# templates

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?

  Join the community

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"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","knowledge management","collaboration","AI integration"],"complexity":"medium","use_cases":["Team memory / knowledge base (log and retrieve important info)","Summarize and send memories via email","Post and manage knowledge in Discord channels and DMs","Expose callable commands for other workflows (save/retrieve/send)","Customize AI agent prompt for formatting messages"],"estimated_setup_minutes":20,"required_services":["Google Docs","Discord","OpenAI (or another LLM)","Gmail (for email summaries)","Optional: MCP server / n8n Agent"],"key_features":["Save team memories to Google Docs","Retrieve memory history on demand","Send summarized memories to email/Discord","Discord channel and DM support","Callable sub-workflows (save_memory, retrieve_memory, send_memories_to_gmail) for easy integration into other automations','Customizable AI agent prompt to control message styling"],"target_audience":["Team leads and knowledge managers","Support and community managers","Developers building internal automations with n8n"]}


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"]

workflow_json_compressed:
  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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"]

workflow_json_compressed:
  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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"]

workflow_json_compressed:
  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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:
  [encoded data, 8344 characters]

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:
  [encoded data, 4428 characters]

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"]

workflow_json_compressed:
  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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"]

workflow_json_compressed:
  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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:
  [encoded data, 8380 characters]

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:
  [encoded data, 6220 characters]

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"]

workflow_json_compressed:
  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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"]

workflow_json_compressed:
  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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"]

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

workflow_json_compressed:
  [encoded data, 5008 characters]

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.

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.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.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"]

workflow_json_compressed:
  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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.

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.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  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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:
[cell repeats an earlier one in this file: 189 characters]

workflow_json_compressed:
  [encoded data, 4356 characters]

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.

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.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.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","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.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.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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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:
  H4sIAAAAAAAAE8VZ227kthl+FYIpsAcMxzrOSELTZrJxdwfJeh3bm3R3vXAo8tcMY4lUSGqciWGgN70uUPSmB6CHm970Afo8eYH2EQpKmoO9Yye7aVr4ZiRSH//D9/0/SV9iwXGGQ33cnMzqUl2A/jD3IjzAFViKM9mU5QBLWgHO8PTw04aWwi6PmdKAJodT9PTRIToGvQCNB9jSmcHZq9cDLBUH9/Oyg2dRnELh+yTyRx6J0tGIpGHqkYAmnCd56FPPx+tljsE2NZpKY3XDrFDSOOxl7cZkIkkLTnJqYGisYOfLA2UBD3CtjHDTcfaK+GHiDUgQea8HuKaaVmBBG5xdYqZKpXEWDfAcxGxuceZ7I2+AmZIWpMUZfu+999C3f/j9v/75G/SmKafyVPpD9PDhtKqVtuhzpc+LUl08fJihU/mJohzZuTDoon+PhLQKLVWjkUwkEtJYKhk4mMDBTBo7B2kFow6+Q3GB/RiWbk7YzmFWLKiF7cVO5b6keQnIzmGzmFXIWKpt+9blxrS5cUiRQ3oMtn39/OiTbqlHql52EJDPlTp3I6jQqlojWC1msw4idhCPlJTALJpM0WQG0ra2PDew/sAhCNm5PJki6iYhpmQhZo1uvTxt/1yY//3n3/4VPTd0Bsgl0ZzKb3/1N3S4ThiiGhBtrCK1qpuSWuAoXzrYxgg5Qz9xpk6m9x8g+LrWYEyXIgfyubBzFLYkBclrJaQ1iC6oKNuwUYOsUmU/+QhMraQBgyoqpKVCIqXFTEhatghd/hsN26b/8S+OIo8aY1Ulvuk9c2gTzhGnliKrqTSF0lU7iFriIlEgCcCBd5OnVV1C1caoRUKgtdJoTiUvhZxtEEs1mzmflUaVksIq7Z5azNN+4aeKi2KJ1oRHHAralNa4hFC5RE9OTg6Rhq8aMLb91MVhZc06Jf9ABwAcPYGy/vmpPHTLVICURK+4MExp/vr+3NraZHt7/YthBXusUJXi3zxAhdKO9TDrso1mjeCO84hKvnLS5bSLihmiR3Ng5y1/XjmNcMUaF5B2eGspxcxQJnIo1N4WvNnLG1FaIfdY2RgLuqsPe6bJ+1+bmlFSOWNzKuTQ5b5i9V5nbeXKmZDrTA3xVVdxPgNt2oriXw36WjbOvYSPi4gEucdJlIQ5SWA0JkCjIPWDJEhH6aaWrRSLni1ALwRcvEMp8wNvQHzvzVJ2Ibid4ywMvE0xS4MbtWxN1BvVe1O50bd/+jUKkaqhj+iGCr/7O3rialhX59qBk2vVjSm5AG1Nm70d/aGtflS61QhTVU2tcOpz+dMFZdCGf1UlzHBF5IcPnXknXelxlaq11Di2tnWlK2trYV9DWfHbrKBa0h/1pD9wEXeIT5zAOiMZLUtXDtCKaqL+qnPEkRuGTFV7tBYrvMkU7W+qjcOa9Gx2QEu0KlUbHRq0EBR9sa5WX6C6pAzmquSg13YeUCsWgKYbbjvsI7CNlgbpdYniQgOz5dJZ7MK+cvxU3kHbfBTDKKKMpN4oJVEaBISOE0Yg8YEB5H6SU3xbp7/e5Tv6fiATuVNaFav7xN0gchqtW3LfbabOMoh44uV5SPIgj0g08oCkYciJT6nnxXE+TscjfJP6NXXMx9cTRSpW3xGCNBoVYegBAepzEuUcCGVJTqDgcTwq8jHP400IPqOl4C6L+xUVpavALuO3ytdRp+fYiVLlDdfjkXP9TQU3usQZfv9u3u19aZTcA2fG3uXluufde/Hs+dHZ5HB69vH+i7Mn+0f79wbo3n1nhNDAH6Cd48a6tnHvAbq6ugb2/Hj/6Gz/6WT6yS6oHaNbQHiAVd1t1LJLF3+lyo/AMC3qLgC4i2Ef0n4HsOny2akk6JDa+ZZislOJkNPFG16g+3ptF0F3+buCuGH9rQA35r1BpWgYrMkE45COw6ggLEzHJII8J0keFiTxvXDEUr8oonxDpsda8HaHg/y3bwAjR57k1p3seFP8gzeK/83A3yGPMM5ZkkQB8YM8JlHAUkJplBKfeiyCfAT+KNghj8O5koAOmirfrg5vpY4g+cHqqJ0VP7I6Dp88O9i/VR3XR+9QhwHJP21AL3FmdQMD/JV7OLxR3jZPry5XMWeqkVYv8QAvaNm4N+9vG9kPu+W3fm5bcvV6pzq7FP5f1bmJ3t3q3MxzVrVh3GVW7z+630Welg7rUR++u2SdhF7AI78gSVQAidg4IpSPc0IjPgqKKE6j3bIO3l7W7Qn1HWV9M2N3yjqOExaPSUCp8yjOSQ5FTMY0p8ko8f0o3PLomFHZnQGVRk9peUE1vJuqf7CkG/1jtruj3X3u6B0b3FNaCiZUY9rguSjK7sz8P9TR0Xe1t6Pv0dfYmIZ+PmaE+nlIIqDg+lpO4jzgSeglYRrxXQII3+FgE3yXAPoDjusPd4hhK/a6XMV+hyJeDzB1NymAs4KWBgbYzKkG3pZYrUpn++pgk6kL2W1gtfoSmHV2tfF5HBcM0q8fNx9OzOcf/tL5JJjDv3ZT9hFdCI4mZp4v0U+5exhS9zAsuflg5nqy4/rPNjGrQRtXp/AAMw3unmPivAu8ICbeiHjRiRdkcZx5wdDzw5d4gJua3zZtlHn+MBz5Lzf2H0FJewJvnO3HstXiz3qfGwN67fDYj5nPPI+wPEpINPYDktIwIIVfRPmI50EeeniwgpyVKqflOnrtphVn+NYQ4AHmwrgbGb7OSkmNPeji2EYQu55prZCzlh6yNseNXsDSPXSnIu6+7pqp+/h4ri6kC4w/jtIwHo9cCfSvOsdWl2nrL669XH3ljeM0jaI0HmCgZjmZrg7yz2SuqN5asBDa2OOGMTCmaMrVvPZoEx6Ei8/E+cs8fMrOf/GicqS8O73+cBzFLm8t7MEWmxzRzCFILuRsHaqdJEhOvCiLvCxOhmGaOrCqoN1t4SbIq5z3F1cTaS56+S1WisELdw98Y+KZaWN/JhN5tpnpD9N4GN4+2zR5JawFfkZ383U89MbxS3zVJ2n6Fsz7nnrpyT69RcR3yGmD0u6f3lxvTLzgxIszL828cJik77beTpSLa3S6eUvvStq2NKyo4BslW+VUoAWjewdwcfZC6fPd1Lu5pr+7sqym+V4WJEPP89y0PvvdGT6kSRyGlEARRSTiCSU5HwOhkAdxVMCoSOOWwBPN5mKxxUPjrvnYR3TzzwbWXTD33Xb3jiS7xFScuTaMs1dug6z497y2WH02wEJy+Bpn3tVrl9Xd55kfcZ3r1wr/7YVc9+suYdpdr3v7Hx4FUXvrGQAA

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"]

workflow_json_compressed:
  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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"]}


name: Multi-Tool Research Agent for Animal Advocacy with OpenRouter, Serper & Open Paws DB
author_name: Open Paws
author_username: openpaws
categories: []
created_at: 2025-07-02T08:03:41.949Z
updated_at: 2025-07-02T08:03:41.949Z
url: https://n8n.io/workflows/5588
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  This general-purpose sub-agent combines multiple research and automation tools to support high-impact decision-making for animal advocacy workflows. It’s designed to act as a reusable, modular unit within larger multi-agent systems—handling search, scraping, scoring, and domain-specific semantic lookup.

  It powers many of the advanced workflows released by Open Paws and serves as a versatile backend utility agent.

  🛠️ What It Does

  Performs real-time Google Search using Serper  
  Scrapes and extracts page content using Jina AI and Scraping Dog  
  Conducts semantic search over the Open Paws knowledge base  
  Generates OpenAI embeddings for similarity search and analysis  
  Routes search and content analysis through OpenRouter LLMs  
  Connects with downstream tools like the Text Scoring Sub-Workflow to evaluate message performance

  &gt; 🧩 This agent is typically used as a sub-workflow in larger automations where agents need access to external tools or advocacy-specific knowledge.

  🧠 Domain Focus: Animal Advocacy

  The agent is pre-configured to interface with the Open Paws database—an open-source, animal advocacy-specific knowledge graph—and is optimized for content and research tasks relevant to farmed animal issues, corporate campaigns, and activist communication.

  🔗 Integrated Tools and APIs

  | Tool          | Purpose                                 |
  |---------------|------------------------------------------|
  | Serper API        | Real-time Google Search queries             |
  | Jina AI           | Web scraping and content extraction         |
  | Scraping Dog      | Social media scraping where Jina is blocked |
  | OpenAI API        | Embedding generation for semantic search    |
  | OpenRouter        | Proxy to multiple LLMs (e.g., GPT-4, Claude)|
  | Open Paws DB      | Advocacy-specific semantic knowledge base   |

  📦 Use Cases

  Create and evaluate online content (e.g. social media, emails, petitions) for predicted performance and advocacy alignment  
  Act as a research and reasoning agent within multi-agent workflows  
  Automate web and social media research for real-time campaign support  
  Surface relevant facts or arguments from an advocacy-specific knowledge base  
  Assist communications teams with message testing and content ideation  
  Monitor search results and scrape pages to inform rapid response messaging  

nodes_used:
  ["@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.executeWorkflowTrigger","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.hunterTool","n8n-nodes-base.hunterTool","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 12508 characters]

metadata_json:
  {"categories":["automation","integration","data processing","research"],"complexity":"complex","use_cases":["Automated research and scraping for advocacy campaigns","Semantic lookup and fact-surfacing from a domain-specific knowledge base","Generating embeddings and similarity search for content analysis","Acting as a reusable sub-agent within multi-agent workflows","Evaluating and scoring draft messages (social posts, emails, petitions) for predicted performance and alignment"],"estimated_setup_minutes":90,"required_services":["Serper API (real-time Google Search)","Jina AI (scraping/content extraction)","Scraping Dog (social media scraping fallback)","OpenAI API (embeddings)","OpenRouter (LLM proxy e.g., GPT-4, Claude)","Open Paws DB (advocacy-specific knowledge graph)"],"key_features":["Real-time Google search queries","Web and social scraping with fallback behavior","Content extraction and parsing","Semantic search over an advocacy knowledge base","OpenAI embeddings for similarity search and analysis"],"target_audience":["Developers building multi-agent automations","Animal advocacy organizations and campaign teams","Communications and content teams (message testing/ideation)"]}


name: Create a Multi-Modal Telegram Support Bot with GPT-4 and Supabase RAG
author_name: Ezema Kingsley Chibuzo
author_username: kingsley
categories: []
created_at: 2025-07-02T09:02:20.931Z
updated_at: 2025-07-02T09:02:20.931Z
url: https://n8n.io/workflows/5589
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  🧠 What It Does
  This n8n workflow turns your Telegram bot into a smart, multi-modal AI assistant that accepts text, documents, images, and audio messages, interprets them using OpenAI models, and responds instantly with context-aware answers.
  It integrates a Supabase vector database to store document embeddings and retrieve relevant information before sending a prompt to OpenAI — enabling a full RAG experience

  💡 Why This Workflow?
  Most support bots can only handle basic text input. This workflow:
  Supports multiple input formats (voice, documents, images, text)
  Dynamically extracts and processes data from uploaded files
  Implements RAG by combining user input with relevant memory or vector-based context
  Delivers more accurate, relevant, and human-like AI responses.

  👤 Who It's For

  Businesses looking to automate support using Telegram
  Freelancers or solopreneurs offering AI Chatbots for businesses.
  Creators building AI-powered bots for real use cases as it's great for Customer support knowledge, Legal or Policy document, long FAQs, Project documentation, and Product information retrieval.
  Devs or analysts exploring AI + multi-format input + vector memory.

  ⚙️ How It Works
  🗂️ Knowledge Base Setup
  Run the “Add to Supabase Vector DB” workflow manually to upload a document from your google drive and embed it into your vector database. This powers the Telegram chatbot’s ability to answer questions using your content. 
  🔁 Telegram Message Routing
  Telegram Trigger captures the user message (Text, Image, Voice, Document)
  Message Router routes input by type using a Switch node
  Each type is handled separately:
       Voice → Translate recording to text (.ogg, .mp3)
       Image → Analyze image to text.
       Text → Sent directly to AI Agent (.txt).
       Document → Parsed (e.g. .docx to .txt) accordingly.

  📎 Document Type Routing

         Before routing documents by type, the Supported  Document File Types node first checks if the file extension is allowed. If not supported, it exits early with an error message — preventing unnecessary processing.
  Supported documents are then routed using the Document Router node, and converted to text for further processing.

  Supported Document File Types
         .jpg   .jpeg   .png   .webp   .pdf   .doc   .docx   .xls   .xlsx   .json   .xml.

  The text content is combined with stored memory and embedded knowledge using a RAG approach, enabling the AI to respond based on real uploaded data.
  🧠 RAG via Supabase
     Uploaded documents are vectorized using OpenAI Embeddings. Embeddings are stored in Supabase with metadata. On new questions, the chatbot:
     Extracts question intent
     Queries Supabase for semantically similar chunks
     Ranks retrieved chunks to find the most relevant match.
     Injects them into the prompt for OpenAI. 
     OpenAI generates a grounded response based on actual document content.

  Response is sent to the Telegram user with content awareness.

  🛠 How to Set It Up

  Open n8n or your local/self-hosted instance.
  Import the `.json
  ` workflow file.
  Set up these credentials:
     Google drive API Key
     Telegram API (Bot Token) Guide
     OpenAI API
     Supabase API Key + Environment
     ConvertAPI API Key
     Postgres API Key
     Cohere API Key
     Add a prompt suited to your business. Add a custom AI agent prompt that reflects your business domain, tone, and purpose. This is very important. Without it, your agent won't know how best to respond.
  Activate the workflow.
  Start testing by sending a message or document to your Telegram bot.

nodes_used:
  ["n8n-nodes-base.telegramTrigger","n8n-nodes-base.telegram","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.extractFromFile","n8n-nodes-base.telegram","n8n-nodes-base.extractFromFile","n8n-nodes-base.telegram","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.memoryPostgresChat","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.rerankerCohere","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.vectorStoreSupabase","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.vectorStoreSupabase"]

workflow_json_compressed:
  [encoded data, 10424 characters]

metadata_json:
  {"categories":["automation","integration","data-processing","ai","chatbot"],"complexity":"complex","use_cases":["Multi-modal customer support bot (text, images, audio, documents)","Document Q&A and knowledge-base retrieval","RAG-powered contextual responses using vector search","Automated ingestion and indexing of documents from Google Drive","Helpdesk/FAQ automation and legal or policy document lookup"],"estimated_setup_minutes":90,"required_services":["Telegram Bot API","OpenAI (GPT-4 + Embeddings)","Supabase (vector DB)","Google Drive API","ConvertAPI (file conversion)","Postgres (DB)","Cohere API"],"key_features":["Supports text, images, audio, and documents","Dynamic file-type routing and conversion (.pdf, .docx, .xls, images, audio)","Audio transcription and image-to-text processing","Embeddings generation and storage in Supabase for RAG","Semantic retrieval of relevant document chunks before prompting GPT-4','Customizable AI agent prompt/tone and domain-specific context injection"],"target_audience":["Businesses automating customer support","Freelancers and consultants building chatbots","Developers integrating multi-modal AI agents with vector DBs','Product teams managing searchable documentation and FAQs"]}


name: Daily Website Data Extraction with Firecrawl and Telegram Alerts
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2025-07-02T11:11:47.144Z
updated_at: 2025-07-02T11:11:47.144Z
url: https://n8n.io/workflows/5591
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  🔥 Automated Daily Firecrawl Scraper with Telegram Alerts
  Get structured insights scraped daily from the web using Firecrawl’s AI extraction engine — then send them directly to your Telegram chat.

  🧰 What this workflow does:
  This workflow automatically scrapes specific structured data from any webpage every day at a scheduled time using the Firecrawl API, checks if results are returned, and then sends the formatted results to Telegram.

  For step-by-step video tutorials of n8n builds, check out my channel:
  https://www.youtube.com/@Automatewithmarc

  🧭 How It Works:
  🕐 Schedule Trigger (Daily at 6PM)
  Starts the workflow every day at a set time.

  🌐 Firecrawl POST Request
  Sends a custom extraction prompt and schema to Firecrawl, targeting any list of URLs you provide.

  ⏳ 30 Seconds Wait
  Waits to give Firecrawl enough time to complete processing.

  📥 GET Firecrawl Result
  Fetches the extraction results using the request ID.

  🔁 Loop with IF Node
  Checks whether data is returned. If not, waits another 15 seconds and retries.

  🧹 Format & Clean (Set Node)
  Prepares and formats the extracted result into a readable message.

  📲 Telegram Message Node
  Delivers the structured data directly to your Telegram channel or group.

  🔧 Requirements:
  ✅ Firecrawl API Key (Header Auth)

  ✅ Telegram Bot Token & Chat ID

  💡 Use Cases:
  Extract structured data (like product info or events) from niche websites
  Automate compliance monitoring or intelligence gathering
  Create market alert bots with real-time info delivery

  🛠 Customization Ideas:
  Swap Telegram with Gmail, Discord, or Slack

  Expand schema to include more complex nested fields

  Add a Google Sheet node to log daily scraped data

  Integrate with a summarizer or language model for intelligent summaries

  Ready to automate your web intelligence gathering?
  🧠 Let Firecrawl do the scraping — and let this workflow do the rest.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","web scraping","data extraction","alerts","integration"],"complexity":"medium","use_cases":["Daily structured web data extraction (products, events, listings)","Automated market or competitive intelligence alerts","Compliance or monitoring alerts from websites","Delivering scraped results to chat platforms (Telegram)","Logging/archiving daily scrape results for analysis"],"estimated_setup_minutes":20,"required_services":["Firecrawl API (API key)","Telegram Bot API (bot token and chat ID)"],"key_features":["Daily scheduled scraping trigger","Custom extraction prompt and schema sent to Firecrawl","Asynchronous polling with retry logic for results","Result formatting and cleaning before delivery","Telegram message delivery of structured results (can swap to other channels)"],"target_audience":["developers","data engineers/analysts","growth/marketing teams doing market monitoring or alerts"]}


name: Process & Summarize PDFs from Email & Messaging Apps with OpenAI GPT
author_name: papcy
author_username: papcy
categories: []
created_at: 2025-07-02T11:37:06.507Z
updated_at: 2025-07-02T11:37:06.507Z
url: https://n8n.io/workflows/5592
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  Process PDFs from Gmail, Outlook, Telegram and WhatsApp with OpenAI

  Transform PDF documents into actionable insights automatically across multiple platforms. This workflow monitors emails and messaging platforms for PDF attachments, extracts content, and delivers AI-powered summaries.

  Who's it for

  Business professionals, teams, and organizations needing automated PDF analysis from emails and messaging platforms. Perfect for processing contracts, reports, invoices, and documents requiring quick review.

  How it works

  Monitors Gmail and Outlook for PDF attachments while receiving PDFs via Telegram bot and WhatsApp Business API. Uses OpenAI to extract text and generate structured summaries with executive overviews, key points, important details, insights, and document type identification. Automatically routes summaries back to original senders.

  Requirements

  Gmail/Outlook OAuth2 credentials
  Telegram Bot API token via @BotFather  
  WhatsApp Business API account
  OpenAI API key

  How to set up

  Configure API credentials in respective nodes, update configuration variables for phone numbers and notification settings, then test with sample PDFs.

  How to customize

  Modify AI models, customize prompts, adjust response formatting, extend file support, add notification channels, or integrate with external systems.

  Perfect for automating document workflows across communication channels.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.telegramTrigger","n8n-nodes-base.whatsAppTrigger","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.whatsApp","n8n-nodes-base.telegram","n8n-nodes-base.whatsApp","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.whatsApp","n8n-nodes-base.telegram","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","document processing","AI/NLP","messaging"],"complexity":"complex","use_cases":["Automated PDF summarization from email and chat","Contract and report review","Invoice and receipt processing","Routing document summaries back to senders","Multi-channel document intake (Gmail, Outlook, Telegram, WhatsApp)"],"estimated_setup_minutes":60,"required_services":["Gmail (OAuth2)","Microsoft Outlook (OAuth2)","Telegram Bot API","WhatsApp Business API","OpenAI API"],"key_features":["Monitors Gmail, Outlook, Telegram and WhatsApp for PDF attachments","Extracts text from PDFs","Generates structured AI summaries (executive overview, key points, insights, document type)","Routes summaries back to original senders","Configurable prompts, models and response formatting"],"target_audience":["Business professionals","Teams and organizations (operations, legal, finance)","Automation engineers and developers"]}


name: Automated Hazard Analysis for ISO 26262 Compliance Using GPT-4
author_name: MRJ
author_username: manirajan
categories: []
created_at: 2025-07-02T13:19:47.154Z
updated_at: 2025-07-02T13:19:47.154Z
url: https://n8n.io/workflows/5594
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  Modular Hazard Analysis Workflow : Free Version

  Business Value Proposition
  Accelerates ISO 26262 compliance for automotive/industrial systems by automating safety analysis while maintaining rigorous audit standards.

  :chart_with_upwards_trend: Key Benefits
  Time
      Instant report generation vs. weeks of documentation for HAZOP

  Risk Mitigation
      Pre-validated templates reduce human error

  Quick guide
  Input a systems_description file to the workflow
  Provide an OPENAI_API_KEY to the chat model. You can also replace the chat model with the model of your interest.

  :play_or_pause_button: Running the Workflow
  Refer to the github repo to understand in detail about how the workflow can be used 

  :email: Contact
  For collaboration proposals or security issues, contact me by Email.

  :warning: Validation & Limitations

  AI-Assisted Analysis Considerations
  | Advantage | Mitigation Strategy | Implementation Example |
  |-----------|---------------------|------------------------|
  | Rapid hazard identification | Human validation layer | Manual review nodes in workflow |
  | Consistent S/E/C scoring | Rule-based validation | ASIL-D → Redundancy check |
  | Edge case coverage | Cross-reference with historical data | Integration with incident databases |

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.convertToFile","n8n-nodes-base.readWriteFile"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","compliance","safety engineering","document generation","LLM integration"],"complexity":"medium","use_cases":["Automated hazard analysis for ISO 26262","Generating safety reports (HAZOP/ASIL) from system descriptions","Speeding up compliance documentation and audit preparation","Risk identification and S/E/C scoring with human validation","Cross-referencing hazards with historical incident data (optional)"],"estimated_setup_minutes":30,"required_services":["OpenAI API (GPT-4 or compatible chat model) - OPENAI_API_KEY","n8n runtime (workflow execution)","Local or shared file storage for systems_description and output reports","GitHub (optional, for repository/instructions and workflow code)","Optional incident/historical-data API or database (for cross-referencing)"],"key_features":["Automated hazard identification using a chat LLM","Modular workflow with manual review nodes for human validation","S/E/C (ASIL) scoring and rule-based validation support","Instant report generation (file output)","Memory buffer/context window to maintain conversational context across steps"],"target_audience":["Automotive functional safety engineers","Safety compliance officers","System architects for automotive/industrial systems"]}


name: Categorize and Label Incoming Gmail Emails Automatically with GPT-4o mini
author_name: Arlin Perez
author_username: arlindeveloper
categories: []
created_at: 2025-07-02T13:36:21.943Z
updated_at: 2025-07-02T13:36:21.943Z
url: https://n8n.io/workflows/5595
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Sort New Gmail messages by category with AI 

  👥 Who's it for  
  This workflow is perfect for individuals or teams who receive a high volume of emails 📥 and want to automatically organize them into Gmail labels 🏷️ using AI. No coding required!

  For sorting existing emails messages in your gmail inbox, please use this free workflow: Categorize and Label Existing Gmail Emails Automatically with GPT-4o mini.

  🤖 What it does  
  It automatically processes new Gmail emails, skips those that already have labels, sends the content to an AI Agent powered by GPT-4o mini 🧠, and applies a relevant label based on the content. All labels must exist in Gmail beforehand.

  ⚙️ How it works  
  📬 Gmail Trigger – Activates on new email received.  
  🚫 Filter – Skips emails that already have a label.  
  🧠 AI Agent (GPT-4o mini) – Analyzes the message and decides which label fits best.  
  🧾 Structured Output Parser – Formats the AI output into a clean JSON.  
  🔀 Switch Node – Routes each email to the correct label path based on the AI result.  
  🏷️ Gmail Nodes – Assign the Gmail label to the original email.

  📋 Requirements  
  Gmail account connected to n8n  
  Pre-created labels in Gmail matching the AI categories  
  OpenAI credentials with GPT-4o mini access  
  n8n's AI Agent & Structured Output Parser nodes  

  🛠️ How to set up  
  Open the workflow and adjust the trigger interval (e.g., every minute, hours or Custom using Cron ⏱️)  
  Check that the Filter skips emails with existing labels  
  Define your categories in the AI Agent prompt and make sure they match the Gmail labels  
  Configure the Switch Node conditions for each category  
  Ensure each Gmail Label Node applies the correct label  
  Save and activate the workflow ✅

  🎨 How to customize the workflow  
  Add or remove categories in the AI prompt & Switch Node   
  Fine-tune prompt instructions to match your specific use case

nodes_used:
  ["n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.filter","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.gmail","n8n-nodes-base.gmail"]

workflow_json_compressed:
  [encoded data, 6024 characters]

metadata_json:
  {"categories":["automation","email management","AI integration","integration"],"complexity":"medium","use_cases":["Automatically label incoming Gmail messages based on content","Triage and route emails to teams or folders","Prioritize customer support or sales emails","Organize newsletters, promotions, and transactional messages","Reduce manual inbox sorting and improve workflow efficiency"],"estimated_setup_minutes":15,"required_services":["Gmail account with pre-created labels","OpenAI account with GPT-4o mini access","n8n instance with AI Agent & Structured Output Parser nodes"],"key_features":["Triggers on new Gmail messages","Skips emails that already have labels","AI Agent (GPT-4o mini) categorizes message content","Structured Output Parser converts AI response to JSON","Switch node routes items to label-specific paths"],"target_audience":["Individuals with high email volume","Support, sales, and marketing teams","No-code users and workflow builders using n8n"]}


name: Generate Brand Marketing Shorts with GPT-4, FAL AI & ElevenLabs for Social Media
author_name: Aashit Sharma
author_username: aashitsharma
categories: []
created_at: 2025-07-02T14:40:58.005Z
updated_at: 2025-07-02T14:40:58.005Z
url: https://n8n.io/workflows/5596
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  AI‑Powered Branded Marketing Videos & Shorts (SSO-Optimized for n8n)

  🧠 About This Flow

  This advanced automation template allows marketing teams, content creators, and branding specialists to automatically generate and publish high-quality, visually captivating branded short videos across YouTube, Instagram, and TikTok — with zero manual effort.

  The system uses AI-powered prompt generation, media rendering, and multi-platform publishing, combining:

  🧠 GPT-4 via OpenRouter – to generate story-rich prompts  
  🎨 Image creation via FAL AI  
  🎞️ Video generation via Kling (FAL AI)  
  🔊 Audio generation via ElevenLabs  
  🛠️ Video compilation via Creatomate  
  🌐 Hosting via Blotato  
  🚀 Publishing via platform-specific authenticated endpoints  
  📊 Logging via Google Sheets  

  All credentials and settings are SSO-enabled or environment variable driven, making it easy to reuse across teams and environments.

  🚀 How It Works

  1. Trigger & Content Fetch

  Triggered on schedule or manually.
  Fetches the next unpublished row from a Google Sheet.
  Columns include: Brand, Title, Caption, Status.

  2. AI-Powered Prompt Generation

  Uses GPT-4 via OpenRouter to generate:
    image_prompt
    video_prompt
    audio_prompt

  3. Media Generation

  Image:** FAL Flux-Pro + polling  
  Audio:** ElevenLabs (5s ambient loop)  
  Video:** Kling via FAL (looped 5s animation)  

  4. Final Video Rendering

  Uses Creatomate to assemble assets into a final short.

  5. Hosting & Upload

  Hosted via Blotato with a public URL returned.

  6. Platform Publishing

  Auto-publishes to:
  YouTube (unlisted)**
  Instagram Reels**
  TikTok (public)**

  7. Logging

  Updates Google Sheet with:
  Final video link  
  Status = Published  
  Platform-specific IDs  

  🧩 Setup Instructions

  Step 1: Clone or Import the Template
  From your n8n dashboard: Import from File → paste the JSON.

  Step 2: Add Environment Variables

  GSHEET_ID=your_sheet_id_here
  CREATOMATE_TEMPLATE_ID=your_template_id
  CREATOMATE_API_KEY=sk_live_...
  BLOTATO_API_KEY=bt_...
  YOUTUBE_ACCOUNT_ID=...
  INSTAGRAM_ACCOUNT_ID=...
  TIKTOK_ACCOUNT_ID=...

  Step 3: Create OAuth Credentials

  | Name | Platform | Usage |
  |------|----------|-------|
  | Google-Marketing | Google | Sheets + YouTube |
  | Meta-Marketing | Instagram/Facebook | Reels |
  | TikTok-Marketing | TikTok | Posting |

  Step 4: Google Sheet Setup

  Use this template.

  Columns:
  Brand, Title, Caption, Status, VideoLink, YouTubeID, InstagramID, TikTokID

  Step 5: Sub-Workflows

  Enable:
  Poll-Until-Image-Ready
  Poll-Until-Video-Ready

  Step 6: Run the Workflow

  Manually
  Scheduled
  Triggered by external app

  ✅ Best Practices

  | Tip | Description |
  |-----|-------------|
  | Use sub-workflows | Clean separation for logic |
  | Use env vars | Safer & cleaner setup |
  | Preview locally | Run once with test brand |
  | Log failures | Add error notifications |

  💡 Customization Ideas

  Add Slack notifications  
  Add overlays via Creatomate  
  Replace GPT with Claude/Mistral  
  Publish to more platforms  
  Use Airtable/Notion instead of Google Sheets  

  🏁 Final Output

  Brand like Nike produces:
  Image of a shoe-shaped building  
  Video of joggers & motion  
  Lo-fi audio  
  Rendered short  
  Posted on all platforms  
  Sheet updated with URLs + IDs  

  🔗 Tags

  #marketing #ai #video-automation #youtube #instagram #tiktok  
  #shorts #branded-content #sso-ready #n8n-template

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.wait","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitOut","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","marketing","video-generation","social-media-publishing","ai-content"],"complexity":"complex","use_cases":["Automated branded short video production","Multi-platform social media publishing (YouTube, Instagram, TikTok)","AI-driven creative asset generation (images, videos, audio)","Content pipeline logging and tracking via Google Sheets","Team-ready SSO/env-var driven deployment for marketing ops"],"estimated_setup_minutes":60,"required_services":["n8n (self-hosted or cloud)","OpenRouter (GPT-4) or compatible LLM endpoint","FAL AI (Flux / Kling) for image & video generation","ElevenLabs for audio generation","Creatomate for video assembly/rendering","Blotato (or hosting service) for public asset hosting","Google Sheets & Google Drive (Sheets + optional Drive access)","YouTube (OAuth account for uploads)","Meta/Instagram (OAuth for Reels)","TikTok (OAuth/API for posting)"],"key_features":["GPT-4 prompt generation for image, video, and audio prompts","Automated image, video, and audio generation (FAL AI + ElevenLabs)","Polling sub-workflows to wait for async media readiness","Final video assembly via Creatomate","Automated hosting and multi-platform publishing (YouTube, Instagram, TikTok)"],"target_audience":["Marketing teams","Content creators & social media managers","Brand managers and agencies producing short-form video ads/content"]}


name: Iterative Content Refinement with GPT-4 Multi-Agent Feedback System
author_name: Sebastian/OptiLever
author_username: lewxiangang
categories: []
created_at: 2025-07-02T15:00:40.640Z
updated_at: 2025-07-02T15:00:40.640Z
url: https://n8n.io/workflows/5597
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who's it for
  This workflow is designed for users who want to implement iterative AI-powered content improvement processes. It's ideal for content creators, marketers, product managers, and anyone who needs to refine ideas through multiple rounds of critique and enhancement until they meet quality standards.

  How it works
  The workflow creates a sophisticated feedback loop using three specialized AI agents that work together to continuously improve content. Starting with an initial input (like a product description), the system generates ideas and then enters a reasoning loop where:

  A Critic Agent analyzes the current output and identifies flaws or areas for improvement
  A Refiner Agent takes the original input plus the critic's feedback to create enhanced versions
  An Evaluator Agent assesses the refined output and determines if it meets the quality threshold

  The loop continues until either the evaluator determines the output is satisfactory or a maximum number of iterations is reached (configurable, default is 5 turns).

  How to set up

  Configure the initial AI agent to generate your starting content
  Set up the loop structure with "Reset Loop" enabled in the loop node options
  Configure three AI agents within the loop:

  Critic: Provide detailed analysis prompts for identifying improvements
  Refiner: Create prompts that incorporate feedback to enhance content
  Evaluator: Define quality criteria and decision-making logic


  Add Edit Fields nodes at the beginning and end of the loop to maintain data structure
  Include a Code node to track iteration count and loop control
  Set up the IF node to check exit conditions (max turns or completion status)

  Requirements

  n8n workflow environment
  Access to AI/LLM nodes (OpenAI, Anthropic, etc.)
  Basic understanding of JSON data structures
  Configured AI model credentials

  How to customize the workflow
  Customize the system prompts for each agent based on your specific use case. The critic should focus on your quality criteria, the refiner should understand your improvement goals, and the evaluator should have clear success metrics. Adjust the maximum iteration count in the code node and IF condition based on your complexity needs and token budget considerations.

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

workflow_json_compressed:
  [encoded data, 4632 characters]

metadata_json:
  {"categories":["automation","AI-assisted content refinement","workflow orchestration","integration"],"complexity":"complex","use_cases":["Iterative content improvement (copy, descriptions, blog drafts)","Automated critique-and-rewrite cycles","Quality-gated content generation","Prompt engineering and model tuning","Multi-round idea refinement and evaluation"],"estimated_setup_minutes":30,"required_services":["n8n workflow environment","LLM API access (OpenAI, Anthropic, or equivalent)","API credentials / secret management"],"key_features":["Three specialized agents: Critic, Refiner, Evaluator","Configurable iterative loop with max turns and exit conditions","Iteration tracking via Code node","Use of Edit Fields to preserve data structure across rounds","IF node to check completion or max-iterations for loop control」「Supports multiple LLM nodes (lmChatOpenAi, agent) and structured output parsing"],"target_audience":["Content creators","Marketers","Product managers and PMMs who refine messaging or specs (technical or non-technical)」「Developers and automation engineers setting up AI workflows"]}


name: SEO Blog Publishing for Jekyll with GPT-4, GitHub & Social Sharing
author_name: Antonio Trento
author_username: antoniotrento
categories: []
created_at: 2025-07-02T15:14:48.020Z
updated_at: 2025-07-02T15:14:48.020Z
url: https://n8n.io/workflows/5598
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  🤖 Auto-Publish SEO Blog Posts for Jekyll with AI + GitHub + Social Sharing

  This workflow automates the entire process of publishing SEO-optimized blog posts (e.g., recipes) to a Jekyll site hosted on GitHub. It uses LangChain + OpenAI to write long-form Markdown articles, and commits them directly to your repository. Optional steps include posting to X (Twitter) and LinkedIn.

  🔧 Features

  📅 Scheduled Execution: Runs daily or manually.
  📥 CSV Input: Reads from a local CSV (/data/recipes.csv) with fields like title, description, keywords, and publish date.
  ✍️ AI Copywriting: Uses a GPT-4 model to generate a professional, structured blog post optimized for SEO in Markdown format.
  🧪 Custom Prompting: Includes a detailed, structured prompt tailored for Italian food blogging and SEO rules.
  🗂 Markdown Generation:
    Automatically builds the Jekyll front matter.
    Generates a clean SEO-friendly slug.
    Saves to _posts/YYYY-MM-DD-title.md.
  ✅ Commits to GitHub: Auto-commits new posts using GitHub node.
  🧹 Post-Processing: Removes processed lines from the source CSV.
  📣 (Optional) Social media sharing: Can post title to X (Twitter) and LinkedIn.

  📁 CSV Format Example

  titolo;prompt_descrizione;keyword_principale;keyword_secondarie;data_pubblicazione
  Pasta alla Norma;Classic Sicilian eggplant pasta...;pasta alla norma;melanzane, ricotta salata;2025-07-04T08:00:00

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.readBinaryFile","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.github","n8n-nodes-base.twitter","n8n-nodes-base.linkedIn","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.scheduleTrigger"]

workflow_json_compressed:
  [encoded data, 4604 characters]

metadata_json:
  {"categories":["automation","content creation","SEO","integration","social sharing"],"complexity":"complex","use_cases":["Automated publishing of SEO-optimized blog posts to a Jekyll site","Batch/content pipeline from CSV input","AI-generated long-form Markdown content (recipes, articles)","Scheduled publishing and post scheduling","Optional cross-posting to social networks (X/Twitter, LinkedIn)"],"estimated_setup_minutes":45,"required_services":["OpenAI (GPT-4) API","LangChain (or equivalent prompt orchestration)","GitHub (repo access for commits; GitHub Pages/Jekyll hosting)","X (Twitter) API — optional","LinkedIn API — optional","Local file storage or mounted volume for CSV/_posts folder"],"key_features":["Scheduled or manual execution","Reads batch input from CSV and processes rows","GPT-4 powered SEO-optimized Markdown generation with Jekyll front matter","Automated SEO-friendly slug and _posts/YYYY-MM-DD-title.md file creation","Commits new posts directly to GitHub repo via GitHub node/actionable commit step"],"target_audience":["Bloggers and content creators","Content/SEO marketers","Developers building content automation pipelines for static sites (Jekyll)"]}


name: Find the Best Favicon from Multiple Sources with GPT-4 Vision Analysis
author_name: Lucas Walter
author_username: lucaswalter
categories: []
created_at: 2025-07-02T15:29:35.749Z
updated_at: 2025-07-02T15:29:35.749Z
url: https://n8n.io/workflows/5599
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  Who's it for

  This workflow is perfect for directory site creators, content managers, and developers who need to automatically find and select the highest quality favicon or logo for websites they're showcasing. Instead of manually hunting down brand assets or settling for blurry default icons, this workflow does the heavy lifting by fetching multiple options and using AI to pick the best one.

  How it works

  The workflow takes a website URL and domain as input, then intelligently fetches favicon images from three different sources:

  Google's Favicon API - Gets the site's actual favicon
  Logo.dev - Provides high-quality brand logos  
  Clearbit - Alternative logo source for business websites

  Once all images are collected, the workflow uses OpenAI's vision model to analyze each icon based on:
  Image quality and resolution (minimum 256x256)
  Brand authenticity (avoiding generic framework icons)
  Visual clarity without artifacts or blur
  Professional presentation suitable for directory listings

  The AI assigns quality scores from 0.0 to 1.0, and the workflow automatically returns the URL of the highest-scoring favicon.

  Requirements

  OpenAI API key (for image analysis)
  Logo.dev API key (free tier available)

  How to set up

  Configure API credentials:
     Add your OpenAI API key to n8n credentials
     Sign up for Logo.dev and add your API token
     The Clearbit and Google APIs require no authentication

  Test the workflow:
     Use the pinned test data (Fyxer AI example) or replace with your own
     Ensure all HTTP nodes can successfully fetch images
     Verify the AI analysis is working by checking the quality scores

  Customize input format:
     Modify the workflow trigger to accept your preferred input format
     Adjust the domain extraction logic if needed for your use case

  How to customize the workflow

  For different quality criteria:
  Edit the AI prompt in the "analyze_each_icon" node to emphasize different aspects (transparency, size, style preferences)

  For additional favicon sources:
  Add more HTTP Request nodes pointing to other favicon/logo APIs
  Update the merge node to handle additional inputs
  Modify the final URL construction logic to handle new sources

  For batch processing:
  Wrap this workflow in a loop to process multiple websites at once
  Add error handling for failed requests or AI analysis timeouts

  The workflow is designed to be reliable and handles errors gracefully - if one favicon source fails, it continues with the available options and still provides the best result possible.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.httpRequest","n8n-nodes-base.filter","n8n-nodes-base.set","n8n-nodes-base.filter","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4884 characters]

metadata_json:
  {"categories":["automation","integration","data processing"],"complexity":"medium","use_cases":["Automatically select highest-quality favicon/logo for website listings","Directory site asset curation","Content management and editorial automation","Brand asset verification and quality control","Batch processing of multiple domains"],"estimated_setup_minutes":15,"required_services":["OpenAI (vision / GPT-4o / image analysis)","Logo.dev API","Clearbit (logo API)","Google Favicon API","n8n instance"],"key_features":["Fetches favicons/logos from multiple sources (Google Favicon API, Logo.dev, Clearbit)","AI vision analysis to score images by quality, authenticity, and clarity","Automatically selects and returns highest-scoring favicon URL","Configurable AI prompt and quality criteria","Graceful error handling when sources fail; continues with available images','Supports batch processing and easy extension with more sources"],"target_audience":["Developers","Directory site creators","Content managers and editors for websites/listings pages"]}


name: Add TypeScript Intellisense Support to Code Nodes with JSDoc
author_name: Wyeth
author_username: wyeth
categories: []
created_at: 2025-07-02T18:18:34.988Z
updated_at: 2025-07-02T18:18:34.988Z
url: https://n8n.io/workflows/5602
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:34
description:
  Are you writing complex Code nodes and need Intellisense support? Follow this simple pattern to get autocomplete for any n8n or custom classes.

nodes_used:
  ["n8n-nodes-base.n8n","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.form","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","developer tools"],"complexity":"simple","use_cases":["Enable TypeScript-style autocomplete in Code nodes","Add JSDoc annotations for n8n and custom classes","Improve developer productivity and code quality in workflows","Standardize code node documentation for teams"],"estimated_setup_minutes":5,"required_services":["n8n instance (Code node)"],"key_features":["Pattern to add JSDoc/TypeScript Intellisense to Code nodes","Autocomplete for n8n built-in classes and APIs","Support for annotating custom classes to surface methods/properties","Quick, copy-paste setup usable across multiple Code nodes"],"target_audience":["developers","automation engineers","n8n workflow authors"]}


name: Automated Stale User Re-Engagement System with Supabase, Google Sheets & Gmail
author_name: iamvaar
author_username: iamvaar
categories: []
created_at: 2025-07-02T18:19:51.584Z
updated_at: 2025-07-02T18:19:51.584Z
url: https://n8n.io/workflows/5603
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  Built this workflow because most of our users signed up, then vanished after ~30 days.
  It runs daily, grabs those stale users from Supabase, updates a Google Sheet for tracking, and automatically sends each one a personalized HTML email through Gmail to bring them back.

  All fully automated — so once it’s set up, it quietly does its job in the background.
  Currently, it only supports Supabase, but the concept should work with any DB or API if you swap out the request node.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.manualTrigger","n8n-nodes-base.removeDuplicates","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.lmChatGoogleVertex","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","user retention","integrations","email outreach","data tracking"],"complexity":"medium","use_cases":["Re-engage inactive/stale users","Automated personalized email campaigns","Maintain a tracking log of outreach in Google Sheets","Reduce churn and improve activation/retention metrics","Prototype outreach flows that can be adapted to other databases/APIs"],"estimated_setup_minutes":45,"required_services":["Supabase (or another DB/API)","Google Sheets","Gmail","Google Vertex (lmChat)"],"key_features":["Daily scheduled job to identify stale users","Fetch stale users from Supabase (replaceable with any DB/API)","Remove duplicates and update a Google Sheet for tracking","Send personalized HTML emails via Gmail","Use an LLM (lmChatGoogleVertex) to generate or personalize message content and agent orchestration for workflow logic"],"target_audience":["growth marketers","product managers","customer success teams / retention specialists', 'SaaS founders/operators, developers implementing outreach automation"]}


name: Search, Manage, and Analyze Podcasts with Listen API for AI Agents
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T18:24:49.663Z
updated_at: 2025-07-02T18:24:49.663Z
url: https://n8n.io/workflows/5605
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 Listen API: Podcast Search, Directory, and Insights API operations to AI agents.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add Listen API: Podcast Search, Directory, and Insights 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 Listen API: Podcast Search, Directory, and Insights 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://listen-api.listennotes.com/api/v2
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (23 total)

  🔧 Best_Podcasts (1 endpoints)

  • GET /best_podcasts: Delete Podcast by ID

  🔧 Curated_Podcasts (2 endpoints)

  • GET /curated_podcasts: Fetch Curated Podcast List by ID
  • GET /curated_podcasts/{id}: Fetch a curated list of podcasts by id

  🔧 Episodes (3 endpoints)

  • POST /episodes: Fetch Episode Recommendations
  • GET /episodes/{id}: Fetch detailed meta data for an episode by id
  • GET /episodes/{id}/recommendations: Fetch recommendations for an episode

  🔧 Genres (1 endpoints)

  • GET /genres: Fetch Podcast Genres

  🔧 Just_Listen (1 endpoints)

  • GET /just_listen: Fetch Random Podcast Episode

  🔧 Languages (1 endpoints)

  • GET /languages: Fetch Supported Languages

  🔧 Playlists (2 endpoints)

  • GET /playlists: Fetch Playlist Details by ID
  • GET /playlists/{id}: Fetch a playlist's info and items (i.e., episodes or podcasts).

  🔧 Podcasts (6 endpoints)

  • POST /podcasts: Fetch Podcast Audience Data
  • POST /podcasts/submit: Submit a podcast to Listen Notes database
  • DELETE /podcasts/{id}: Request to delete a podcast
  • GET /podcasts/{id}: Fetch detailed meta data and episodes for a podcast by id
  • GET /podcasts/{id}/audience: Fetch audience demographics for a podcast
  • GET /podcasts/{id}/recommendations: Fetch recommendations for a podcast

  🔧 Regions (1 endpoints)

  • GET /regions: Fetch Supported Regions

  🔧 Related_Searches (1 endpoints)

  • GET /related_searches: Fetch Related Search Terms

  🔧 Search (1 endpoints)

  • GET /search: Full-Text Search

  🔧 Spellcheck (1 endpoints)

  • GET /spellcheck: Spell Check Search Term

  🔧 Trending_Searches (1 endpoints)

  • GET /trending_searches: Fetch Trending Search Terms

  🔧 Typeahead (1 endpoints)

  • GET /typeahead: Typeahead Search

  🤖 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 Listen API: Podcast Search, Directory, and Insights 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","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.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","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","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"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["integration","AI agents","developer tools","data access"],"complexity":"medium","use_cases":["Expose Listen Notes Podcast Search/Directory/Insights API to AI agents via MCP","Enable AI-driven podcast search, recommendations, and metadata retrieval","Build conversational agents or tools that query podcast data (episodes, playlists, genres, trends)","Rapidly prototype AI integrations that need podcast audience and recommendation data"],"estimated_setup_minutes":20,"required_services":["Listen API (ListenNotes / https://listen-api.listennotes.com)","n8n instance with public webhook access (or tunneling service)","AI agent platforms or clients that support MCP (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["Full MCP-compatible server exposing 23 Listen API endpoints","Automatic parameter population via $fromAI() expressions","Native n8n HTTP Request handling and error management","Supports search, episodes, podcasts, playlists, genres, regions, trends, spellcheck, typeahead and more","Returns native Listen API response payloads to AI agents with minimal mapping needed (production-ready)"],"target_audience":["Developers and engineers integrating podcast data into AI agents","AI/ML practitioners building conversational tools or agent workflows","Product teams and researchers needing podcast metadata and audience insights to power features or analysis"]}


name: Complete Lyft API Integration for AI Agents with 16 Operations using MCP
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-02T18:27:51.067Z
updated_at: 2025-07-02T18:27:51.067Z
url: https://n8n.io/workflows/5606
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 16 Lyft API operations to AI agents.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add Lyft 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 Lyft 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.lyft.com/v1
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (16 total)

  🔧 Cost (1 endpoints)

  • GET /cost: Retrieve Cost Estimate

  🔧 Drivers (1 endpoints)

  • GET /drivers: List Nearby Drivers

  🔧 Eta (1 endpoints)

  • GET /eta: Retrieve Pickup ETA

  🔧 Profile (1 endpoints)

  • GET /profile: Retrieve User Profile

  🔧 Rides (7 endpoints)

  • GET /rides: Update Sandbox Ride Status
  • POST /rides: Request a Lyft
  • GET /rides/{id}: Get the ride detail of a given ride ID
  • POST /rides/{id}/cancel: Cancel a ongoing requested ride
  • PUT /rides/{id}/destination: Update the destination of the ride
  • PUT /rides/{id}/rating: Add the passenger's rating, feedback, and tip
  • GET /rides/{id}/receipt: Get the receipt of the rides.

  🔧 Ridetypes (1 endpoints)

  • GET /ridetypes: Update Driver Availability

  🔧 Sandbox (4 endpoints)

  • PUT /sandbox/primetime: Set Prime Time Percentage
  • PUT /sandbox/rides/{id}: Propagate ride through ride status
  • PUT /sandbox/ridetypes: Preset types of rides for sandbox
  • PUT /sandbox/ridetypes/{ride_type}: Driver availability for processing ride request

  🤖 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 Lyft 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.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.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["integration","automation","AI integration"],"complexity":"medium","use_cases":["Expose Lyft API endpoints to AI agents as an MCP tool","Automate ride requests, cancellations, ETA and cost checks","Sandbox testing and simulating ride flows","Embed Lyft functionality into custom AI apps or agent workflows","Provide a developer-facing API bridge for Lyft within n8n"],"estimated_setup_minutes":20,"required_services":["n8n instance with MCP support","Lyft API credentials","Publicly reachable URL/webhook (for MCP endpoint)","AI agent or platform (e.g., Claude, Cursor, custom agent) for consumption"],"key_features":["Exposes 16 Lyft API operations via an MCP-compatible endpoint","Supports cost, drivers, ETA, profile, rides and sandbox operations","Uses $fromAI() expressions to auto-populate parameters from agents","Returns native Lyft API responses and handles HTTP errors via n8n","Quick import + activate workflow pattern for rapid deployment (zero mapping required)"],"target_audience":["developers building AI agents or integrations","automation engineers and workflow builders using n8n","QA/testers using Lyft sandbox flows for simulation and testing"]}


name: Generate Structured Scientific Research PDF Summaries with GPT-4o
author_name: AiAgent
author_username: lifehacks
categories: []
created_at: 2025-07-02T20:15:33.660Z
updated_at: 2025-07-02T20:15:33.660Z
url: https://n8n.io/workflows/5607
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  Disclaimer
  This workflow contains a community node.

  What It Does
  Leverage the power of GPT-4o to seamlessly summarize a scientific research PDF of your choosing. By simply downloading a PDF of a scientific research article into a folder on your computer this powerful workflow will automatically read the article and produce a detailed summarization of the article. The workflow will then save this summarization onto your computer for future convenience.
  Who Is This For?
  The workflow is the perfect tool for all types of self-learners attempting to improve their knowledge base as efficiently as possible. It is a way to rapidly improve your knowledge base using peer reviewed scientific articles in a quick and efficient way. This workflow will provide a more detailed summary of the scientific research article than a typical abstract, while taking a fraction of the time it would take to read an entire paper. It will provide you with enough information to have a firm grasp on the information provided within the scientific article and will allow you to determine if you would like to dive deeper into the article.  This workflow is perfect for professionals who need to stay current on the most recent literature in their field, as well as the self-learners who enjoy diving deep into a specific topic. It can aid anyone who is performing academic research, a literature review, or attempting to increase their knowledge base in a field using peer reviewed sources.
  How It Works
  Utilizing the power of GPT-4o, the moment you save a PDF of a scientific research article to a predesignated folder it will being to read the article and produce a summary that will be saved into another designated folder on your computer via the following steps below.
  Search the internet and your favorite journal databases for a scientific article that interests you.
  With the n8n workflow activated, download a PDF of the scientific article and save it to a specific designated folder.
  Saving the scientific article to this folder will trigger the workflow to initiate.
  The workflow will then extract the contents of the PDF and pass the data along to an AI agent utilizing the power of GPT-4o.
  This AI agent will produce a detailed summary of the scientific article.
   	This summary will include the following:
  	Introduction heading discussing the importance of the article and the specific aims of the study
  	Methods heading detailing how the study was conducted, what variables they evaluated, what their inclusion and exclusion criteria were, and what their measurement standards were.
  	Results heading providing specific data provided in the study for all variables tested as well as the statistical significance of each result.
  	Summary heading evaluating the importance of the results, how it compares to other scientific articles in the same field, as well as the recommendations of the authors on how to interpret the data provided by the results.
  	Conclusion heading summarizing the strengths and weaknesses of the scientific article as well as providing deficiencies in knowledge on the subject that would be a good topic for future studies.
  After the AI agent has completed its summary, it will convert the summary to text and save it to a designated folder on your computer for future viewing.
  Set Up Steps
  You will need to create a folder on your computer where you would like to save your scientific article PDFs. You will then copy the pathway to this folder into the local file trigger node.
  You will need to obtain an Open AI API key from platform.openai.com/api-keys
  After you obtain this Open AI API key you will need to connect it to the Open AI Chat Model connected to the Summarizer Tools Agent.
  You will now need to fund your Open AI account. GPT-4o costs ~$0.01 to run the workflow.
  Finally, create a folder on your computer you wish to have the summarizations saved to. Copy the pathway to this folder into the Save to Folder node.
  Customization
  This workflow is easy to customize to a specific area of research to provide the best possible summarization. If you have a specific expertise in a field of study, you can customize the output to provide data at a higher level of understanding for that field. For example, if you are a marine biologist, you can change the portion of the text prompt in the summarizer tool from "You are a research expert who is providing data to another researcher." to "You are a marine biologist expert who is providing data to another marine biologist."
  Disclaimer
  If the pdf is too large, open AI will not be able to summarize it and will provide the error that you have reached your limit of requests.

nodes_used:
  ["n8n-nodes-base.localFileTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.convertToFile","n8n-nodes-base.readWriteFile","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4384 characters]

metadata_json:
  {"categories":["automation","document processing","AI summarization","research productivity"],"complexity":"medium","use_cases":["Summarize scientific research PDFs","Literature reviews and rapid article triage","Keeping up-to-date with field-specific literature","Preparing reading notes for academic or professional use","Converting papers into structured summaries for teaching or collaboration"],"estimated_setup_minutes":15,"required_services":["OpenAI (GPT-4o) API","Local filesystem access (folder watch/save)","Source of PDFs (journal databases, preprint servers, publisher websites)","n8n (with community node used in workflow)"],"key_features":["Automatically triggers on PDF saved to a watched folder","Extracts text from PDF","Uses GPT-4o agent to generate a structured summary (Introduction, Methods, Results, Summary, Conclusion)","Saves generated summary to a designated folder","Customizable prompt/agent to tailor summaries to a discipline or audience"],"target_audience":["Researchers and academics","Graduate students and PhD candidates","Self-learners and knowledge workers who read scientific literature regularly','Clinicians and professionals needing quick article summaries"]}


name: Convert YouTube Videos to Shorts with Klap & Auto-Post to Multiple Social Platforms
author_name: Dr. Firas
author_username: drfiras
categories: []
created_at: 2025-07-02T20:29:57.407Z
updated_at: 2025-07-02T20:29:57.407Z
url: https://n8n.io/workflows/5608
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  Convert YouTube videos to viral Shorts with Klap and auto-post with Blotato

  &gt; ⚠️ Disclaimer: This workflow uses Community Nodes and requires a self-hosted n8n instance.

  Who is this for?

  This workflow is perfect for content creators, YouTubers, marketing teams and entrepreneurs who want to effortlessly convert long YouTube videos into short, viral-ready clips and publish them automatically on TikTok, Instagram, YouTube Shorts and other platforms.

  What problem is this workflow solving?

  Manually creating short, engaging clips from YouTube videos takes hours:
  Selecting highlights
  Adding subtitles and effects
  Downloading and editing
  Posting individually on each platform

  This workflow eliminates all of that:
  AI-powered Shorts generation with Klap
  Smart scheduling based on your posting calendar
  Full automation of uploads to multiple platforms

  What this workflow does

  From a simple YouTube link sent via Telegram, the workflow:
  Extracts the YouTube URL and number of Shorts requested
  Sends the video to Klap for AI-powered Shorts generation
  Checks when the Shorts are ready
  Schedules publication times based on your custom settings
  Uploads the Shorts to Blotato
  Auto-posts on TikTok, YouTube Shorts, Instagram and more
  Sends a confirmation recap to Telegram

  Setup

  Connect your Telegram bot to the trigger node
  Add your Klap API key for video processing
  Link your Google Sheets with your scheduling preferences
  Add your Blotato API key and social platform IDs
  Adjust the number of Shorts generated if needed
  Modify the scheduling logic or time windows in the Google Sheets

  How to customize this workflow to your needs

  Change AI video settings in the Klap API request  
  Adjust time windows and frequency in the scheduling nodes  
  Limit the workflow to specific platforms (e.g., TikTok only)  
  Add a manual approval step before publishing  
  Modify the Telegram recap message content  



  📄 Documentation: Notion Guide

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

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegramTrigger","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
  [encoded data, 8744 characters]

metadata_json:
  {"categories":["automation","content creation","social media","video processing","integration"],"complexity":"complex","use_cases":["Convert long YouTube videos into short viral-ready clips","Automate multi-platform posting (TikTok, Instagram, YouTube Shorts)","Schedule posts based on custom calendar/preferences","Bulk content repurposing and cross-posting","Triggered workflows via Telegram with recap notifications"],"estimated_setup_minutes":60,"required_services":["Klap API (AI video/shorts generation)","Blotato (upload & cross-posting)","Telegram Bot (trigger & recaps)","Google Sheets (scheduling/preferences)","YouTube account (source videos)","Destination platform accounts/APIs: TikTok, Instagram, YouTube Shorts","Self-hosted n8n instance (community nodes)"],"key_features":["AI-powered Shorts generation (Klap)","Automated readiness checks and polling","Scheduling logic driven by Google Sheets","Auto-upload to Blotato and multi-platform posting","Telegram-based trigger and confirmation recap messages','Configurable generation count and scheduling windows','Supports adding manual approval step or limiting target platforms"],"target_audience":["Content creators and YouTubers","Social media managers and marketing teams","Growth/marketing entrepreneurs and small agencies"]}


name: AI-Powered Lead Generation with Apollo, GPT-4, and Telegram to Database
author_name: Paul
author_username: diagopl
categories: []
created_at: 2025-07-02T22:02:15.494Z
updated_at: 2025-07-02T22:02:15.494Z
url: https://n8n.io/workflows/5611
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  AI-Powered Lead Generation with Apollo, GPT-4, and Telegram to Database

  Overview

  This intelligent lead generation workflow transforms voice commands or text input into verified prospect lists through automated Apollo.io scraping. The system processes natural language requests, extracts search parameters using AI, and delivers clean, verified contact data directly to your database.

  Key Features

  🎤 Voice & Text Input Processing
  Voice Recognition**: Converts audio messages to text using OpenAI's transcription API
  Natural Language Processing**: AI agent interprets requests and extracts search criteria
  Flexible Input**: Supports both voice commands and text messages

  🔍 Smart Lead Scraping
  Apollo.io Integration**: Automated scraping using official Apollo.io API
  Dynamic URL Generation**: Builds search URLs based on extracted parameters
  Intelligent Parsing**: Processes location, industry, and job title criteria

  ✅ Email Verification & Filtering
  Verified Emails Only**: Filters results to include only verified email addresses
  Duplicate Prevention**: Compares against existing database to avoid duplicates
  Data Quality Control**: Ensures high-quality prospect data

  📊 Automated Data Management
  Database Integration**: Automatic storage in PostgreSQL/Supabase
  Structured Data**: Organizes contacts with complete profile information
  Real-time Updates**: Instant database updates with new prospects

  How It Works

  Input Processing: Receive voice message or text command
  AI Analysis: Extract search parameters (location, industry, job titles)
  URL Construction: Build Apollo.io search URL with extracted criteria
  Data Scraping: Retrieve prospect data via Apollo.io API
  Email Verification: Filter for verified email addresses only
  Duplicate Check: Compare against existing database records
  Data Storage: Save new prospects to database
  Confirmation: Send success notification with count of new leads

  Supported Search Parameters

  Location**: City, state, country combinations
  Industry**: Business sectors and verticals
  Job Titles**: Executive roles, departments, seniority levels
  Company Size**: Organization scale and employee count

  Data Fields Extracted

  Contact Information
  First Name & Last Name
  Email Address (verified only)
  LinkedIn Profile URL
  Phone Number (when available)

  Professional Details
  Current Job Title
  Company Name
  Industry
  Seniority Level
  Employment History

  Location Data
  City & State
  Country
  Full Location String

  Company Information
  Website URL
  Business Industry
  Organization Details

  Technical Architecture

  Core Components
  n8n Workflow Engine**: Orchestrates the entire process
  OpenAI Integration**: Powers voice transcription and AI analysis
  Apollo.io API**: Source for prospect data
  PostgreSQL/Supabase**: Database storage and management

  API Integrations
  OpenAI Whisper API for voice transcription
  OpenAI GPT for natural language processing
  Apollo.io API for lead data retrieval
  Supabase API for database operations

  Use Cases

  Sales Teams
  Quickly build prospect lists for outreach campaigns
  Target specific industries or job roles
  Maintain clean, verified contact databases

  Marketing Professionals
  Generate targeted lead lists for campaigns
  Research prospects in specific markets
  Build comprehensive contact databases

  Business Development
  Identify potential partners or clients
  Research competitive landscapes
  Generate contact lists for networking

  Recruitment
  Find candidates in specific locations
  Target particular job roles or industries
  Build talent pipeline databases

  Benefits

  ⚡ Speed & Efficiency
  Voice commands for instant lead generation
  Automated processing eliminates manual work
  Batch processing for large prospect lists

  🎯 Precision Targeting
  AI-powered parameter extraction
  Flexible search criteria combinations
  Industry and role-specific filtering

  📈 Data Quality
  Verified email addresses only
  Duplicate prevention
  Structured, consistent data format

  🔄 Automation
  End-to-end automated workflow
  Real-time database updates
  Instant confirmation notifications

  Setup Requirements

  Prerequisites
  n8n workflow platform
  OpenAI API access
  Apollo.io API credentials
  PostgreSQL or Supabase database
  Messaging platform integration

  Configuration Steps
  Import workflow into n8n
  Configure API credentials
  Set up database connections
  Customize search parameters
  Test with sample voice/text input

  Customization Options

  Search Parameters
  Modify location formats
  Add custom industry categories
  Adjust job title variations
  Set result limits

  Data Processing
  Customize field mappings
  Add data validation rules
  Implement additional filters
  Configure output formats

  Integration Options
  Connect to CRM systems
  Add email marketing tools
  Integrate with sales platforms
  Export to various formats

  Success Metrics

  Processing Speed**: Voice-to-database in under 30 seconds
  Data Accuracy**: 95%+ verified email addresses
  Automation Level**: 100% hands-free operation
  Scalability**: Process 500+ leads per request

  Transform your lead generation process with intelligent automation that understands natural language and delivers verified prospects directly to your database.

nodes_used:
  ["n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.filter","n8n-nodes-base.limit","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.postgres","n8n-nodes-base.compareDatasets","n8n-nodes-base.noOp","n8n-nodes-base.supabase","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@apify/n8n-nodes-apify.apify","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8476 characters]

metadata_json:
  {"categories":["automation","integration","data processing","lead generation","ai/nlp"],"complexity":"complex","use_cases":["Sales prospecting and list building","Targeted marketing campaign list generation","Business development research and partner discovery","Recruitment sourcing and talent pipeline building","Automated database enrichment and hygiene"],"estimated_setup_minutes":45,"required_services":["n8n platform","OpenAI (Whisper for transcription & GPT for NLP)","Apollo.io API","PostgreSQL or Supabase (database)","Telegram (messaging integration)"],"key_features":["Voice and text input processing (Whisper + GPT)","Natural language parameter extraction for searches","Automated Apollo.io lead scraping with dynamic URL construction","Email verification and filtering (verified-only)","Duplicate detection against existing database records to prevent re-imports"],"target_audience":["Sales teams","Marketing professionals","Business development teams/analysts\",\"Recruiters\",\"Automation/operations engineers"]}


name: Import CSV Contacts to Notion Database from Google Drive
author_name: Sebastien
author_username: sebn8n
categories: []
created_at: 2025-07-02T22:38:33.300Z
updated_at: 2025-07-02T22:38:33.300Z
url: https://n8n.io/workflows/5612
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  How to use
  Get a .csv file with your contacts (you can download this from any contact manager app)
  Set API key for Google Drive API, and Notion (you need to create a "connection" in Notion)
  Create Database for your contacts in Notion
  Choose which properties to extract from the .csv and pass it in to the Notion database. Right now, it transfer 4 pieces of information: full name, email, phone, and company.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.code","n8n-nodes-base.notion","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["integration","data import","productivity","CRM"],"complexity":"medium","use_cases":["Import contacts from CSV into Notion","Migrate contact lists from contact managers to Notion","Automate population of a Notion contacts database","Periodic bulk updates of contact data"],"estimated_setup_minutes":15,"required_services":["Google Drive API (Google account)","Notion API (Notion integration/connection)"],"key_features":["Reads CSV file from Google Drive","Extracts contact fields (full name, email, phone, company)","Maps CSV fields to Notion database properties","Creates new pages/entries in a Notion database","Manual trigger with progress/sticky note feedback"],"target_audience":["small business owners","sales and marketing teams","operations/admins managing contact lists in Notion\",\"Notion users wanting automated imports"]}


name: Send Gmail Messages with Custom Aliases and Attachments via API
author_name: Jacob @ vwork Digital
author_username: jacob-vwork-digital
categories: []
created_at: 2025-07-02T22:47:02.127Z
updated_at: 2025-07-02T22:47:02.127Z
url: https://n8n.io/workflows/5613
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  This n8n template allows you to send emails with a custom alias from your Gmail account
  Since the native Gmail node has some limitations regarding use of email aliases, this template allows you to set up your own internal endpoint/sub-workflow to send emails as an email alias .

  How it works
  This workflow uses a Code node and the Gmail API via an HTTP node to format the email content and send using an alias on your Gmail account.

  Setup instructions
  You must have added the email address as an alias you wish to send as in your Gmail account, guide on how to do so here.
  You must have created a Gmail credential in N8N, guide on how to do so here.
  Use your Gmail OAuth Credential in the HTTP node. 
  Use this template as an API endpoint or a sub-workflow, and send this payload to it via POST:
  {
    "senderName": "SENDER NAME HERE",
    "fromEmail": "FROM EMAIL HERE",
    "replyTo": "REPLY TO EMAIL HERE",
    "toEmail": "jacob@vwork.digital",
    "subject": "SUBJECT LINE HERE",
    "htmlBody": "HTML BODY HERE - MUST BE JSON STRINGIFIED",
    "file_urls": [
      "FILE URLS FOR ATTACHMENTS HERE"
    ]
  }
  Notes
  Only the following are required fields:
  fromEmail
  toEmail
  subject
  htmlBody
  Customizing this workflow
  You can easily convert this to a sub-workflow by swapping out the Webhook trigger for a "When executed by another workflow" trigger

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.webhook"]

workflow_json_compressed:
  [encoded data, 4432 characters]

metadata_json:
  {"categories":["integration","automation","email"],"complexity":"medium","use_cases":["Send transactional or campaign emails from n8n using a custom alias","Expose an internal API endpoint/sub-workflow for other workflows or services to send email","Send emails with attachments provided as public file URLs","Override reply-to and sender name for outgoing messages"],"estimated_setup_minutes":15,"required_services":["Gmail (Google Workspace or Gmail account) with alias configured","n8n instance","Gmail OAuth credential created in n8n","Publicly accessible file URLs or storage for attachments"],"key_features":["Send mail via Gmail API using a custom alias (bypasses native Gmail node limitation)","Accepts JSON payload (senderName, fromEmail, replyTo, toEmail, subject, htmlBody, file_urls)","Supports HTML body and file attachments (via URLs)","Can be used as webhook/API endpoint or converted to sub-workflow","Uses Code and HTTP nodes to format and call Gmail API"],"target_audience":["Developers","Automation engineers","DevOps / IT administrators who manage workflows and email sending"]}


name: Website Scam Risk Detector with GPT-4o and SerpAPI
author_name: AiAgent
author_username: lifehacks
categories: []
created_at: 2025-07-03T01:55:28.771Z
updated_at: 2025-07-03T01:55:28.771Z
url: https://n8n.io/workflows/5614
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  What It Does
  This intelligent workflow simplifies the complex task of determining whether a website is legitimate or potentially a scam. By simply submitting a URL through a form, the system initiates a multi-agent evaluation process. Four dedicated AI agents—each powered by GPT-4o and connected to SerpAPI—analyze different dimensions of the website: domain and technical details, search engine signals, product and pricing patterns, and on-site content analysis. Their findings are then passed to a fifth AI agent, the Analyzer, powered by GPT-4o mini, which consolidates the data, scores the site on a scale of 1–10 for scam likelihood, and presents the findings in a clear, structured format for the user.

  Who It's For
  This workflow is ideal for anyone who needs to quickly and reliably assess the trustworthiness of a website. Whether you're a consumer double-checking a store before making a purchase, a small business owner validating supplier sites, a cybersecurity analyst conducting threat assessments, or a developer building fraud detection into your platform — this tool offers fast, AI-powered insights without the need for manual research or technical expertise. It's designed for both individuals and teams who value accurate, scalable scam detection.

  How It Works
  The process begins with a simple form submission where the user enters the URL of the website they want to investigate. Once submitted, the workflow activates four specialized AI agents—each powered by GPT-4o and connected to SerpAPI—to independently analyze the site from different angles:

  Agent 1 examines domain age, SSL certificates, and TLD trustworthiness.

  Agent 2 reviews search engine results, forum mentions, and public scam reports.

  Agent 3 analyzes product pricing patterns and brand authenticity.

  Agent 4 assesses on-site content quality, grammar, legitimacy of claims, and presence of business info.

  Each agent returns its findings, which are then aggregated and passed to a fifth AI agent—the Analyzer. This final agent, powered by GPT-4o mini, evaluates all the input, assigns a scam likelihood score from 1 to 10, and compiles a neatly formatted summary with organized insights and a disclaimer for context.

  Set UP
  You will need to obtain an Open AI API key from platform.openai.com/api-keys
  After you obtain this Open AI API key you will need to connect it to the Open AI Chat Model for all of the Tools agents (Analyzer, Domain & Technical Details, Search Engine Signals, Product & Pricing Patterns, and Content Analysis Tools Agents).
  You will now need to fund your Open AI account. GPT 4o costs ~$0.01 to run the workflow.
  Next you will need to create a SerpAPI account at https://serpapi.com/users/sign_up
  After you create an account you will need to obtain a SerpAPI key.
  You will then need to use this key to connect to the SerpAPI tool for each of the tools agents (Domain & Technical Details, Search Engine Signals, Product & Pricing Patterns, and Content Analysis Tools Agents)
  Tip: SerpAPI will allow you to run 100 free searches each month. This workflow uses ~5-15 SerpAPI searches per run. If you would like to utilize the workflow more than that each month, create multiple SerpAPI accounts and have an API key for each account. When you utilize all 100 free searches for an account, switch to the API key for another account within the workflow.

  Disclaimer
  This tool is designed to assist in evaluating the potential risk of websites using AI-generated insights. The scam likelihood score and analysis provided are based on publicly available information and should not be considered a definitive or authoritative assessment. This tool does not guarantee the accuracy, safety, or legitimacy of any website. Users should perform their own due diligence and use independent judgment before engaging with any site.

  N8N, OpenAI, its affiliates, and the creators of this workflow are not responsible for any loss, damages, or consequences arising from the use of this tool or the actions taken based on its results.

nodes_used:
  ["n8n-nodes-base.merge","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.toolSerpApi","@n8n/n8n-nodes-langchain.toolSerpApi","@n8n/n8n-nodes-langchain.toolSerpApi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.toolSerpApi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.formTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6256 characters]

metadata_json:
  {"categories":["fraud detection","security","automation","integration"],"complexity":"complex","use_cases":["Quickly assess whether an e-commerce or informational website is likely a scam","Pre-screen suppliers or partner sites for small businesses","Support cybersecurity threat assessments and triage","Integrate scam-detection into apps or workflows (developers)","Consumer-facing verification before purchases"],"estimated_setup_minutes":30,"required_services":["OpenAI (GPT-4o, GPT-4o-mini)","SerpAPI","n8n platform"],"key_features":["Multi-agent analysis (4 GPT-4o agents) covering domain, search signals, product/pricing, and on-site content","Aggregator/Analyzer agent (GPT-4o mini) that consolidates results and scores scam likelihood 1–10","Form-based URL submission and structured summary output with disclaimer","Uses SerpAPI for search and public signals (configurable API keys)","Configurable, modular agents allowing parallel checks and results merging"],"target_audience":["Consumers","Small business owners","Cybersecurity analysts / fraud investigators"]}


name: Email-Based Book Recommendations with Ollama LLM and OpenLibrary API
author_name: Oneclick AI Squad
author_username: oneclick-ai
categories: []
created_at: 2025-07-03T02:24:11.108Z
updated_at: 2025-07-03T02:24:11.108Z
url: https://n8n.io/workflows/5615
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow listens for incoming book request emails, extracts the user's intent using the Ollama LLM, queries book data (title, summary, details) via an API, and sends a personalized recommendation email. Ideal for automated book suggestions using LLMs and structured APIs, great for newsletters, reading clubs, and educational bots.

  How It Works

  Email Request: Triggers the workflow when a new email with a book request is received.
  Analyze Email with Ollama: Extracts user intent and book preferences using the Ollama LLM.
  Create Book Search Query: Generates a query based on the analyzed intent.
  Book Search API: Fetches book data (title, summary, details) from an API.
  Check API Response: Validates the API response for book availability.
  Handle No Book Found: Manages cases where no suitable book is found.
  Extract Book Summary: Pulls the summary from the API response.
  Wait for Summary Response: Pauses to ensure summary data is ready.
  Retrieve Book Details: Gathers additional book details.
  Format Book Data: Structures the book information for the recommendation.
  Enhance Data with Code: Refines the data using custom code.
  Generate Email Content: Creates a personalized email recommendation.
  Send Email: Delivers the recommendation to the user.

  How to Use

  Import the workflow into n8n.
  Configure email credentials for the Email Request node.
  Set up Ollama LLM API credentials and endpoint.
  Configure the Book Search API with appropriate credentials and endpoint.
  Test with a sample email requesting a book recommendation.
  Adjust the Generate Email Content node for custom email templates if needed.
  Ensure the Send Email node is linked to a valid email service.

  Requirements

  Email service API credentials (e.g., Gmail, SMTP)
  Ollama LLM API access
  Book Search API credentials

  Customizing This Workflow

  Modify the Analyze Email with Ollama node to refine intent extraction for specific genres.
  Adjust the Book Search API query to target different book databases.
  Customize the Generate Email Content node to include additional details like author bios.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOllama","n8n-nodes-base.emailReadImap","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4720 characters]

metadata_json:
  {"categories":["automation","integration","recommendation","email automation","AI/LLM"],"complexity":"medium","use_cases":["Automated personalized book recommendations","Newsletter or reading-club recommendation emails","Educational content suggestions for students or classrooms","Customer engagement for bookstores/libraries","Prototype/testing of LLM-powered recommendation flows"],"estimated_setup_minutes":45,"required_services":["Email service (Gmail, SMTP, or other SMTP provider)","Ollama LLM API access","Book Search API (e.g., OpenLibrary or other book database)","n8n instance or server"],"key_features":["Email-triggered workflow to start on incoming requests","LLM (Ollama) analysis to extract intent and preferences","Automated creation of search queries and API-based book lookup","Response validation and handling for no-results cases","Data extraction and enrichment (summary, details) with code nodes for refinement"],"target_audience":["Developers integrating LLMs with APIs","Marketers and newsletter creators","Community managers for reading clubs or book communities"]}


name: Automated GitLab Backup of Workflows with Username Organization
author_name: Oneclick AI Squad
author_username: oneclick-ai
categories: []
created_at: 2025-07-03T02:59:33.655Z
updated_at: 2025-07-03T02:59:33.655Z
url: https://n8n.io/workflows/5616
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:34
description:
  Overview
  This solution ensures the secure backup and version control of your self-hosted n8n workflows by storing them in a GitLab repository. It compares current workflows with their GitLab counterparts, updates files when differences are detected, and organizes them in user-specific folders (e.g., repo -&gt; username -&gt; workflow.json). Backups are triggered manually or weekly, with a success notification sent via email.

  Operational Process
  Manual Backup Trigger**: Initiates the backup process on demand.
  Scheduled Weekly Backup**: Automatically triggers the backup every week.
  Fetch N8N Workflows**: Retrieves all workflows from n8n using the API (getAll:workflow).
  Prepare Backup Metadata**: Generates metadata, including user details for folder organization.
  Process Each Workflow**: Handles each workflow individually for processing.
  Format Workflow for GitLab**: Structures workflows with proper versioning for GitLab compatibility.
  Rate Limit Control**: Manages API rate limits to ensure smooth operation.
  Create to GitLab Repository**: Saves workflows to GitLab; creates a new file if it doesn’t exist.
  Check Backup Status**: Verifies if the file exists; if true, proceeds to update; if false, loops back.
  Update Backup Summary**: Updates the existing file in GitLab with the latest version.
  Log Backup Results**: Records the outcome of the backup process.
  Send Email**: Sends a confirmation email:  
    "Hello, The scheduled backup of all n8n workflows has been completed successfully. All workflows have been committed to the GitLab repository without any errors. Regards, n8n Automation Bot"

  Implementation Guide
  Import this solution into your n8n instance.
  Configure GitLab API credentials and specify the target repository.
  Set up n8n API access to enable workflow retrieval.
  Customize the Prepare Backup Metadata node to map users to folders as needed.
  Test the process using the Manual Backup Trigger to confirm GitLab integration.
  Schedule weekly backups via the Scheduled Weekly Backup node (recommended for Fridays).

  Requirements
  GitLab API credentials with write access
  n8n API access for workflow retrieval
  A configured GitLab repository

  Customization Options
  Adjust the Prepare Backup Metadata node to include additional user fields.
  Modify the Rate Limit Control node to accommodate varying API limits.
  Tailor the Send Email node to include custom notification details.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.n8n","n8n-nodes-base.set","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.gitlab","n8n-nodes-base.emailSend","n8n-nodes-base.gitlab","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  H4sIAAAAAAAAE+VZe2/cNhL/KoQanBOcuNGDei1w6DlO3eYudto4SQHHbsDHaFexltxKlDdbd7/7gXqt1tbaTlscDrh/FqvhcDgczvxmOLyxMmFNreD8fB1E+sPr9Ff903l6bNnWAjS1pjdWJktNJYdXhk+IMIGUprHnejwiVHhOGDmOcB0S+YnwfS8J4piGqZ/GfuxSElISu6lPeMK5F7uWbWlYLHOq4agAUZ6BrpZHarHMQYOwprqoYGNbki7AmlqHlVYLqkGgF5RfVUukUiRjiX5WxVWaq1WJtELfZ/o1ZehNMaMy+w0EYmv0voSilmFbms5Ka/rx0rakEmD+3jRbjpIkCtKQ4oBSHxMSeJhRJ8GMxAmwmLtJZOa3qpxQWdG80+Ndkc1mUBjx66UZlrHEtXzMaAmTRc295VqqMtOZktb0I449x/aDS9ta0oIuQENRWtObTSPqAxRlzedu7FZPTwQicMMAM0oCTFyH45gHFPsRd4nHPMK5u9XzjM9BVDkI9DPAVb5uNd6radny79fVu6usVVQ5NL6hobimeW3VNIPcKLwCuCrNgo3IQ/2Srq3pRyOlJ/2gqsKauvHmcmOOW2koX8njXK2saUrzEm5bY+L19gjD0OPcCXAKxMMkjR1Mg4RiRsPIAeESP/W29jgGzefoND7dOs1eW8hY3tp/6Di2O7L/NMu351bArxWU+s3SzKppG9viBQiQOqN5PUHG8nCZ1SYze3h1eOrGP/37xQdHqrfFgmz1Ne5NOVeV1AgjDaW2Nvt9w4mFywPOceQFDBOeMEwjIDgIRBpwERHqRVvZPxawpAV0TnwCmgqq6X7fAH3LHn48bg+13btt0bLMZnIBUtdjO59d8LFaBSyoHsRYQ3zZ0FqVSl1kcmbZ1jXNK0P4x80NeiLVymh3riQ8PXj/7ujg2USrY1UsqH56sF6v1/jkBAtx8AxtNlZvrXbRJdXz24v+2ND2Ltpwlc8ftXi97MOsJyetfpcb28okzysBb/QcimMTSGUPhjtn70/8fj+cUUgIodgLPQ8TChFOEu7iIISUB6FwIp4OT19xKEv0HeXzPhj2n/0yz/Qr+YJqPofylhu44YNucEfvbfwmPk19SHAACceE8BDHhPo4oRGPBOfUjZNB/NbG6vVFqSpaxH+824aOjV3i/HmvXbVa4DZsWh078sudYFLsM3C967kXEqH6B6ELKxMX1hQ9+VwqOcmE3ZGN0O2A+eqHKNfZ9WCw+d7ONDYYTDWf/SBXUgKvN7xlGRB7xhK0zuRswNVRtiya6oyb7Q6YelrPZlLvlsF89UPXjV+8GpigJ23nN9niyIDhQM6Aut1dAaZOOBzw9aSeqVqK20xbkkRocyGHcFELUAVuC4n2sFvqaVtd3IdS/QFOtHqtVlAc0RKePpu0sV4+PbguqnKus4Nn6FvUf6DpY6YulfpMZTOz/f/IiQWdSSjn7dTu63GT6We6bibW/9AUHcxAQkHzgx2oTbMcbhnOkL7OagUsc8rh6fOPv1D82yE+d3BycYE/XT6f2ejg08GzLcenv9+l/fLp909PanKNsxMj+JaGu6nAkB5KBAZrunhv0sH/3Sk//y+c0h9NiQKo5zEXMLjMFPXEwSwKIsxo5Ph+kgSOGLjkW6oBvc4WmUZHSupC5XuTyopmt7KKF/dpZQVsrtRVfUPiThh7PnMwCf0IE/AcnHDXweB4DvNpREJi0ttuJqILg2bW1LtT6k22xR5xE+p7CcEp+BwTF2JM49DHPktc4vM4ZWyQlI7mwK+6Uu9MU13tL3yzdHdrkfeYjMmVFFn3PRjqwN2aeraVQ6o/tMFj2RanJZyBNCtdQ3Oc7Y5pngnarF+HHddWvcaCZdIArjW1qBTW7rJdYg5BMGDMx67gCSYQOZgJwrDDHQ/CICKxE1u2pZZQNLJuBjGvoZh0IxP4tTIl+10EaDga/Vqmze72tugFRaEKg4e2VWSzec/xggrU3hYQRsscaAmI1we1VlWBBsZuLkY7vuANLkEsTaggYYw9hwpMXI9iyoFhxyfghFESRLGz9YXXatZ5wlsoq1zvd4Wx4in8C0qn2iQ4V7OtVjXpdU3ZC7fHNDN3Wa3Qsi1feyN3+QRtNlO0a/pvJwsoSzoD9Pvv6OC9vJJqJVE9tJumyoobobt6tcQHNDtruNIqz9edciBG1auL1n5gUED8qeo/EmHEHd/FMScUEydhOOER4DCJooB5MWXpoC/wvi50ejyoFgtarPd6wSzTeV1hDxwhIWN9C0utJJjgbKbgqqybCKygks+tqbWgmblU96m1DZOnB3ex9+DZJNOwmPTmMxPaKIJSVQXvkvTtcBQ1NhdQa6uKdbsh1rU+zByzCBiMrRX419mb00lzqFm6fvoIhYZFvo1klec28p416nG1WGT6pPE5s0Jr7UfvtHOUTD5uzq4PoVTlAgp0ndG6PUabtllWlzu3OxHNOQ2bEcfk/OVLWr1iKy//4fCd2DpN21rb7UegkYZEjco6kxW8kSZkO+9tVwg84hEmCOaMAyaEJpgyN8JCpC5NXIcGbHDlOwMpECyMmH3+WY8avrspObyTkD3XT3jo4wAMVIZOiFlAUuyKhKRRJFzmOXcSsoYvxlV+gDxX9oW8kO/mgMq+t8b6diTN89rmfU2I5rREDEAi3rU1UTnAiomRdpjnOzOuoZ+yyLRuEE/PoWtubl0brTI9V5VGVK4bRCtriW9hRgthLlhGm8PeA9ALpetwGeB1WTVX06bbtNWj3ZVUOksz3jiQbWn1XX0WU4syPpmZ/xOuFiasCrXoxr6sf/vncKw+oebybk0bc971xXKhl70bfu9erY9jfvbzu3NyrarTgUOcvPsR4fFemDcokAJCIirAx8L3Y0x84mLK4xD7Ibjc9aMkDQb9kKP6fjjoIL/d4sfX4GLg7CuW/hAyPgr9/gTUPfl6NDsUAo0nNrwvrf3PQxJLXRFFMceeH/qYhILi2E0i7KU8jHzmMC+IBx6oM361Rqdq2Jq8XTnVPC3LsFuW1A4yUkTNwRSH1jQInUbb5tC++aZL069kprPaalNUg1DT+ihR876Qr5Eq0Krp82uFSk0LXcNGVyxZ+1vHEfGEF3GB3QSIMUCAWZoy7DDKzXuOS/cYwP16C4S+Y2MvvFs8cJWbaty3rVUmTAyYBvM9dunbgG9BFxlc0xz9DZm2dmOfutkP5QDSqBRo2bS9S7ToGt77rRLzAJzEdbGfuMI0JymOI5fhWITgORAGiZ+MWsX7eqt4D1gl7K3i+uResxzVtyQQqO3xZnJmozOtCjoDu7bB6QDTG1u1rNDYKK2RemA5G5X0GkrjTYsBRprsgwwCIPiSlRokby8wjZimnVYig3V4lZVgo1zNSlQ0t45GlxKkKBHtsmKT6icjh3Jptx3P/lGo60QaK8EX4JXZz5tC1Dh77RoZfRvRJARfUD9lDEecxZiEETNAGWAee5S4hDlOEjY3yq4LagSP3JamNw1cTz9+vKnbrHvKlBbTMyngizV1NpemuB/pMozJe1Q+Gl1g7Ko/tsIDd4A7su3t1AceD0bVGnt6G1PrwWepUenjD7Jj8u99AhyVPb7bMdn33azvs+djnjVGVRs/w3Gzfv2R7TuKv0r+vtfpv+bY7jHq2AL3df/G4+yeCB2N6PtacCMrbDb/AU7mMWeOIQAA

metadata_json:
  {"categories":["backup","integration","version control","automation"],"complexity":"medium","use_cases":["Automated backup of n8n workflows to GitLab","Version control and change tracking for workflows","Organizing backups by username for team-based repositories","Scheduled and on-demand backups for disaster recovery","Audit and compliance by maintaining commit history"],"estimated_setup_minutes":30,"required_services":["GitLab (API access, repository with write permissions)","n8n (API access to retrieve workflows)","Email/SMTP provider (for notifications)"],"key_features":["Manual and scheduled (weekly) backup triggers","Fetches all workflows from n8n and processes individually","Organizes files in repo by username (repo -> username -> workflow.json)","Creates new files or updates existing ones after diffing","Rate limit control and batch processing to avoid API throttling limits (splitInBatches, rate limit control node patterns)"],"target_audience":["n8n self-hosted administrators","DevOps / SRE teams","Automation engineers implementing CI/backup for workflows"]}


name: Generating SEO-Optimized Product Descriptions for Shopify and Google Shopping Using AI
author_name: Sebastian/OptiLever
author_username: lewxiangang
categories: []
created_at: 2025-07-03T03:18:07.250Z
updated_at: 2025-07-03T03:18:07.250Z
url: https://n8n.io/workflows/5617
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Tired of spending HOURS writing product descriptions that don’t rank or convert? This could be your solution.

  This free Product Description Writer workflow for n8n uses a multi-agent AI system to turn your product list into conversion-focused, SEO-ready copy. It analyzes your product images, identifies key features, and writes optimized titles and descriptions for platforms like Shopify and Google Shopping. It can process your entire catalog in minutes, saving you countless hours of manual work.

  This workflow is perfect for:
  🛒 Shopify stores
  🛒 Etsy sellers
  🛒 Product managers
  🛒 Digital marketers
  🛒 Anyone who hates writing product copy manually!

  How it works

  This workflow automates the entire product description process in a few high-level steps:
  Reads Your Products: The workflow starts by reading product data from your specified Google Sheet, including the product name, an image URL, and optional fields like brand voice or target market.
  Analyzes Product Images: It downloads each product image and uses an AI vision model (GPT-4o-mini) to perform a detailed visual analysis, extracting objective information like materials, colors, features, and structure.
  Writes Optimized Copy: The visual analysis and your original data are passed to two specialized AI agents. The first drafts a Shopify-optimized title and description, while the second refines it and generates additional SEO-focused copy for Google Merchant Center.
  Updates Your Spreadsheet: The final, optimized product titles and descriptions for both Shopify and Google are automatically written back to the original Google Sheet.

  Set up steps

  Setting up this workflow takes only a few minutes. You will need to configure credentials for the following services:
  Google Sheets**: To allow the workflow to read your product list and write back the results.
  OpenAI**: To power the AI agents that analyze images and generate the copy.

  Detailed instructions and customization tips are included in the sticky notes inside the workflow itself.

  Benefits
  Automated Vision-Based Copywriting**: Reduces manual description writing time.
  Multi-Channel Ready**: Outputs are optimized for both Shopify and Google Merchant Center standards.
  Brand Alignment**: Uses optional user-provided draft descriptions and brand voice to maintain brand tone.
  SEO and Conversion Focus**: Titles and descriptions are optimized for both search engines and consumer engagement.
  Image-Centric Accuracy**: Uses actual product images for accurate attribute extraction, minimizing errors from missing or vague text data.
  Tips & Customization
  To adjust brand voice or tone, modify the system prompts in the Shopify and GMC AI agents.
  To extend the workflow for scheduled runs, add a cron trigger or a Google Sheets "status column" filter.
  For QA/debugging, consider adding logging nodes to Slack or Discord, or export AI outputs to a review sheet before updating the main sheet.
  To improve Shopify or GMC field mappings, edit the final Google Sheets update node's column settings.
  For speed optimization, the batch size in the Loop Over Items node can be adjusted, but be mindful of API rate limits.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.editImage","n8n-nodes-base.if","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 14292 characters]

metadata_json:
  {"categories":["automation","e-commerce","content-generation","AI","data processing (ETL)"],"complexity":"medium","use_cases":["Bulk generation of SEO-optimized product titles and descriptions","Converting product images into attribute-driven copy","Preparing copy for Shopify and Google Merchant Center","Catalog enrichment and SEO optimization","Saving manual copywriting time for large catalogs"],"estimated_setup_minutes":10,"required_services":["Google Sheets (API/credentials)","OpenAI (GPT-4o-mini or compatible vision/LM models)","(Optional) Shopify API (if pushing directly)","(Optional) Google Merchant Center API (if pushing directly)","(Optional) Slack or Discord (for logging/QA)"],"key_features":["Image-based product attribute extraction using AI vision","Multi-agent AI pipeline: draft + refinement agents","Generates Shopify-optimized and Google Shopping (GMC) copy","Batch processing to handle entire catalogs quickly","Writes final outputs back to Google Sheets automatically"],"target_audience":["Shopify store owners","Ecommerce managers and product managers","Digital marketers and SEO specialists」「Small business owners and Etsy sellers」「Copywriters and catalog managers"]}


