /media/{media-id}/likes: Get a list of users who have liked this media.
  • POST /media/{media-id}/likes: Set a like on this media by the current user.

  🔧 Tags (3 endpoints)

  • GET /tags/search: Search Tags by Name
  • GET /tags/{tag-name}: Get information about a tag object.
  • GET /tags/{tag-name}/media/recent: Get a list of recently tagged media.

  🔧 Users (10 endpoints)

  • GET /users/search: Search Users by Name
  • GET /users/self/feed: Get User Feed
  • GET /users/self/media/liked: Get User Liked Media
  • GET /users/self/requested-by: Get Follow Requests
  • GET /users/{user-id}: Get basic information about a user.
  • GET /users/{user-id}/followed-by: Get the list of users this user is followed by.
  • GET /users/{user-id}/follows: Get the list of users this user follows.
  • GET /users/{user-id}/media/recent: Get the most recent media published by a user.
  • GET /users/{user-id}/relationship: Get information about a relationship to another user.
  • POST /users/{user-id}/relationship: Modify the relationship between the current user and the target user.

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native Instagram API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

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metadata_json:
  {"categories":["integration","AI integration","social media","API proxy"],"complexity":"medium","use_cases":["Expose Instagram API to AI agents (MCP)","Build AI assistants that read/search Instagram media, tags, locations, and users","Automate social media workflows (likes, comments, relationships)","Prototype AI-driven moderation or analytics on Instagram data","Embed Instagram access into custom AI apps or agent toolchains"],"estimated_setup_minutes":5,"required_services":["n8n instance (self‑hosted or cloud)","Instagram API credentials / access token","Public webhook endpoint (or tunneling service like ngrok) for MCP trigger","AI agent or client that supports MCP (e.g., Claude Desktop, Cursor, custom agent)"],"key_features":["Implements 27 Instagram API endpoints (media, users, tags, locations, geographies)","MCP Trigger serving as AI-agent-accessible server endpoint","HTTP Request nodes mapping to https://api.instagram.com/v1","AI-aware parameter injection via $fromAI() expressions","Returns native Instagram API responses to agents (no mapping required)"],"target_audience":["Developers integrating Instagram with AI agents","AI engineers building tool-enabled agents","Automation engineers and SREs deploying MCP endpoints in n8n"]}


name: Proxy Detection by IP2Proxy - MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T04:57:14.410Z
updated_at: 2025-07-02T04:57:14.410Z
url: https://n8n.io/workflows/5582
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 1 IP2Proxy Proxy Detection API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

  Import this workflow into your n8n instance
  Credentials Add IP2Proxy Proxy Detection credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the IP2Proxy Proxy Detection API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ip2proxy.com
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (1 total)

  🔧 General (1 endpoints)

  • GET /: Check Proxy IP

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native IP2Proxy Proxy Detection API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
[cell repeats an earlier one in this file: 156 characters]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","ai-integration","security"],"complexity":"simple","use_cases":["Real-time proxy detection for incoming IPs","Fraud prevention and access control","Enriching requests with IP intelligence","Routing or blocking traffic based on proxy status","Integrating proxy checks into AI agent workflows"],"estimated_setup_minutes":20,"required_services":["IP2Proxy Proxy Detection API (https://api.ip2proxy.com)","n8n instance with MCP trigger and HTTP Request nodes","Publicly reachable webhook/MCP endpoint"],"key_features":["Exposes IP2Proxy Proxy Detection API as an MCP-compatible server","Single GET / endpoint for proxy-check operations","AI-driven parameter population via $fromAI() expressions","Native API responses returned to calling AI agents","Built-in HTTP request error handling and n8n logging"],"target_audience":["Developers","AI/agent integrators","Security and fraud teams (SRE/ops) benefited by IP intelligence workflows"]}


name: IP2WHOIS Domain Lookup MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T05:05:43.403Z
updated_at: 2025-07-02T05:05:43.403Z
url: https://n8n.io/workflows/5583
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 1 IP2WHOIS Domain Lookup API operations to AI agents.

  ⚡ Quick Setup
  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community
  Import this workflow into your n8n instance
  Credentials Add IP2WHOIS Domain Lookup credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the IP2WHOIS Domain Lookup API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://api.ip2whois.com/v2
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (1 total)

  🔧 General (1 endpoints)

  • GET /: Lookup WHOIS Data

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native IP2WHOIS Domain Lookup API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
[cell repeats an earlier one in this file: 156 characters]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","data lookup","domain intelligence","API"],"complexity":"simple","use_cases":["Automated WHOIS/domain information lookup","Enriching domain records in security or CRM systems","Threat intelligence and OSINT investigations","AI agents requiring live domain metadata","Integrating domain lookup into workflows or apps"],"estimated_setup_minutes":200,"required_services":["IP2WHOIS Domain Lookup API (API key/credentials)","n8n instance (self-hosted or n8n.cloud)","AI agent or client that supports MCP endpoints (e.g., Claude, Cursor)"],"key_features":["Exposes IP2WHOIS Domain Lookup as an MCP server endpoint","Single GET / endpoint for WHOIS lookups","Automatic parameter population via $fromAI() expressions","Native passthrough of API responses to AI agents","Built-in HTTP error handling and n8n logging"],"target_audience":["Developers","AI integrators","Security analysts / SOC teams / threat intel operators (OSINT)"]}


name: IPQualityScore API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T05:10:39.355Z
updated_at: 2025-07-02T05:10:39.355Z
url: https://n8n.io/workflows/5584
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 3 IPQualityScore API operations to AI agents.

  ⚡ Quick Setup

  Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free?

  Join the community

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

  🔧 How it Works

  This workflow converts the IPQualityScore API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to https://ipqualityscore.com/api
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (3 total)

  🔧 Json (3 endpoints)

  • GET /json/email/{YOUR_API_KEY_HERE}/{USER_EMAIL_HERE}: Email Validation
  • GET /json/phone/{YOUR_API_KEY_HERE}/{USER_PHONE_HERE}: Phone Validation
  • GET /json/url/{YOUR_API_KEY_HERE}/{URL_HERE}: Malicious URL Scanner

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Path parameters and identifiers
  • Query parameters and filters
  • Request body data
  • Headers and authentication

  Response Format: Native IPQualityScore API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Cursor: Add MCP server SSE URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n HTTP request handling and logging
  • Extensible: Easily modify or add custom logic

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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","security","automation","AI integration"],"complexity":"simple","use_cases":["Email validation","Phone validation","Malicious URL scanning","Expose IPQualityScore API to AI agents","Real-time validation in conversational agents or workflows"],"estimated_setup_minutes":20,"required_services":["IPQualityScore API (API key)","n8n instance (self-hosted or cloud)","Public webhook endpoint or tunneling (to expose MCP trigger)","AI agents or apps that support MCP (e.g., Claude Desktop, Cursor, custom AI)"],"key_features":["MCP server wrapper for IPQualityScore API","Three prebuilt endpoints: email, phone, URL","Automatic parameter population via $fromAI() expressions","Native IPQualityScore responses returned to AI agents","Built-in n8n HTTP request error handling and logging"],"target_audience":["Developers integrating validation into AI tools","AI app builders wanting a tool endpoint","Fraud/security analysts needing quick validation endpoints for agents or workflows"]}


name: Evaluate Animal Advocacy Text with Hugging Face Open Paws AI Models
author_name: Open Paws
author_username: openpaws
categories: []
created_at: 2025-07-02T07:06:15.647Z
updated_at: 2025-07-02T07:06:15.647Z
url: https://n8n.io/workflows/5587
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:34
description:
  This sub-workflow uses two custom Hugging Face regression models from Open Paws to evaluate and predict the real-world performance and advocacy alignment of text content. It’s designed to support animal advocacy organizations in optimizing their messaging across platforms like social media, email campaigns, and more.

  🛠️ What It Does

  Sends input text to two deployed Hugging Face endpoints:

    Predicted Performance Model – Estimates real-world content success (e.g., engagement, shares, opens) based on patterns from real online data.
    Advocate Preference Model – Predicts how well the content will resonate with animal advocates (emotional impact, relevance, rationality, etc.)
  Outputs structured scores for both models
  Can be integrated into larger workflows for automated content review, filtering, or revision

  📊 About the Models

  Text Performance Prediction Model**
    Trained on real-world data from 30+ animal advocacy organizations, this model predicts actual online performance of content—including social media, email marketing, and other outreach channels.

  Advocate Preference Prediction Model**
    Trained on ratings from animal advocates to evaluate how well a piece of text aligns with advocacy goals and values.

  Model Repositories:

  open-paws/text_performance_prediction_longform
  open-paws/animal_advocate_preference_prediction_longform

  &gt; 📌 You must deploy each model as an inference endpoint on Hugging Face. Click "Deploy" on each model’s repo, then add the endpoint URL and your Hugging Face access token using n8n credentials.

  📦 Use Cases

  Advocacy content review before publishing
  Automated scoring of outreach messages
  Filtering or flagging content with low predicted impact
  A/B testing support for message optimization

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","ai/ml","content optimization","nonprofit/advocacy"],"complexity":"medium","use_cases":["Advocacy content review before publishing","Automated scoring of outreach messages (social, email)","Filtering or flagging low-impact or misaligned content","A/B testing support for message optimization","Integration into larger workflows for automated revision or routing"],"estimated_setup_minutes":20,"required_services":["Hugging Face inference endpoints (deployed models)","Hugging Face access token","n8n (installed and configured)"],"key_features":["Sends input text to two custom Hugging Face regression endpoints","Returns structured performance and advocate-alignment scores","Supports integration into larger n8n workflows (review, filtering, revision)","Trained models specific to animal advocacy messaging","Lightweight sub-workflow (9 nodes) for embedding into pipelines"],"target_audience":["Animal advocacy organizations","Communications and campaign teams","Content strategists and marketers for nonprofits/causes"]}


