# templates

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 11:38:22
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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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 11:38:23
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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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 11:38:23
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]


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 11:38:23
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

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

  ⚡ Quick Setup

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

  🔧 How it Works

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

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

  📋 Available Operations (23 total)

  🔧 Customer_Service_Metric_Task (3 endpoints)

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

  🔧 Inventory_Task (3 endpoints)

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

  🔧 Order_Task (3 endpoints)

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

  🔧 Schedule (6 endpoints)

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

  🔧 Schedule_Template (2 endpoints)

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

  🔧 Task (6 endpoints)

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

  🤖 AI Integration

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

  Response Format: Native Feed API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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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 11:38:23
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:
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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 11:38:22
description:
  Complete MCP server exposing 2 Negotiation API operations to AI agents.

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

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

  🔧 How it Works

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

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

  📋 Available Operations (2 total)

  🔧 Find_Eligible_Items (1 endpoints)

  • GET /find_eligible_items: Find Eligible Listings

  🔧 Send_Offer_To_Interested_Buyers (1 endpoints)

  • POST /send_offer_to_interested_buyers: Send Discount Offer

  🤖 AI Integration

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

  Response Format: Native Negotiation API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

nodes_used:
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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 11:38:22
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

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

  ⚡ Quick Setup

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

  🔧 How it Works

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

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

  📋 Available Operations (27 total)

  🔧 Geographies (1 endpoints)

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

  🔧 Locations (3 endpoints)

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

  🔧 Media (10 endpoints)

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

  🔧 Tags (3 endpoints)

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

  🔧 Users (10 endpoints)

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

  🤖 AI Integration

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

  Response Format: Native Instagram API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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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 11:38:23
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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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 11:38:22
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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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 11:38:23
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:
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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 11:38:22
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:
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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 11:38:22
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:
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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 11:38:20
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.

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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 11:38:20
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:
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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 11:38:21
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.

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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 11:38:22
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"]

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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 11:38:20
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:
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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 11:38:21
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:
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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 11:38:20
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"]

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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 11:38:21
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:
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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 11:38:22
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:
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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 11:38:22
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:
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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 11:38:21
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"]

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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 11:38:23
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.

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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 11:38:23
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:
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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 11:38:20
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.

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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 11:38:20
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

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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 11:38:20
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.

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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 11:38:22
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.

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

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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 11:38:22
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]


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 11:38:20
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]


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 11:38:21
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]


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 11:38:22
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:
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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 11:38:20
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:
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name: Scrape LinkedIn Profiles & Save to Google Sheets with Apify
author_name: Oneclick AI Squad
author_username: oneclick-ai
categories: []
created_at: 2025-07-03T03:57:18.386Z
updated_at: 2025-07-03T03:57:18.386Z
url: https://n8n.io/workflows/5618
scraped_at: 2025-09-14 11:38:20
description:
  This n8n workflow automates the process of scraping LinkedIn profiles using the Apify platform and organizing the extracted data into Google Sheets for easy analysis and follow-up.

  Use Cases
  Lead Generation**: Extract contact information and professional details from LinkedIn profiles
  Recruitment**: Gather candidate information for talent acquisition
  Market Research**: Analyze professional networks and industry connections
  Sales Prospecting**: Build targeted prospect lists with detailed professional information

  How It Works

  1. Workflow Initialization & Input
  Webhook Start Scraper**: Triggers the entire scraping workflow
  Read LinkedIn URLs**: Retrieves LinkedIn profile URLs from Google Sheets
  Schedule Scraper Trigger**: Sets up automated scheduling for regular scraping

  2. Data Processing & Extraction
  Data Formatting**: Prepares and structures the LinkedIn URLs for processing
  Fetch Profile Data**: Makes HTTP requests to Apify API with profile URLs
  Run Scraper Actor**: Executes the Apify LinkedIn scraper actor
  Get Scraped Results**: Retrieves the extracted profile data from Apify

  3. Data Storage & Completion
  Save to Google Sheets**: Stores the scraped profile data in organized spreadsheet format
  Update Progress Tracker**: Updates workflow status and progress tracking
  Process Complete Wait**: Ensures all operations finish before final steps
  Send Success Notification**: Alerts users when scraping is successfully completed

  Requirements

  Apify Account
  Active Apify account with sufficient credits
  API token for authentication
  Access to LinkedIn Profile Scraper actor

  Google Sheets
  Google account with Sheets access
  Properly formatted input sheet with LinkedIn URLs
  Credentials configured in n8n

  n8n Setup
  HTTP Request node credentials for Apify
  Google Sheets node credentials
  Webhook endpoint configured

  How to Use

  Step 1: Prepare Your Data
  Create a Google Sheet with LinkedIn profile URLs
  Ensure the sheet has a column named 'linkedin_url'
  Add any additional columns for metadata (name, company, etc.)

  Step 2: Configure Credentials
  Set up Apify API credentials in n8n
  Configure Google Sheets authentication
  Update webhook endpoint URL

  Step 3: Customize Settings
  Adjust scraping parameters in the Apify node
  Modify data fields to extract based on your needs
  Set up notification preferences

  Step 4: Execute Workflow
  Trigger via webhook or manual execution
  Monitor progress through the workflow
  Check Google Sheets for scraped data
  Review completion notifications

  Good to Know

  Rate Limits**: LinkedIn scraping is subject to rate limits. The workflow includes delays to respect these limits.
  Data Quality**: Results depend on profile visibility and LinkedIn's anti-scraping measures.
  Costs**: Apify charges based on compute units used. Monitor your usage to control costs.
  Compliance**: Ensure your scraping activities comply with LinkedIn's Terms of Service and applicable laws.

  Customizing This Workflow

  Enhanced Data Processing
  Add data enrichment steps to append additional information
  Implement duplicate detection and merge logic
  Create data validation rules for quality control

  Advanced Notifications
  Set up Slack or email alerts for different scenarios
  Create detailed reports with scraping statistics
  Implement error recovery mechanisms

  Integration Options
  Connect to CRM systems for automatic lead creation
  Integrate with marketing automation platforms
  Export data to analytics tools for further analysis

  Troubleshooting

  Common Issues
  Apify Actor Failures**: Check API limits and actor status
  Google Sheets Errors**: Verify permissions and sheet structure
  Rate Limiting**: Implement longer delays between requests
  Data Quality Issues**: Review scraping parameters and target profiles

  Best Practices
  Test with small batches before scaling up
  Monitor Apify credit usage regularly
  Keep backup copies of your data
  Regular validation of scraped information accuracy

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name: Generate & Publish Professional COE Blogs with Gemini AI and Google Drive
author_name: Oneclick AI Squad
author_username: oneclick-ai
categories: []
created_at: 2025-07-03T04:20:23.967Z
updated_at: 2025-07-03T04:20:23.967Z
url: https://n8n.io/workflows/5619
scraped_at: 2025-09-14 11:38:21
description:
  This n8n workflow transforms simple chat requests into professional Center of Excellence (COE) blog posts using AI, then automatically publishes them to Google Drive.

  What Is This?

  An intelligent blog creation system that takes a topic from chat and produces executive-level blog posts. Uses three AI stages to ensure high-quality, professional content suitable for business consumption.

  Why Use This?

  Professional Content**: Creates sophisticated blogs with business insights
  Save Time**: Topic to published blog in 2-3 minutes
  No Writing Skills Needed**: AI handles all the writing and formatting
  Auto-Publishing**: Creates and shares Google Docs automatically
  Easy to Use**: Just chat your topic, get your blog

  How It Works

  1. Blog Request & Planning
  Start Blog Request**: Chat interface receives your blog topic
  Create Blog Outline**: AI generates structured outline with sections
  AI Brain for Outline**: Powers the initial content planning

  2. Content Review & Writing
  Review & Fix Outline**: AI improves outline structure and flow
  Write Full Blog Post**: Transforms outline into complete professional blog
  AI Brain for Review/Writing**: Advanced AI models handle content creation

  3. Publish & Share Blog
  Clean Up Text Format**: Removes formatting issues for clean presentation
  Save Blog to Google Drive**: Creates properly formatted Google Doc
  Email Blog to Stakeholder**: Shares with specified team members
  Make Blog Public**: Creates shareable public link
  Send Blog Link to User**: Returns document URL via chat

  How to Use

  Start Chat: Access the chat interface and type your blog topic
  Wait: AI automatically processes (2-3 minutes)
  Get Your Blog: Receive Google Drive link to your published blog

  Good to Know

  Processing Time**: 2-3 minutes per blog
  Content Quality**: Uses advanced Gemini AI models for professional output
  Auto-Formatting**: Creates clean Google Docs ready for sharing
  Instant Sharing**: Stakeholders get email notifications automatically
  Public Access**: Generates shareable links for broader distribution

  Customizing This Workflow

  Content Style
  Modify AI prompts to match your company's writing tone
  Adjust content evaluation criteria for different audiences
  Change blog structure templates

  Publishing & Sharing
  Update stakeholder email addresses
  Change Google Drive folder destinations
  Modify sharing permissions (public/private)
  Add more distribution channels

  AI Enhancement
  Switch between different AI models for speed vs quality
  Add more review stages for specialized content
  Include company-specific knowledge sources

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.code","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5252 characters]


name: Generate SWOT Analysis Reports with OpenAI, Google Sheets & APITemplate PDF Export
author_name: Sebastian/OptiLever
author_username: lewxiangang
categories: []
created_at: 2025-07-03T06:15:48.765Z
updated_at: 2025-07-03T06:15:48.765Z
url: https://n8n.io/workflows/5622
scraped_at: 2025-09-14 11:38:20
description:
  SWOT Analysis Generator That Produces PDF Reports In n8n

  Want to skip the manual work and instantly generate SWOT analyses for your business plans, investor decks, or strategy docs? 🚀 This workflow lets you automate the entire SWOT (Strengths, Weaknesses, Opportunities, Threats) process—using AI and no-code tools! Whether you're using this for yourself or creating documents for clients, this workflow will save you hours of time and help identify the key components of growing any business.

  Tools We’ll Be Using:
  OpenAI API**: Powers AI-driven extraction and generation of SWOT sections, introductions, conclusions, and more.
  n8n**: The no-code automation platform that orchestrates this workflow.
  Google Sheets**: Stores your company data and report outputs (download the provided "SWOT Analysis" template and fill it out).
  APITemplate.io**: Converts HTML reports into downloadable, multi-page PDFs.
  DeepSeek API* *(optional): An alternative to OpenAI for specific reasoning tasks.
  Gmail OAuth2**: Sends the final report via email.

  If you’re building a business, doing client work, or just want faster strategic planning—this will save you HOURS.

  How It Works

  This n8n workflow transforms structured company data from a Google Sheet into a fully formatted, investor-grade SWOT report in both HTML and PDF formats. Here’s the process in a few high-level steps:

  Load Data: Pulls company information from the "Company Info Input" tab in the "SWOT Analysis" Google Sheet.
  AI Analysis: Uses AI (via OpenAI or DeepSeek) to categorize data into Strengths, Weaknesses, Opportunities, and Threats, and generates detailed narrative sections for each.
  Create Report Sections: Produces a strategic introduction, conclusion, table of contents, and title page using AI.
  Format and Combine: Converts all sections into styled HTML and merges them into a single document.
  Generate PDF: Converts the HTML into a polished, multi-page PDF using APITemplate.io.
  Save and Share: Saves the report back to Google Sheets and emails the PDF to a specified recipient.

  The result is a professional, investor-ready SWOT report with minimal manual effort, ready for sharing or review.

  Setup Steps

  Setting up this workflow typically takes 15-30 minutes, depending on your familiarity with the tools. Here’s what you’ll need to do:

  Configure Credentials**: Set up API keys and OAuth2 credentials for Google Sheets, OpenAI, APITemplate.io, Gmail, and optionally DeepSeek.
  Prepare Your Google Sheet**: Download the provided "SWOT Analysis" template, fill out the "Company Info Input" tab with your company data, and ensure it’s accessible.
  Import the Workflow**: Copy the workflow JSON into your n8n instance and connect your credentials.

  Detailed instructions for each step, including credential setup and customization options, are available in the sticky notes within the workflow. Refer to these for step-by-step guidance.

  Benefits

  Efficiency**: Automates the entire SWOT report generation process, saving hours of manual work.
  Professional Output**: Delivers fully styled HTML and PDF reports with headings, paragraphs, and custom layouts.
  AI-Driven Insights**: Ensures clarity and relevance in every section through targeted AI analysis.
  Seamless Sharing**: Automatically saves reports to Google Sheets and emails them to stakeholders.

  This workflow is perfect for entrepreneurs, consultants, or strategists looking to streamline their SWOT analysis process and deliver high-quality, professional reports effortlessly.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatDeepSeek","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.limit","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: EPA Clean Water Act Data Access & Compliance Monitoring API Integration
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T06:16:29.462Z
updated_at: 2025-07-03T06:16:29.462Z
url: https://n8n.io/workflows/5623
scraped_at: 2025-09-14 11:38:23
description:
  ⚠️ ADVANCED USE ONLY - U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Water Act (CWA) Rest Services 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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Water Act (CWA) Rest Services 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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Water Act (CWA) Rest Services credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Water Act (CWA) Rest Services API into an MCP-compatible interface for AI agents.

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

  📋 Available Operations (36 total)

  🔧 Cwa_Rest_Services.Get_Download (2 endpoints)

  • GET /cwa_rest_services.get_download: Submit CWA Download Data
  • POST /cwa_rest_services.get_download: Clean Water Act (CWA) Download Data Service

  🔧 Cwa_Rest_Services.Get_Facilities (2 endpoints)

  • GET /cwa_rest_services.get_facilities: Submit CWA Facility Search
  • POST /cwa_rest_services.get_facilities: Clean Water Act (CWA) Facility Search Service

  🔧 Cwa_Rest_Services.Get_Facility_Info (2 endpoints)

  • GET /cwa_rest_services.get_facility_info: Submit CWA Facility Details
  • POST /cwa_rest_services.get_facility_info: Clean Water Act (CWA) Facility Enhanced Search Service

  🔧 Cwa_Rest_Services.Get_Geojson (2 endpoints)

  • GET /cwa_rest_services.get_geojson: Submit CWA GeoJSON Data
  • POST /cwa_rest_services.get_geojson: Clean Water Act (CWA) GeoJSON Service

  🔧 Cwa_Rest_Services.Get_Info_Clusters (2 endpoints)

  • GET /cwa_rest_services.get_info_clusters: Submit CWA Info Clusters
  • POST /cwa_rest_services.get_info_clusters: Clean Water Act (CWA) Info Clusters Service

  🔧 Cwa_Rest_Services.Get_Map (2 endpoints)

  • GET /cwa_rest_services.get_map: Submit CWA Map Data
  • POST /cwa_rest_services.get_map: Clean Water Act (CWA) Map Service

  🔧 Cwa_Rest_Services.Get_Qid (2 endpoints)

  • GET /cwa_rest_services.get_qid: Submit CWA Paginated Results
  • POST /cwa_rest_services.get_qid: Clean Water Act (CWA) Paginated Results Service

  🔧 Cwa_Rest_Services.Metadata (2 endpoints)

  • GET /cwa_rest_services.metadata: Submit CWA Metadata
  • POST /cwa_rest_services.metadata: Clean Water Act (CWA) Metadata Service

  🔧 Rest_Lookups.Bp_Tribes (2 endpoints)

  • GET /rest_lookups.bp_tribes: Submit BP Tribes Data
  • POST /rest_lookups.bp_tribes: ECHO BP Tribes Lookup Service

  🔧 Rest_Lookups.Cwa_Parameters (2 endpoints)

  • GET /rest_lookups.cwa_parameters: Submit CWA Parameters
  • POST /rest_lookups.cwa_parameters: ECHO CWA Parameter Lookup Service

  🔧 Rest_Lookups.Cwa_Pollutants (2 endpoints)

  • GET /rest_lookups.cwa_pollutants: Submit CWA Pollutants
  • POST /rest_lookups.cwa_pollutants: ECHO CWA Pollutants Lookup Service

  🔧 Rest_Lookups.Federal_Agencies (2 endpoints)

  • GET /rest_lookups.federal_agencies: Submit Federal Agencies
  • POST /rest_lookups.federal_agencies: ECHO Federal Agency Lookup Service

  🔧 Rest_Lookups.Icis_Inspection_Types (2 endpoints)

  • GET /rest_lookups.icis_inspection_types: Submit ICIS Inspection Types
  • POST /rest_lookups.icis_inspection_types: ECHO ICIS NPDES Inspection Types Lookup Service

  🔧 Rest_Lookups.Icis_Law_Sections (2 endpoints)

  • GET /rest_lookups.icis_law_sections: Submit ICIS Law Sections
  • POST /rest_lookups.icis_law_sections: ECHO ICIS NPDES Law Sections Lookup Service

  🔧 Rest_Lookups.Naics_Codes (2 endpoints)

  • GET /rest_lookups.naics_codes: Submit NAICS Codes
  • POST /rest_lookups.naics_codes: ECHO NAICS Codes Lookup Service

  🔧 Rest_Lookups.Npdes_Parameters (2 endpoints)

  • GET /rest_lookups.npdes_parameters: Submit NPDES Parameters
  • POST /rest_lookups.npdes_parameters: ECHO NPDES Parameters Lookup Service

  🔧 Rest_Lookups.Wbd_Code_Lu (2 endpoints)

  • GET /rest_lookups.wbd_code_lu: Submit WBD Codes
  • POST /rest_lookups.wbd_code_lu: ECHO WBD Code Lookup Service

  🔧 Rest_Lookups.Wbd_Name_Lu (2 endpoints)

  • GET /rest_lookups.wbd_name_lu: Submit WBD Names
  • POST /rest_lookups.wbd_name_lu: ECHO WBD Name Lookup Service

  🤖 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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Water Act (CWA) Rest Services API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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name: Connect AI Agents to EPA Clean Air Act Data with MCP Integration
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T06:16:58.599Z
updated_at: 2025-07-03T06:16:58.599Z
url: https://n8n.io/workflows/5624
scraped_at: 2025-09-14 11:38:23
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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Air Act API operations to AI agents.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Air Act 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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Air Act 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://echodata.epa.gov/echo
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (16 total)

  🔧 Air_Rest_Services.Get_Download (2 endpoints)

  • GET /air_rest_services.get_download: Request Air Quality Data
  • POST /air_rest_services.get_download: Clean Air Act Download Data Service

  🔧 Air_Rest_Services.Get_Facilities (2 endpoints)

  • GET /air_rest_services.get_facilities: Query Air Quality Facilities
  • POST /air_rest_services.get_facilities: Clean Air Act Facility Search

  🔧 Air_Rest_Services.Get_Facility_Info (2 endpoints)

  • GET /air_rest_services.get_facility_info: Request Facility Details
  • POST /air_rest_services.get_facility_info: Clean Air Act Facility Enhanced Search

  🔧 Air_Rest_Services.Get_Geojson (2 endpoints)

  • GET /air_rest_services.get_geojson: Request Air Quality GeoJSON
  • POST /air_rest_services.get_geojson: Clean Air Act GeoJSON Service

  🔧 Air_Rest_Services.Get_Info_Clusters (2 endpoints)

  • GET /air_rest_services.get_info_clusters: Request Info Clusters Data
  • POST /air_rest_services.get_info_clusters: Clean Air Act Info Clusters Service

  🔧 Air_Rest_Services.Get_Map (2 endpoints)

  • GET /air_rest_services.get_map: Request Air Quality Map
  • POST /air_rest_services.get_map: Clean Air Act Map Service

  🔧 Air_Rest_Services.Get_Qid (2 endpoints)

  • GET /air_rest_services.get_qid: Query by Query ID
  • POST /air_rest_services.get_qid: Clean Air Act Search by Query ID

  🔧 Air_Rest_Services.Metadata (2 endpoints)

  • GET /air_rest_services.metadata: Request Air Quality Metadata
  • POST /air_rest_services.metadata: Clean Air Act Metadata Service

  🤖 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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Air Act API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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name: Free AI Image Generator - n8n Automation Workflow with Gemini/ChatGPT
author_name: Agent Circle
author_username: agentcircle
categories: []
created_at: 2025-07-03T06:57:15.342Z
updated_at: 2025-07-03T06:57:15.342Z
url: https://n8n.io/workflows/5626
scraped_at: 2025-09-14 11:38:20
description:
  This n8n template demonstrates how to use AI to generate custom images from scratch - fully automated, prompt-driven, and ready to deploy at scale.

  Use cases are many: You can use it for marketing visuals, character art, digital posters, storyboards, or even daily image generation for your personal purposes.

  How It Works
  The flow is triggered by a chat message in N8N or via Telegram. The default image size is 1080 x 1920 pixels. To use a different size, update the values in the “Fields - Set Values” node before triggering the workflow.
  The input is parsed into a clean, structured prompt using a multi-step transformation process.
  Our AI Agent sends the final prompt to Google Gemini’s image model for generation (you can also integrate with OpenAI or other chat models).
  The raw image data created by the AI Agent will be run through a number of codes to make sure it's feasible for your preview if needed and downloading.
  Then, we use an HTTP node to fetch the result so you can preview the image.
  You can send it back to the chat message in N8N or Telegram, or save it locally to your disk.

  How To Use
  Download the workflow package.
  Import the package into your N8N interface.
  Set up the credentials in the following nodes for tool access and usability: "Telegram Trigger"; "AI Agent - Create Image From Prompt"; "Telegram Response" or "Save Image To Disk" (based on your wish).
  Activate the "Telegram Response" OR "Save Image To Disk" node to specify where you want to save your image later.
  Open the chat interface (via N8N or Telegram).
  Type your image prompt or detailed descriptions and send.
  Wait for the process to run and finish in a few seconds.
  Check the result in your desired saving location.

  Requirements
  Google Gemini account with image generation access.
  Telegram bot access and chat setup (optional).
  Connection to local storage (optional).

  How To Customize
  We’re setting the default image size to 1080 x 1920 pixels and the default image model to "flux". You can customize both of these values in the “Fields – Set Values” node. Supported image model options include: "flux", "kontext", "turbo", and "gptimage".
  In the “AI Agent – Create Image From Prompt” node, you can also change the AI chat model. By default, it uses Google Gemini, but you can easily replace it with OpenAI ChatGPT, Microsoft AI Copilot, or any other compatible provider.

  Need Help?
  Join our community on different platforms for support, inspiration and tips from others.

  Website: https://www.agentcircle.ai/
  Etsy: https://www.etsy.com/shop/AgentCircle
  Gumroad: http://agentcircle.gumroad.com/
  Discord Global: https://discord.gg/d8SkCzKwnP
  FB Page Global: https://www.facebook.com/agentcircle/
  FB Group Global: https://www.facebook.com/groups/aiagentcircle/
  X: https://x.com/agent_circle
  YouTube: https://www.youtube.com/@agentcircle
  LinkedIn: https://www.linkedin.com/company/agentcircle

nodes_used:
  ["n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.telegramTrigger","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.telegram","n8n-nodes-base.readWriteFile"]

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name: Multi-Channel Workflow Error Alerts with Telegram, Gmail & Messaging Apps
author_name: Khairul Muhtadin
author_username: khmuhtadin
categories: []
created_at: 2025-07-03T10:30:15.915Z
updated_at: 2025-07-03T10:30:15.915Z
url: https://n8n.io/workflows/5629
scraped_at: 2025-09-14 11:38:21
description:
  The Error Notification workflow is designed to instantly notify you whenever any other n8n workflow encounters an error, using popular communication channels like Telegram and Gmail—with optional support for Discord, Slack, and WhatsApp. 

  💡 Why Use Error Notification workflow?

  Immediate Awareness:** Get instant alerts when workflows fail, preventing unnoticed errors and downtime.
  Multi-Channel Flexibility:** Notify your team via Telegram, Gmail, and optionally Slack, Discord, or WhatsApp.
  Detailed Context:** Receive rich error information including the error message, node name, time, and execution link for quicker fixes.
  Easy Integration:** Built with native n8n nodes and customizable code, simple to adopt without complex setup.
  Open Source & Free:** Use and adapt this workflow at no cost, making professional error monitoring accessible.

  ⚡ Who Is This For?

  n8n Workflow Developers:** Quickly spot and respond to automation issues in development or production.
  Operations Teams:** Maintain uptime and swiftly troubleshoot errors across multiple workflows.
  Small to Medium Businesses:** Gain professional error alerting without expensive monitoring tools.
  Automation Enthusiasts:** Enhance your automation reliability with real-time failure notifications.

  ❓ What Problem Does It Solve?

  This workflow embedd error detection and notification directly within your n8n instance. It automates the process of catching errors as they occur, compiling meaningful context, and delivering it instantly via your preferred messaging platforms. This drastically reduces your response time to issues and streamlines error management, improving your automation reliability and operational confidence.

  🔧 What This Workflow Does

  ⏱ Trigger: Listens for any error generated in your n8n workflows using the n8n Error Trigger node.

  📎 Step 2: Executes a Code node that formats a detailed error message capturing workflow name, error node, description, timestamp, and an execution URL.

  🔍 Step 3: Sends the formatted error notification to multiple communication channels: Telegram and Gmail by default, plus optionally Discord, Slack, and WhatsApp (disabled by default).

  💌 Step 4: Delivers rich, parsed HTML-formatted messages to ensure error readability and immediate actionability.

  🔐 Setup Instructions

  Import the provided .json file into your n8n instance (Cloud or self-hosted).

  Set up credentials:
     Gmail OAuth credentials for sending emails via Gmail node
     Telegram API credentials for Telegram notifications
     (Optional) Discord Webhook URL credential for Discord notifications
     (Optional) Slack Webhook credential for Slack notifications
     (Optional) WhatsApp connection credentials (if enabled)

  Customize the Code node if needed to adjust the error message format or target chat IDs.

  Update the chat IDs and recipient details in each notification node according to your channels.

  Test the workflow by manually triggering an error in another workflow to verify proper notifications.

  🧩 Pre-Requirements

  Active n8n instance (cloud or self-hosted) with version supporting Error Trigger node
  Telegram bot credentials and chat ID
  (Optional) Gmail, Discord, Slack, or WhatsApp accounts and webhook credentials if you want to use those channels

  🛠️ Customize It Further

  Enable and configure additional notification nodes like Slack or WhatsApp to fit your team's communication style.
  Customize the error message template in the Code node to include extra metadata or format it differently (e.g., markdown).
  Integrate with incident management tools via webhook nodes or create tickets automatically on error.

  🧠 Nodes Used

  Error Trigger
  Code
  Telegram
  Gmail
  Discord (disabled)
  Slack (disabled)
  WhatsApp (disabled)
  Sticky Note (for description)

  📞 Support

  Made by: khaisa Studio  
  Tag: notification,error,monitoring,workflow,automation,alerts  
  Category: Monitoring & Alerts  
  Need a custom? Need a custom? contact me on LinkedIn or Web

nodes_used:
  ["n8n-nodes-base.errorTrigger","n8n-nodes-base.code","n8n-nodes-base.gmail","n8n-nodes-base.whatsApp","n8n-nodes-base.slack","n8n-nodes-base.telegram","n8n-nodes-base.discord","n8n-nodes-base.stickyNote"]

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name: Transform YouTube Videos into Interactive MCQ Quizzes with Google Forms & Gemini AI
author_name: Md. Nazmul Islam
author_username: pomegai
categories: []
created_at: 2025-07-03T11:09:11.552Z
updated_at: 2025-07-03T11:09:11.552Z
url: https://n8n.io/workflows/5631
scraped_at: 2025-09-14 11:38:21
description:
  AI-Powered MCQ Quiz Generator from YouTube Videos

  Transform any YouTube video into an interactive MCQ quiz automatically! This workflow uses Google Gemini AI to analyze video content and generate comprehensive multiple-choice questions with automatic grading - perfect for educators, trainers, and content creators.

  Who is this For
  This workflow is perfect for:
  Educators** creating quizzes from educational YouTube content
  Corporate Trainers** developing assessments from training videos
  Content Creators** engaging their audience with interactive quizzes
  Students** testing their knowledge on video lectures
  Online Course Creators** building assessments from video content

  Features
  AI Video Analysis**: Google Gemini 2.5 Flash analyzes entire YouTube videos (up to 50 minutes)
  Dynamic Question Generation**: Creates up to 90 MCQ questions with 3 options each
  Automatic Form Creation**: Generates Google Forms with quiz functionality
  Smart Grading**: Built-in correct answer identification and scoring
  Error Handling**: Robust error management with user feedback

  How It Works
  User Input via n8n Web Form:
     Form Name (Quiz Title)
     Email Address
     YouTube Video URL
     Number of Questions (1-90)

  AI Processing Pipeline:
     Google Gemini analyzes the YouTube video content
     AI extracts key concepts and generates relevant questions
     Structured output parser formats questions into JSON

  Google Forms Integration:
     Automatically creates a new Google Form
     Adds all generated questions with multiple choice options
     Configures quiz settings with correct answers and scoring

  Completion & Access:
     User receives direct link to the generated quiz
     Form ready for immediate use or sharing

  Video Demo:
  	See this youtube Video to explore "how it works".

  Set Up Steps
  Import the Workflow
     Create a new workflow in n8n
     Import the JSON file by clicking "three dots" (upper right corner) &gt; "Import from file..."

  Configure Google Gemini API
     Get your Google AI Studio API key from Google AI Studio
     On “HTTP Request to Gemini” node replace the “API_KEY” from url with your API key.
     Create a "Google Gemini (PaLM) API" credential in n8n
     Add your API key to the credential
     Connect the credential to the "Google Gemini Chat Model" node

  Set Up Google Forms Integration
     Enable Google Forms API in Google Cloud Console
     Create a "Google OAuth2 API" credential in n8n
     Authorize the credential with Forms permissions
     Connect the credential to both HTTP Request nodes (“Create a Google Form” node and “Create MCQ Quizzes” node)

  Configure Form Trigger
     The workflow includes a built-in form trigger
     No additional setup needed - the form URL will be generated automatically
     Customize form fields if needed in the “Input YouTube URL" node

  Test the Workflow
     Activate the workflow
     Submit the form to generate a test quiz
     Verify the Google Form is created successfully

  Pre-requisites
  Necessary Accounts:**
    Google Account (for Forms API access)
    Google AI Studio Account (for Gemini API access)
    n8n Instance (cloud or self-hosted)

  API Access:**
    Google Forms API enabled
    Google drive API enabled 
    Google Generative AI API access
    Valid API keys and OAuth credentials

  N8N Requirements:**
    n8n version 1.95.2 or higher
    LangChain nodes package installed
    Internet access for API calls

  Customization Guidance
  Question Generation Prompts:
     Modify the prompt in "Set Prompt and model" node for different question styles
     Adjust difficulty levels or focus areas
     Change question format (True/False, Fill-in-blanks, etc.)

  Form Customization:
     Update form title and description templates
     Add additional input fields (difficulty level, subject area)
     Customize success/error messages

  Advanced Features You Can Add:
     Email Notifications: Send quiz links via email
     Analytics Integration: Track quiz performance and completion rates
     Multi-language Support: Generate quizzes in different languages
     Question Bank Storage: Save generated questions to a database
     Batch Processing: Generate multiple quizzes from a YouTube playlist

  Error Handling Enhancements:
     Add retry logic for API failures
     Implement fallback question generation
     Create detailed error logging

  Technical Specifications
  Video Length**: Up to 50 minutes supported
  Question Limit**: 1-90 questions per quiz
  Processing Time**: 2-10 minutes depending on video length
  Supported Formats**: YouTube videos (public and unlisted)
  Output Format**: Google Forms with automatic grading

  Limitations & Considerations
  YouTube video must be publicly accessible or unlisted
  Processing time increases with video length and question count
  API rate limits may apply for high-volume usage
  Some complex visual content may not be fully analyzed

  Ready to Transform Videos into Quizzes?
  This workflow streamlines the entire process from video analysis to quiz deployment. Perfect for educators and trainers looking to create engaging assessments from video content quickly and efficiently.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitInBatches","n8n-nodes-base.if","n8n-nodes-base.formTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.form","n8n-nodes-base.form","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Crypto Alpha Scanner with OpenAI - On-Chain and Social Alerts to Telegram
author_name: Luka Zivkovic
author_username: zivkovic58
categories: []
created_at: 2025-07-03T13:13:56.485Z
updated_at: 2025-07-03T13:13:56.485Z
url: https://n8n.io/workflows/5632
scraped_at: 2025-09-14 11:38:22
description:
  🎯 What This Does
  This n8n workflow is a comprehensive crypto intelligence system that monitors multiple data sources simultaneously to identify alpha opportunities, whale movements, and emerging trends before they become mainstream. 

  It's like having a team of crypto analysts working 24/7 to spot the next big move.*

  Installment payment plan available on the link
  ⚡ Key Features

  🐋 Whale Tracking: Monitor VIP wallets and smart money movements in real-time

  📊 Multi-DEX Monitoring: Track price movements, volume, and buy pressure across DEXs

  🆕 New Token Discovery: Catch tokens within 24 hours of launch

  📱 Social Intelligence: Analyze Reddit sentiment and Twitter activity (optional)

  🤖 AI-Powered Analysis: OpenAI summarizes and prioritizes signals by risk/opportunity

  📨 Smart Telegram Alerts: Beautifully formatted alerts with actionable insights

  🔄 Cross-Source Validation: Higher confidence through multiple data point correlation

  🚀 What Makes This Special

  Unlike basic price alerts, this system provides context and intelligence:
  Early Alpha Detection: Spots whale accumulation before social discovery
  Risk Assessment: AI categorizes signals by risk level (LOW/MEDIUM/HIGH/EXTREME)
  Pattern Recognition: Detects exploits, new listings, partnerships, airdrops
  Trend Scoring: Composite scores based on whale activity + social sentiment + DEX data
  Smart Filtering: Only sends high-priority alerts to reduce noise

  📈 Real-World Use Cases
  For Traders

  Get notified when whales start accumulating before price pumps
  Spot new tokens with high whale interest and low social awareness
  Receive exploit warnings to protect your investments
  Track trending tokens with momentum building

  For Researchers

  Monitor smart money wallets and their strategies
  Analyze correlation between whale movements and social sentiment
  Track DeFi protocol updates and governance changes
  Study market psychology through cross-source data

  For Portfolio Managers

  Early warning system for portfolio holdings
  Discovery of emerging opportunities before mainstream adoption
  Risk management through exploit and dump warnings
  Market intelligence for strategic decision making

  🛠️ Setup Requirements
  Required (Free Tier Available)

  Etherscan API (Free) - For whale transaction monitoring
  Telegram Bot (Free) - For receiving alerts
  OpenAI API (~$0.50-2/day) - For intelligent analysis
  n8n Instance (Free self-hosted or cloud)

  Optional Upgrades

  Reddit OAuth (Free) - Improves social monitoring reliability
  Twitter/Apify ($0.4 / 1K tweets) - Professional Twitter monitoring

  🎛️ Configuration Options
  Hot Tokens Monitoring
  hotTokens: ['PEPE', 'WIF', 'BONK', 'JTO', 'PYTH', 'ARB', 'OP']
  VIP Wallets (Smart Money)
  vipWallets: [
    '0xae2Fc483527B8EF99EB5D9B44875F005ba1FaE13', // jaredfromsubway.eth
    '0x47ac0Fb4F2D84898e4D9E7b4DaB3C24507a6D503', // Binance 2
    // Add your own discovered alpha wallets
  ]
  Sensitivity Thresholds
  thresholds: {
    whaleMove: 500000,        // Minimum USD for whale alerts
    dexVolume: 100000,        // Minimum volume to report
    priceChange1h: 10,        // Percentage change threshold
    twitterEngagement: 100    // Minimum engagement for Twitter
  }
  📱 Sample Alert Output
  🚨 CRYPTO ALPHA SCANNER
  ⏰ 14:30:25 UTC

  💎 ALPHA OPPORTUNITIES 💎
  ──────────────────────────────

  🎯 $PEPE - Whale accumulation before social discovery
  ├─ 🐋 Whales: 5 buys / 1 sells (Accumulating)
  ├─ 💬 Social: 12 mentions (Bullish)
  ├─ 📊 Volume: $2,500k | Buy pressure: 73%
  └─ 🔥 Patterns: whale_buying_new, pump_detected

  📈 TRENDING TOKENS
  ──────────────────────────────

  🔥 $WIF (Score: 28)
  ├─ Whale: 🟢 Accumulating
  ├─ Social: 45 mentions (T:23 R:22)
  ├─ DEX: 68% buy pressure | $1,200k vol
  └─ Change: +15.3% (24h)

  📊 INTELLIGENCE SUMMARY
  ├─ Signals Analyzed: 23
  ├─ Tokens Tracked: 15
  ├─ Alpha Opportunities: 3
  └─ High Priority: 8
  🔧 Quick Start Guide
  1️⃣ Basic Setup (10 minutes)

  -- Get Etherscan API key (etherscan.io/apis)
  -- Create Telegram bot (@BotFather)
  -- Get OpenAI API key (platform.openai.com)
  -- Import workflow into n8n
  -- Configure credentials in each node

  2️⃣ Customize Configuration

  -- Edit "Load Configuration" node
  -- Add your target tokens to hotTokens
  -- Add whale wallets to vipWallets
  -- Adjust thresholds for sensitivity

  3️⃣ Test & Deploy

  -- Execute workflow manually to test
  -- Check Telegram for formatted alerts
  -- Enable schedule trigger (runs every 30 minutes)

  🎯 Who This Is For
  ✅ Perfect For:

  Active Crypto Traders seeking early signals
  DeFi Researchers tracking protocol developments
  Whale Watchers following smart money
  Alpha Hunters looking for pre-pump opportunities
  Risk Managers needing exploit warnings

  ❌ Not Ideal For:

  Complete crypto beginners
  Set-and-forget investors
  Those wanting guaranteed profits

  🛡️ Risk Disclaimer
  This tool provides information and analysis only. It does not guarantee profits and all crypto investments carry significant risk. The system is designed to help you make informed decisions, but you should:

  Always do your own research (DYOR)**
  Never invest more than you can afford to lose**
  Understand that past performance doesn't predict future results**
  Be aware that whale movements can be deceptive**

  🆘 Support & Community
  Support is available on the Discord channel

  ✅ Complete setup documentation
  ✅ Troubleshooting guide
  ✅ Configuration examples

  📚Community Resources

  💬 Discord community access
  🔄 Regular workflow updates
  💡 Strategy sharing with other users

  ⚡ Get Started Today
  Transform your crypto trading with professional-grade intelligence. This system has been refined through months of testing and real-world usage.
  Ready to spot the next alpha opportunity before everyone else?

  N8N Link to get you started

nodes_used:
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name: Transform Images into AI Videos with MiniMax Hailuo 02 & Upload to YouTube/TikTok
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-07-03T13:43:09.677Z
updated_at: 2025-07-03T13:43:09.677Z
url: https://n8n.io/workflows/5633
scraped_at: 2025-09-14 11:38:20
description:
  This automated workflow takes a static image and a textual prompt and transforms them into an animated video using the MiniMax Hailuo 02 model. It then uploads the generated video to YouTube and TikTok, and updates a Google Sheet with relevant links and metadata.

  Benefits of This Workflow

  Fully Automated Pipeline**: From prompt to video to social media publication — all without manual intervention.
  Scalable Content Creation**: Generate and distribute dozens of videos per hour with minimal human input.
  Cross-Platform Posting: Automatically pushes content to **YouTube and TikTok simultaneously.
  SEO Optimization**: Uses AI to generate catchy, keyword-rich video titles that improve visibility.
  Easy Integration**: Based on Google Sheets for input/output, making it accessible to non-technical users.
  Time-Efficient**: Batch-processing enabled with scheduled runs every few minutes.
  Customizable Duration**: Video duration can be adjusted (default is 6 seconds).

  How It Works  
  Trigger & Data Fetching:  
     The workflow starts either manually or via a scheduled trigger (e.g., every 5 minutes).  
     It checks a Google Sheet for new entries where the "VIDEO" column is empty, indicating pending video generation tasks.  

  Video Creation:  
     For each entry, the workflow extracts the image URL and prompt from the Google Sheet.  
     It sends these inputs to the MiniMax Hailuo 02 to generate a video. The API processes the image and prompt, optimizes the prompt, and creates a short video (default: 6 seconds).  

  Status Monitoring:  
     The workflow polls the API every 60 seconds to check if the video is COMPLETED.  
     Once ready, it retrieves the video URL and uploads the file to Google Drive.  

  YouTube & TikTok Upload:  
     The video is sent to YouTube and TikTok via the Upload-Post.com API (The free plan allows uploads to all platforms except TikTok. To enable, upgrade to a paid plan.).  
     A GPT-generated SEO-optimized title is created for the video.  
     The Google Sheet is updated with the video URL and YouTube link.  

  Set Up Steps  
  Google Sheet Setup:  
     Create a Google Sheet with columns: IMAGE (input image URL), PROMPT (video description), VIDEO (auto-filled), and YOUTUBE_URL (auto-filled).  
     Link the sheet to the workflow using the Google Sheets node.  

  API Keys:  
     Obtain a fal.run API key (for MiniMax Hailuo) and configure the "Authorization" header in the "Create video" node.  
     Get an Upload-Post.com API key (10 free uploads/month) and set it in the "Upload on YouTube/TikTok" nodes.  

  Workflow Configuration:  
     Replace YOUR_USERNAME in the Upload-Post nodes with your profile name (e.g., "test1").  
     Adjust the video duration (6 or 10 seconds) in the "Create video" node.  
     Set the Schedule Trigger interval (e.g., 5 minutes) to automate checks for new tasks.  

  Execution:  
     Run the workflow manually or let the scheduler process new rows automatically.  
     The system handles video generation, uploads, and Google Sheet updates end-to-end.  

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

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest"]

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name: Track Top Meme Coin Prices with Telegram Bot and CoinGecko API
author_name: Muhammad Zeeshan Ahmad
author_username: connectedwithaiagents
categories: []
created_at: 2025-07-03T15:53:34.293Z
updated_at: 2025-07-03T15:53:34.293Z
url: https://n8n.io/workflows/5634
scraped_at: 2025-09-14 11:38:21
description:
  Platform: n8n (Telegram Bot Integration)
  Purpose: Let users fetch top meme coin prices in real-time using a simple /memecoin Telegram command 
   How It Works (Logic Breakdown)
  This flow listens for a Telegram command and fetches data from the CoinGecko API to respond with live memecoin prices.

  🔹 1. Telegram Trigger Node
  Listens for incoming Telegram messages from users.

  Activated when a message is sent in a Telegram chat connected to the bot.

  Passes the raw message (e.g., /memecoin) to the next node.

  🔹 2. IF Node – Check if Message is /memecoin
  Condition: {{$json"message"}} === "/memecoin"

  If true ➝ continue to fetch data from CoinGecko.

  If false ➝ nothing happens.

  🔹 3. HTTP Request – Fetch Meme Coins from CoinGecko
  API: https://api.coingecko.com/api/v3/coins/markets?...category=meme-token

  Fetches top 5 meme tokens by market cap.

  Data includes:

  Name

  Symbol

  Current price (USD)

  Coin ID (for URL linking)

  🔹 4. Function Node – Format the Message
  Parses the JSON response from CoinGecko.

  Builds a clean message like:

  ruby
  Copy
  Edit
  🚀 Dogecoin (DOGE)
  💰 Price: $0.123
  🔗 More: https://www.coingecko.com/en/coins/dogecoin
  Loops through top 5 meme coins and adds line breaks.

  🔹 5. Telegram Send Node – Reply to User
  Sends the formatted message to the original chat.

  Uses chat_id from the trigger to ensure correct user receives it.

  🖼 Sample User Flow
  👤 User types /memecoin in Telegram bot

  🤖 Bot fetches meme coin prices

  📬 Bot replies with live prices + links

nodes_used:
  ["n8n-nodes-base.telegramTrigger","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.telegram"]

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name: EPA Environmental Compliance Data API for AI Agents with MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:19:25.557Z
updated_at: 2025-07-03T16:19:25.557Z
url: https://n8n.io/workflows/5636
scraped_at: 2025-09-14 11:38:23
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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Resource Conservation and Recovery Act  API operations to AI agents.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add U.S. EPA Enforcement and Compliance History Online (ECHO) - Resource Conservation and Recovery Act  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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Resource Conservation and Recovery Act  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://echodata.epa.gov/echo
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (16 total)

  🔧 Rcra_Rest_Services.Get_Download (2 endpoints)

  • GET /rcra_rest_services.get_download: Request RCRA Data Download
  • POST /rcra_rest_services.get_download: Resource Conservation and Recovery Act (RCRA) Download Data Service

  🔧 Rcra_Rest_Services.Get_Facilities (2 endpoints)

  • GET /rcra_rest_services.get_facilities: Request RCRA Facility Search
  • POST /rcra_rest_services.get_facilities: Resource Conservation and Recovery Act (RCRA) Facility Search Service

  🔧 Rcra_Rest_Services.Get_Facility_Info (2 endpoints)

  • GET /rcra_rest_services.get_facility_info: Request RCRA Facility Details
  • POST /rcra_rest_services.get_facility_info: Resource Conservation and Recovery Act (RCRA) Facility Enhanced Search Service

  🔧 Rcra_Rest_Services.Get_Geojson (2 endpoints)

  • GET /rcra_rest_services.get_geojson: Request RCRA GeoJSON Data
  • POST /rcra_rest_services.get_geojson: Resource Conservation and Recovery Act (RCRA) GeoJSON Service

  🔧 Rcra_Rest_Services.Get_Info_Clusters (2 endpoints)

  • GET /rcra_rest_services.get_info_clusters: Request RCRA Info Clusters
  • POST /rcra_rest_services.get_info_clusters: Resource Conservation and Recovery Act (RCRA) Info Clusters Service

  🔧 Rcra_Rest_Services.Get_Map (2 endpoints)

  • GET /rcra_rest_services.get_map: Request RCRA Map Data
  • POST /rcra_rest_services.get_map: Resource Conservation and Recovery Act (RCRA) Map Service

  🔧 Rcra_Rest_Services.Get_Qid (2 endpoints)

  • GET /rcra_rest_services.get_qid: Request RCRA Paginated Results
  • POST /rcra_rest_services.get_qid: Resource Conservation and Recovery Act (RCRA) Paginated Results Service

  🔧 Rcra_Rest_Services.Metadata (2 endpoints)

  • GET /rcra_rest_services.metadata: Request RCRA Metadata
  • POST /rcra_rest_services.metadata: Resource Conservation and Recovery Act (RCRA) Metadata Service

  🤖 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 U.S. EPA Enforcement and Compliance History Online (ECHO) - Resource Conservation and Recovery Act  API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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