# templates

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 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
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

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

workflow_json_compressed:
  [encoded data, 4212 characters]

metadata_json:
  {"categories":["automation","integration","data processing","web scraping"],"complexity":"medium","use_cases":["Lead generation","Recruitment / candidate sourcing","Market research","Sales prospecting"],"estimated_setup_minutes":30,"required_services":["Apify (account, actor access, API token)","Google Sheets (Google account + Sheets access)","LinkedIn (target profiles to be scraped)"],"key_features":["Scrape LinkedIn profiles via Apify actor","Read LinkedIn URLs from Google Sheets","Save structured results back to Google Sheets","Webhook-triggered and scheduled runs","Batch processing with rate-limit aware delays and progress tracking/update nodes\",\"Configurable scraping parameters and data formatting\",\"Success/failure notifications and basic error handling"],"target_audience":["Growth marketers","Sales teams / SDRs","Recruiters / talent sourcers\",\"Data analysts / market researchers\",\"Automation / DevOps engineers"]}


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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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]

metadata_json:
  {"categories":["content creation","AI-powered automation","integration","document publishing"],"complexity":"medium","use_cases":["Generate executive-level COE blog posts from simple chat prompts","Automated publishing of blog posts to Google Drive/Docs","Email stakeholders and share public links automatically","Standardize and accelerate internal knowledge/COE communications","Quickly produce formatted content without writing skills"],"estimated_setup_minutes":20,"required_services":["Google Gemini AI (lmChat via Google Cloud)","Google Drive & Google Docs (Google Workspace)","Email service (Gmail or SMTP)","n8n (workflow automation host)"],"key_features":["Three-stage AI pipeline: outline, review/fix, full-write","Auto-cleaning and formatting of text","Creates Google Doc and saves to specified Drive folder","Automatically emails stakeholders and generates public share link","Returns document URL to user via chat interface (end-to-end)"],"target_audience":["Content marketers","Center of Excellence (COE) leads and internal comms","Product/marketing managers who need fast content generation`,`Marketing ops & demand-gen teams`,`Technical writers & knowledge managers"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
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:
  [encoded data, 27504 characters]

metadata_json:
  {"categories":["automation","integration","document generation","data processing","reporting"],"complexity":"medium","use_cases":["Automated SWOT report generation","Creating investor-grade strategy documents","Delivering client strategy/consulting reports","Periodic competitive or strategic analysis","Saving and emailing final PDFs from structured input data"],"estimated_setup_minutes":20,"required_services":["OpenAI API","n8n","Google Sheets (OAuth2)","APITemplate.io","Gmail (OAuth2)","DeepSeek API (optional)"],"key_features":["AI-driven extraction and generation of Strengths, Weaknesses, Opportunities, Threats","Generates introductions, conclusions, table of contents and title page via AI","Formats content as styled HTML and converts to multi-page PDF","Saves outputs and source data to Google Sheets","Sends final PDF via Gmail email automation (OAuth2 credentialed)"],"target_audience":["Entrepreneurs / business owners","Consultants and agencies","Strategists and business analysts"]}


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 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
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.

nodes_used:
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workflow_json_compressed:
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metadata_json:
  {"categories":["integration","data processing","compliance monitoring","geospatial"],"complexity":"complex","use_cases":["Access U.S. EPA ECHO Clean Water Act (CWA) APIs","Automated compliance and enforcement monitoring","Facility search and detailed facility reporting","Download and paginated data retrieval","GeoJSON/map data ingestion and visualization pipelines','Lookup/reference data retrieval (pollutants, NAICS, WBD, etc.)"],"estimated_setup_minutes":10,"required_services":["U.S. EPA ECHO Clean Water Act (CWA) Rest Services (https://echodata.epa.gov/)","n8n instance with MCP trigger support","Credentials for ECHO API","AI agent or platform consuming MCP endpoints (e.g., Claude, Cursor, custom)"],"key_features":["36 MCP-exposed operations covering downloads, facilities, maps, geojson, metadata and lookup endpoints","GET and POST endpoints for each operation","MCP trigger to serve AI agent requests","AI expression support ($fromAI()) to auto-populate parameters","Native HTTP request handling and error management in n8n responses returned to agents','Supports paginated results, geojson/map outputs, and various lookup services"],"target_audience":["advanced n8n users and developers","data engineers and analysts working with EPA CWA data","environmental compliance teams and researchers integrating EPA data into workflows','AI integrators building tools that call EPA data via MCP endpoints"]}


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 19:11:03
metadata_generated_at: 2025-09-14 21:18:34
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 16 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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metadata_json:
  {"categories":["integration","data access","automation","AI integration","environmental data"],"complexity":"medium","use_cases":["Expose EPA ECHO Clean Air Act API to AI agents via MCP","Automated environmental compliance queries and monitoring","Facility lookup and detailed facility info retrieval","Retrieve maps and geojson for visualization or geospatial analysis","Embed EPA air-quality data into custom AI apps or pipelines"],"estimated_setup_minutes":20,"required_services":["n8n instance (publicly reachable or via tunnel)","U.S. EPA Enforcement and Compliance History Online (ECHO) - Clean Air Act API (credentials)","AI agent or MCP-compatible client (e.g., Claude Desktop, Cursor) or other MCP consumer"],"key_features":["Converts 16 EPA ECHO Clean Air Act API operations into an MCP-compatible interface","MCP Trigger node exposes a server endpoint for AI agents","HTTP Request nodes perform calls to https://echodata.epa.gov/echo","AI-ready parameter mapping using $fromAI() expressions","Supports GET and POST variants for each operation (16 operations, 32 endpoints total variants listed in template description contextually handled by nodes/expressions where applicable.)"],"target_audience":["Developers integrating environmental data into apps","AI integrators building agent tool endpoints","Data engineers and analysts working with EPA air-quality data"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
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"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","AI","image-generation","chatbot-integration","content-creation"],"complexity":"medium","use_cases":["Generate marketing visuals and social media images","Create character art and digital posters","Storyboard and concept art generation","Automated daily image generation","Respond to image requests via Telegram or n8n chat"],"estimated_setup_minutes":20,"required_services":["Google Gemini (image generation access)","Telegram bot (optional, for chat trigger/response)","Local storage or file system access (optional)","HTTP endpoint access","Optional: OpenAI / Microsoft Copilot (if replacing Gemini)"],"key_features":["Prompt parsing and multi-step prompt transformation","Image generation via Google Gemini (configurable to other providers)","Default and customizable image size and model","Fetch and preview generated images via HTTP","Option to send images back through Telegram or save to disk automatically"],"target_audience":["Developers building AI-driven workflows","Marketers producing visual content at scale","Designers and illustrators prototyping concepts quickly"]}


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 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
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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metadata_json:
  {"categories":["monitoring","alerts","integration","communication","automation"],"complexity":"medium","use_cases":["Real-time workflow error notifications","Incident detection and response","Team notifications across messaging apps and email","Centralized monitoring for multiple n8n workflows","Automated escalation via optional channels or webhooks"],"estimated_setup_minutes":20,"required_services":["n8n instance (cloud or self-hosted)","Telegram bot (API + chat ID)","Gmail (OAuth credentials)","Discord (webhook) - optional","Slack (webhook) - optional","WhatsApp connection/credentials - optional"],"key_features":["Listens for any n8n workflow errors using Error Trigger node","Formats detailed error context (workflow name, node, message, timestamp, execution URL) via Code node","Sends multi-channel notifications: Telegram and Gmail by default","Optional Discord, Slack, and WhatsApp channels (disabled by default)","HTML-parsed rich messages for readability and actionable alerts','Easy customization of message template and enabled channels"],"target_audience":["n8n workflow developers","Operations/SRE teams","Small to medium businesses (SMBs) managing automations\",\"Automation enthusiasts and hobbyists"]}


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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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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metadata_json:
  {"categories":["automation","education","content-creation","assessment","AI"],"complexity":"complex","use_cases":["Generate MCQ quizzes from YouTube lecture or tutorial videos","Create assessments for corporate training videos","Build interactive quizzes for online courses","Enable student self-testing from recorded lectures","Engage audiences with automated quiz content for creators"],"estimated_setup_minutes":45,"required_services":["n8n (cloud or self-hosted) with LangChain nodes package","Google AI Studio / Gemini (Generative AI) API access","Google Cloud Project with Google Forms API enabled","Google Drive API enabled","Google OAuth2 credentials for Forms API","YouTube (public or unlisted video URLs)"],"key_features":["AI video analysis using Google Gemini to extract concepts from videos up to 50 minutes","Dynamic generation of up to 90 multiple-choice questions (3 options each)","Automatic Google Form creation with quiz settings and correct answers","Automatic grading and scoring configuration","Web form trigger for user inputs (title, email, video URL, question count)"],"target_audience":["Educators","Corporate trainers","Content creators and YouTubers building engagement tools"]}


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 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
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

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  ["n8n-nodes-base.reddit","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.telegram","n8n-nodes-base.splitOut","n8n-nodes-base.splitInBatches","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["crypto","automation","monitoring","alerting","analytics','social-listening','integration"],"complexity":"complex","use_cases":["Whale movement tracking and alerts","New token discovery within 24h of launch","Cross-source alpha/opportunity detection (on-chain + social + DEX)","Exploit/dump warnings and risk assessment","Trend scoring and prioritization for trading or research"],"estimated_setup_minutes":30,"required_services":["Etherscan API","Telegram Bot (BotFather)","OpenAI API","n8n instance (self-hosted or cloud)","(optional) Reddit OAuth","(optional) Twitter/Apify"],"key_features":["Real-time whale/smart-money monitoring","Multi-DEX price/volume and buy-pressure tracking","New token detection (early launch monitoring)","Social intelligence (Reddit/Twitter)","OpenAI-powered signal summarization and risk scoring (LOW/MEDIUM/HIGH/EXTREME)"],"target_audience":["Active crypto traders","DeFi researchers","Portfolio managers/analysts looking for early signals','Whale-watchers and alpha hunters','Developers/ops users automating crypto intelligence"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
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"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","content creation","social media","integration","AI"],"complexity":"complex","use_cases":["Convert static images + prompts into short AI-generated videos","Automated cross-platform publishing to YouTube and TikTok","Batch content creation and scheduled publishing","SEO-optimized video title generation and metadata tracking","Centralized task management via Google Sheets"],"estimated_setup_minutes":30,"required_services":["fal.run (MiniMax Hailuo 02 API)","Upload-Post.com (YouTube/TikTok upload proxy)","Google Sheets","Google Drive","YouTube account","TikTok account (may require paid Upload-Post plan)","OpenAI (GPT for SEO titles)","n8n"],"key_features":["End-to-end automation from Google Sheet row to published video","AI-driven video creation from image + prompt (MiniMax Hailuo 02)","Polling and status monitoring for asynchronous video processing","Uploads generated videos to Google Drive, YouTube and TikTok","GPT-generated SEO-optimized titles and metadata insertion into sheet, automated sheet updates with video links and status tracking, scheduled/batch processing, configurable video duration"],"target_audience":["Content creators and video marketers","Social media managers and growth teams","Digital agencies and consultants producing high-volume short videos for platforms like YouTube/TikTok, creators who want low-code automation"]}


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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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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metadata_json:
  {"categories":["automation","integration","chatbot","crypto"],"complexity":"simple","use_cases":["Fetch top meme coin prices on demand","Provide quick crypto price lookup inside Telegram","Community engagement via a bot command","Integrate CoinGecko market data into chat workflows"],"estimated_setup_minutes":10,"required_services":["Telegram Bot API","CoinGecko API","n8n instance (self-hosted or cloud)"],"key_features":["Telegram command trigger (/memecoin)","Fetch top 5 meme tokens by market cap from CoinGecko","Format human-readable price messages with links","Return real-time USD prices","Minimal 5-node workflow (trigger, IF, HTTP, function, send)"],"target_audience":["Developers","Crypto enthusiasts","Community managers"]}


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 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 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.

nodes_used:
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metadata_json:
  {"categories":["integration","data access","automation","government data"],"complexity":"medium","use_cases":["Allow AI agents to query EPA ECHO (RCRA) data (facilities, maps, geojson, downloads)","Build AI-driven environmental compliance or monitoring assistants","Embed RCRA data access into custom AI apps or agents via MCP","Perform geospatial queries and visualize facility data","Fetch paginated results, metadata, and bulk downloads for analysis"],"estimated_setup_minutes":20,"required_services":["U.S. EPA ECHO (RCRA) API (https://echodata.epa.gov/echo)","n8n instance with MCP trigger support"],"key_features":["MCP-compatible server endpoint exposing 16 RCRA API operations","Automatic $fromAI() parameter population for AI-driven requests","Native HTTP request handling with built-in error management","Supports GET and POST variants for multiple endpoints (facility, map, geojson, downloads, metadata, paginated qid, etc.)","Returns native EPA API responses directly to AI agents (no mapping required)"],"target_audience":["developers building AI integrations","data engineers/analysts working with environmental datasets","AI/agent builders (Claude, Cursor, custom agents) integrating external tools into workflows"]}


name: YouTube Analytics Data Reporting API Integration for AI Agents
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:42:46.204Z
updated_at: 2025-07-03T16:42:46.204Z
url: https://n8n.io/workflows/5637
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 8 YouTube Reporting API operations to AI agents.

  ⚡ Quick Setup

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

  📋 Available Operations (8 total)

  🔧 V1 (8 endpoints)

  • GET /v1/jobs: Retrieve Report Metadata
  • POST /v1/jobs: Creates a job and returns it.
  • DELETE /v1/jobs/{jobId}: Deletes a job.
  • GET /v1/jobs/{jobId}: Gets a job.
  • GET /v1/jobs/{jobId}/reports: Lists reports created by a specific job. Returns NOT_FOUND if the job does no...
  • GET /v1/jobs/{jobId}/reports/{reportId}: Gets the metadata of a specific report.
  • GET /v1/media/{resourceName}: Method for media download. Download is supported on the URI `/v1/media/{+name...
  • GET /v1/reportTypes: List Report Types

  🤖 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 YouTube Reporting API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

nodes_used:
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metadata_json:
  {"categories":["integration","api","automation","data processing","ai-integration"],"complexity":"medium","use_cases":["Expose YouTube Reporting API to AI agents (MCP)","Automate retrieval and listing of YouTube report metadata","Download report media and integrate report data into AI workflows","Enable AI agents to call YouTube Reporting endpoints as tools","Prototype or extend custom AI apps with native report access"],"estimated_setup_minutes":20,"required_services":["n8n instance","YouTube Reporting API / Google Cloud project (OAuth/Service Account credentials)","AI agents or platforms that support MCP (e.g., Claude, Cursor)"],"key_features":["MCP trigger acting as server endpoint for AI agents","8 prebuilt YouTube Reporting API operations (jobs, reports, media, reportTypes)","AI-ready parameter binding via $fromAI() expressions","Native n8n HTTP request nodes with built-in error handling and logging","Returns native YouTube Reporting API responses; easily extensible"],"target_audience":["developers","AI engineers","data analysts working with YouTube data integrations"]}


name: Star Wars Language Translation API for AI Agents - 6 Languages
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:42:57.695Z
updated_at: 2025-07-03T16:42:57.695Z
url: https://n8n.io/workflows/5638
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:34
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 6 Starwars Translations API operations to AI agents.

  ⚡ Quick Setup

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

  📋 Available Operations (6 total)

  🔧 Translate (6 endpoints)

  • GET /translate/cheunh: Translate to Cheunh
  • GET /translate/gungan: Translate to Gungan
  • GET /translate/huttese: Translate to Huttese
  • GET /translate/mandalorian: Translate to Mandalorian
  • GET /translate/sith: Translate to Sith
  • GET /translate/yoda: Translate to Yoda

  🤖 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 Starwars Translations API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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

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metadata_json:
  {"categories":["integration","automation","AI","translation"],"complexity":"simple","use_cases":["Expose Star Wars translation endpoints to AI agents via MCP","Translate user text to Cheunh, Gungan, Huttese, Mandalorian, Sith, or Yoda","Rapidly prototype AI tools or chatbots with Star Wars translations","Serve as a tool endpoint for Claude, Cursor, or custom AI apps","Extend or customize translation logic within n8n workflows"],"estimated_setup_minutes":200,"required_services":["FunTranslations Starwars Translations API (https://api.funtranslations.com)","n8n instance (with MCP trigger support)","AI agents or clients that consume MCP endpoints (e.g., Claude, Cursor, custom AI apps)","Optional: API credentials/token for FunTranslations"],"key_features":["MCP server endpoint exposing 6 translation operations","HTTP request nodes calling FunTranslations API","AI expressions ($fromAI()) to auto-populate parameters","Returns native API responses to requesting AI agents","Built-in HTTP error handling and n8n logging for production useability (extensible)"],"target_audience":["developers integrating AI tools","AI engineers and chatbot builders","no-code/low-code automation users familiar with n8n workflows\",\"hobbyists and community members experimenting with fun translations"]}


name: Background Removal API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:49:58.183Z
updated_at: 2025-07-03T16:49:58.183Z
url: https://n8n.io/workflows/5640
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 3 Background Removal 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 Background Removal 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 Background Removal 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.remove.bg/v1.0
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (3 total)

  🔧 Account (1 endpoints)

  • GET /account: Fetch Account Balance

  🔧 Improve (1 endpoints)

  • POST /improve: Submit Image for Improvement

  🔧 Removebg (1 endpoints)

  • POST /removebg: Remove Image Background

  🤖 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 Background Removal API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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

workflow_json_compressed:
  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

metadata_json:
  {"categories":["integration","automation","image-processing","AI"],"complexity":"simple","use_cases":["Remove image backgrounds programmatically","Improve/enhance images via remove.bg improve endpoint","Expose remove.bg functionality as an MCP tool for AI agents","Integrate background removal into AI-driven workflows and apps","Query account balance and usage for billing/monitoring"],"estimated_setup_minutes":20,"required_services":["remove.bg Background Removal API (api.remove.bg)","n8n instance (self-hosted or n8n.cloud)","AI agent or client that supports MCP (e.g., Claude Desktop, Cursor, custom AI apps)"],"key_features":["MCP-compatible server endpoint for AI agents","Three ready endpoints: GET /account, POST /improve, POST /removebg","Automatic parameter population using $fromAI() expressions","Native n8n HTTP Request nodes with built-in error handling and logging","Quick deploy: import workflow, add credentials, activate webhook/SSE URL, connect agents"],"target_audience":["developers","AI engineers","automation architects / integrators"]}


name: topupsapi MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:49:59.290Z
updated_at: 2025-07-03T16:49:59.290Z
url: https://n8n.io/workflows/5641
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:34
description:
  Complete MCP server exposing 2 topupsapi 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 topupsapi 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 topupsapi 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://polls.apiblueprint.org
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Questions (2 endpoints)

  • GET /questions: Create Question 1
  • POST /questions: Create a New Question

  🤖 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 topupsapi API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","AI agent tooling","API gateway"],"complexity":"simple","use_cases":["Expose REST API endpoints to AI agents via MCP","Allow AI agents to read and create poll questions","Quickly prototype agent tool integrations","Provide a lightweight server for agent-based workflows","Testing and demoing MCP-enabled AI tools"],"estimated_setup_minutes":20.5,"required_services":["n8n instance (hosted or self-hosted)","topupsapi / polls.apiblueprint.org API (external HTTP API)","MCP-capable AI agent or client (e.g., Claude Desktop, Cursor)"],"key_features":["MCP trigger acting as an AI-agent-accessible server endpoint","Two exposed endpoints: GET /questions and POST /questions","HTTP Request nodes to proxy calls to the external API","Automatic parameter population via $fromAI() expressions","Native API responses returned directly to agents (full data structure)"],"target_audience":["developers integrating APIs with AI agents","AI/ML engineers building agent tools","product builders prototyping conversational tool integrations"]}


name: Pinecone API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:50:18.920Z
updated_at: 2025-07-03T16:50:18.920Z
url: https://n8n.io/workflows/5642
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:34
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

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

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add Pinecone 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 Pinecone 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://controller.{environment}.pinecone.io
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (15 total)

  🔧 Collections (4 endpoints)

  • GET /collections: Describe Collection
  • POST /collections: Create collection
  • DELETE /collections/{collectionName}: Delete Collection
  • GET /collections/{collectionName}: Describe collection

  🔧 Describe_Index_Stats (1 endpoints)

  • POST /describe_index_stats: Retrieve Index Stats

  🔧 Indexes (5 endpoints)

  • GET /indexes: Configure Index
  • POST /indexes: Create index
  • DELETE /indexes/{indexName}: Delete Index
  • GET /indexes/{indexName}: Describe index
  • PATCH /indexes/{indexName}: Configure index

  🔧 Query (1 endpoints)

  • POST /query: Execute Query

  🔧 Vectors (4 endpoints)

  • POST /vectors/delete: Delete Vectors
  • POST /vectors/fetch: Fetch Vectors
  • POST /vectors/update: Update Vectors
  • POST /vectors/upsert: Upsert Vectors

  🤖 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 Pinecone API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","ai-integration","data-processing"],"complexity":"medium","use_cases":["Expose Pinecone vector DB operations to AI agents (MCP)","Index management (create/delete/configure)","Vector CRUD (upsert, fetch, update, delete) and query execution","Connect AI agents (Claude, Cursor, custom) to Pinecone for RAG or retrieval","Build custom AI tools that call Pinecone via a unified MCP endpoint"],"estimated_setup_minutes":20,"required_services":["Pinecone API (account + API key)","n8n instance (self-hosted or n8n cloud)","AI agent/client that supports MCP (e.g., Claude Desktop, Cursor, custom agents)","Publicly reachable webhook URL or tunneling if n8n is local"],"key_features":["Complete MCP server exposing 15 Pinecone API operations","Automatic parameter population via $fromAI() expressions","Supports collections, indexes, query, and vector endpoints","Native n8n HTTP request handling and error management","Returns native Pinecone API responses to AI agents directly"],"target_audience":["Developers building AI integrations","AI/ML engineers using vector DBs","Data engineers managing embeddings and indexes"]}


name: Transportation Laws and Incentives MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:51:11.627Z
updated_at: 2025-07-03T16:51:11.627Z
url: https://n8n.io/workflows/5644
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 4 Transportation Laws and Incentives 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 Transportation Laws and Incentives 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 Transportation Laws and Incentives API into an MCP-compatible interface for AI agents.

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • HTTP Request Nodes: Handle API calls to http://developer.nrel.gov/api/transportation-incentives-laws
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (4 total)

  🔧 V1.{Output_Format} (1 endpoints)

  • GET /v1.{output_format}: Return a full list of laws and incentives that match your query.

  🔧 V1 (3 endpoints)

  • GET /v1/category-list.{output_format}: Return the law categories for a given category type.
  • GET /v1/pocs.{output_format}: Get the points of contact for a given jurisdiction.
  • GET /v1/{id}.{output_format}: Fetch the details of a specific law given the law's ID.

  🤖 AI Integration

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

  Response Format: Native Transportation Laws and Incentives API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

nodes_used:
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metadata_json:
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name: Swagger2OpenAPI Converter MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:51:57.066Z
updated_at: 2025-07-03T16:51:57.066Z
url: https://n8n.io/workflows/5646
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 6 Swagger2OpenAPI Converter API operations to AI agents.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Credentials Add Swagger2OpenAPI Converter 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 Swagger2OpenAPI Converter 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://mermade.org.uk/api/v1
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (6 total)

  🔧 Badge (1 endpoints)

  • GET /badge: Redirect to Badge SVG

  🔧 Convert (2 endpoints)

  • GET /convert: Convert Swagger in Body
  • POST /convert: Convert a Swagger 2.0 definition passed in the body to OpenAPI 3.0.x 

  🔧 Status (1 endpoints)

  • GET /status: Check API Status

  🔧 Validate (2 endpoints)

  • GET /validate: Validate OpenAPI in Body
  • POST /validate: Validate an OpenAPI 3.0.x definition supplied in the body of the 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 Swagger2OpenAPI Converter 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.stickyNote","n8n-nodes-base.httpRequestTool"]

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metadata_json:
  {"categories":["integration","automation","developer tools","API conversion","AI integration"],"complexity":"medium","use_cases":["Convert Swagger 2.0 definitions to OpenAPI 3.0.x","Validate OpenAPI specifications","Expose API conversion/validation as an MCP tool for AI agents","Embed API conversion into AI-driven workflows or custom apps","Provide a programmatic badge redirect endpoint and status checks"],"estimated_setup_minutes":20,"required_services":["n8n instance (webhook-accessible)","Swagger2OpenAPI Converter API (https://mermade.org.uk/api/v1) - credentials required","AI agent or platform to consume MCP endpoints (e.g., Claude, Cursor, custom AI apps)"],"key_features":["MCP server exposing 6 Swagger2OpenAPI endpoints (convert, validate, badge, status)","GET and POST conversion endpoints for Swagger→OpenAPI","AI-ready parameter binding using $fromAI() expressions","Native n8n HTTP Request handling with built-in error management and logging","Direct response passthrough to calling AI agents (native API responses returned to agent)"],"target_audience":["API developers","Integration engineers","AI/assistant developers integrating tools for agents or chatops workflows"]}


name: Clean Company Names for Cold Emails with GPT-4 Mini and Google Sheets
author_name: James Francis
author_username: paperjam
categories: []
created_at: 2025-07-03T17:03:37.291Z
updated_at: 2025-07-03T17:03:37.291Z
url: https://n8n.io/workflows/5647
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  Overview
  In cold email campaigns, the lead's company name is the 2nd most frequently inserted variable after their first name. They're critical for effective cold email personalization. However, company names are often messy and can contain taglines, legal suffixes (e.g. LLC, Inc.), and other variations that would never be written out by a human in an email.

  If your email starts with "I came across Techwave Solutions LLC on LinkedIn...", it's a dead giveaway that you're sending a tempalted email and a response is much less likely. 

  This simple workflow uses AI to clean up messy company names in a Google Sheet so that your cold email campaigns can achieve better results. 

  How It Works
  A form is submitted with a Google Sheet url
  The workflow grabs the leads and uses an LLM node to clean the company names
  The updated leads are saved back in a new sheet within the original spreadsheet

  Setup Steps
  Add your Google Sheets and OpenAI (or your AI model provider of choice) credentials to n8n
  Create a Google Sheet with your list of leads. IMPORTANT: the sheet MUST have a column called "Company"
  (Optional). The AI workflow has a highly optimized system prompt. However, you may achieve better results by updating the list of examples in the prompt with companies (real or fake) in the industry you're targeting.

  If you have any questions or feedback about this workflow, or would like me to build custom workflows for your business, email me at n8n@paperjam.agency.

nodes_used:
  ["n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","data processing","integration","email outreach"],"complexity":"simple","use_cases":["Clean and standardize company names for cold email personalization","Preprocess lead data in Google Sheets","Improve email deliverability and reply rates via better personalization","Batch-normalize company name variations and legal suffixes"],"estimated_setup_minutes":15,"required_services":["Google Sheets","OpenAI (or compatible LLM provider)","n8n"],"key_features":["Uses an LLM to clean and normalize messy company names","Reads leads from a Google Sheet and writes results to a new sheet","Trigger via form submission","Editable system prompt with example mappings for domain/industry-specific tuning","Non-destructive update (outputs to a new sheet)"],"target_audience":["marketers","sales development reps (SDRs)","growth teams and demand gen specialists`,`small business owners and founders`,`data operators/analysts handling lead lists"]}


name: Sync Linear Issues to Todoist Tasks Automatically (Create, Update, Close)
author_name: Léo Mathurin
author_username: leo-mathurin
categories: []
created_at: 2025-07-03T17:12:27.386Z
updated_at: 2025-07-03T17:12:27.386Z
url: https://n8n.io/workflows/5648
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  ✨ Try It Out!
  Sync your Linear issues to Todoist automatically with this n8n workflow. When an issue is created, updated, or completed in Linear, a corresponding task is created, updated, or closed in Todoist.

  ⚙️ How It Works

  Triggered by issue changes via linearTrigger
  Routes based on action (create, update, remove)
  Checks if a matching Todoist task already exists (via issue ID)
  If the issue has:
    A due date
    And is assigned to you (youremail@example.com)  
    ➤ Then it creates or updates the task accordingly
  If the issue is marked Done, the Todoist task is closed
  If it's deleted in Linear, the Todoist task is also removed
  Sub-issues get enriched with their parent title for clarity

  🛠️ Customization

  Replace youremail@example.com with your Linear email in the IF nodes
  Adjust which states are synced (e.g. “In Progress”, “Todo”...)
  Customize the Todoist project, labels, or title formatting

  ⚠️ Bi-directional Sync?

  This workflow is one-way (Linear ➜ Todoist).  
  Bi-directional syncing might be possible but isn’t handled here—it would be a cool upgrade!

  ✅ Requirements

  n8n with OAuth2 access to Linear and Todoist
  Your Linear email set in the workflow for filtering
  A target Todoist project (default: Inbox)

  💬 Need Help?

  Ask in the n8n Forum or join the Discord.

  Happy Automating! 🚀

nodes_used:
  ["n8n-nodes-base.todoist","n8n-nodes-base.linearTrigger","n8n-nodes-base.todoist","n8n-nodes-base.if","n8n-nodes-base.todoist","n8n-nodes-base.noOp","n8n-nodes-base.switch","n8n-nodes-base.if","n8n-nodes-base.switch","n8n-nodes-base.todoist","n8n-nodes-base.if","n8n-nodes-base.linear","n8n-nodes-base.set","n8n-nodes-base.todoist","n8n-nodes-base.switch","n8n-nodes-base.todoist","n8n-nodes-base.todoist","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.todoist","n8n-nodes-base.linear","n8n-nodes-base.set","n8n-nodes-base.todoist","n8n-nodes-base.todoist","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["integration","task automation","productivity"],"complexity":"medium","use_cases":["Sync Linear issues to Todoist tasks (create/update/close)","Keep personal Todoist list updated from engineering workflow","Automatically close or remove tasks when issues are done/deleted","Enrich sub-issues with parent titles for clarity","Filter and sync only issues assigned to a specific user"],"estimated_setup_minutes":20,"required_services":["n8n instance with OAuth2 credentials","Linear (OAuth2 API access)","Todoist (OAuth2 API access)"],"key_features":["One-way sync from Linear -> Todoist","Creates Todoist tasks when Linear issues are created","Updates Todoist tasks when Linear issues change (title, due date, assignment)","Closes Todoist tasks when Linear issues are marked Done","Deletes Todoist tasks when Linear issues are deleted in Linear (remove action)"],"target_audience":["Developers","Product managers","Engineering teams using Linear and Todoist for task management"]}


name: [New York Times] Article Search API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T17:16:42.689Z
updated_at: 2025-07-03T17:16:42.689Z
url: https://n8n.io/workflows/5649
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 1 Article Search 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 Article Search 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 Article Search API into an MCP-compatible interface for AI agents.

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

  📋 Available Operations (1 total)

  🔧 Articlesearch.Json (1 endpoints)

  • GET /articlesearch.json: Search Articles

  🤖 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 Article Search 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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workflow_json_compressed:
  [encoded data, 4532 characters]

metadata_json:
  {"categories":["integration","automation","AI integration","data retrieval"],"complexity":"simple","use_cases":["Search NYT articles programmatically","Provide news search as a tool for AI agents","Feed article data into content-generation or research workflows","Build news monitoring or alerting systems"],"estimated_setup_minutes":20,"required_services":["New York Times Article Search API (api.nytimes.com)","n8n instance (self-hosted or cloud)","AI agent or client that supports MCP endpoints (e.g., Claude, Cursor, custom AI apps)"],"key_features":["MCP Trigger exposes Article Search API to AI agents","HTTP Request nodes call NYT /articlesearch.json endpoint","AI-aware parameter population via $fromAI() expressions","Returns native NYT API responses to agents","Built-in HTTP error handling and n8n logging/SSE support (for agents)"],"target_audience":["Developers","AI engineers/integrators","Data journalists and researchers」「Content teams and product builders"]}


name: NPR Listening Service MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T17:17:19.888Z
updated_at: 2025-07-03T17:17:19.888Z
url: https://n8n.io/workflows/5650
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 9 NPR Listening Service 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 NPR Listening Service credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

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

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

  📋 Available Operations (9 total)

  🔧 V2 (9 endpoints)

  • GET /v2/aggregation/{aggId}/recommendations: Get a set of recommendations for an aggregation independent of the user's lis...
  • GET /v2/channels: List Available Channels
  • GET /v2/history: Get User Ratings History
  • GET /v2/organizations/{orgId}/categories/{category}/recommendations: Get a list of recommendations from a category of content from an organization
  • GET /v2/organizations/{orgId}/recommendations: Get a variety of details about an organization including various lists of rec...
  • GET /v2/promo/recommendations: Get Recent Promo Audio
  • POST /v2/ratings: Submit Media Ratings
  • GET /v2/recommendations: Get User Recommendations
  • GET /v2/search/recommendations: Get Search 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 NPR Listening Service API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","AI-integration","media"],"complexity":"medium","use_cases":["Expose NPR Listening Service to AI agents as an MCP tool","Provide recommendations, search, promo and channel data to AI workflows","Allow AI agents to submit user ratings and access user history","Rapidly prototype AI integrations with NPR content (Claude, Cursor, custom apps)","Extend or customize NPR API logic within n8n workflows"],"estimated_setup_minutes":20,"required_services":["NPR Listening Service API (listening.api.npr.org)","n8n instance with MCP trigger node","NPR Listening Service credentials / API key"],"key_features":["MCP server endpoint exposing 9 NPR Listening Service endpoints (recommendations, search, channels, history, ratings, promos, organization/category lookups)","MCP Trigger node to accept AI agent requests","HTTP Request nodes mapping to NPR API endpoints","$fromAI() expressions to auto-populate path/query/body parameters","Native n8n HTTP error handling and logging for production readiness`,`Easily extensible to add custom logic or additional endpoints"],"target_audience":["developers","AI engineers","integration specialists\",\"product managers"]}


name: Mobility API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T17:17:40.259Z
updated_at: 2025-07-03T17:17:40.259Z
url: https://n8n.io/workflows/5651
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:34
description:
  Complete MCP server exposing 2 Mobility 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 Mobility 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 Mobility 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://developer.o2.cz/mobility/sandbox/api
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (2 total)

  🔧 Info (1 endpoints)

  • GET /info: Retrieve Application Info

  🔧 Transit (1 endpoints)

  • GET /transit/{from}/{to}: Transit between basic residential units

  🤖 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 Mobility 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: 217 characters]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","AI-integration"],"complexity":"simple","use_cases":["Expose Mobility API as an MCP server for AI agents","Allow AI agents to call /info and /transit endpoints","Prototype AI-driven transit or location workflows","Proxy and log Mobility API responses for AI consumption"],"estimated_setup_minutes":200,"required_services":["Mobility API (https://developer.o2.cz/mobility/sandbox/api)","n8n instance with credentials configured","MCP-capable AI agents or platforms (e.g., Claude, Cursor, custom AI apps)"],"key_features":["MCP Trigger serving as server endpoint for AI agents","HTTP Request nodes mapping to Mobility API endpoints","AI-driven parameter population via $fromAI() expressions","Native Mobility API response passthrough","Built-in HTTP request error handling and n8n logging support (extensible)"],"target_audience":["developers","AI engineers","automation/ops engineers using n8n integrations and MCP agents"]}


name: NPR Station Finder Service MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T17:19:57.522Z
updated_at: 2025-07-03T17:19:57.522Z
url: https://n8n.io/workflows/5654
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 2 NPR Station Finder Service 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 NPR Station Finder Service credentials
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  This workflow converts the NPR Station Finder Service API into an MCP-compatible interface for AI agents.

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

  📋 Available Operations (2 total)

  🔧 V3 (2 endpoints)

  • GET /v3/stations: Get Station 1
  • GET /v3/stations/{stationId}: Retrieve metadata for the station with the given numeric ID

  🤖 AI Integration

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

  Response Format: Native NPR Station Finder Service API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","AI","API"],"complexity":"simple","use_cases":["Expose NPR Station Finder API as MCP endpoints for AI agents","Enable AI/chatbots to look up station lists and station metadata","Rapidly prototype AI tools that need radio station info","Integrate station metadata into apps or workflows"],"estimated_setup_minutes":20,"required_services":["n8n instance with MCP enabled","NPR Station Finder Service (https://station.api.npr.org)","AI agent or platform (e.g., Claude, Cursor, custom AI apps)"],"key_features":["MCP trigger acting as server endpoint for AI agents","Two GET endpoints: /v3/stations and /v3/stations/{stationId}","HTTP Request nodes proxying requests to NPR API","$fromAI() expressions to auto-populate parameters from agents","Native response passthrough and built-in HTTP error handling','Easily extensible to add custom logic or endpoints"],"target_audience":["developers","AI builders and integrators","automation/citizen integrators looking to expose APIs to agents"]}


name: Notion API MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T17:20:55.744Z
updated_at: 2025-07-03T17:20:55.744Z
url: https://n8n.io/workflows/5655
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing 13 Notion API operations to AI agents.

  ⚡ Quick Setup

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

  📋 Available Operations (13 total)

  🔧 V1 (13 endpoints)

  • DELETE /v1/blocks/{id}: Delete a block
  • GET /v1/blocks/{id}: Retrieve a block
  • PATCH /v1/blocks/{id}: Update a block
  • GET /v1/blocks/{id}/children: Retrieve block children
  • PATCH /v1/blocks/{id}/children: Append block children
  • GET /v1/comments: Retrieve Comments
  • GET /v1/databases/{id}: Retrieve a database
  • PATCH /v1/databases/{id}: Update a database
  • POST /v1/databases/{id}/query: Query a database
  • GET /v1/pages/{id}: Retrieve a Page
  • PATCH /v1/pages/{id}: Update Page properties 
  • GET /v1/pages/{page_id}/properties/{property_id}: Retrieve a Page Property Item
  • GET /v1/users/{id}: Retrieve a 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 Notion API responses with full data structure

  Error Handling: Built-in n8n HTTP request error management

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

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

  ✨ Benefits

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

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

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

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metadata_json:
  {"categories":["integration","automation","developer tools","ai integration","api gateway"],"complexity":"medium","use_cases":["Expose Notion API to AI agents as an MCP tool","Allow agents to read, create, update, and delete Notion blocks/pages/databases","Enable agent-driven workflows and automations against Notion data","Prototype AI integrations and tools that operate on Notion content","Provide a unified API gateway for multiple AI clients (Claude, Cursor, custom agents)"],"estimated_setup_minutes":200,"required_services":["Notion API (workspace and integration token)","n8n instance (self-hosted or cloud)","Publicly reachable webhook endpoint (or tunnel like ngrok)","AI agents or tools that support MCP (optional: Claude, Cursor, custom agents)"],"key_features":["Implements 13 Notion endpoints (blocks, pages, databases, comments, users)","MCP Trigger node exposes server endpoint for AI agents","Automatic parameter population via $fromAI() expressions","Returns native Notion API responses to agents","Built-in n8n HTTP request error handling and logging support easy debugging and production useability (sic)"],"target_audience":["Developers","AI/ML engineers building agent tooling","Automation/integration engineers using n8n and Notion APIs\",\"No-code/low-code creators leveraging n8n workflows\",\"Product teams prototyping Notion-powered AI features"]}


name: Auto-Generate WhatsApp Proposals from Voice or Text using GPT & APITemplate
author_name: Floyd Mahou
author_username: floyd
categories: []
created_at: 2025-07-03T18:30:35.302Z
updated_at: 2025-07-03T18:30:35.302Z
url: https://n8n.io/workflows/5656
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  How it works
  • Transcribes a WhatsApp voice or text message from a prospect using Whisper or GPT
  • Extracts key information (name, need, context, urgency) via AI
  • Matches the most relevant service pack by comparing the prospect’s need with Airtable data
  • Dynamically fills a branded template via APITEMPLATE (HTML or PDF)
  • Generates a clean, personalized business proposal — including dynamic links (payment, calendar, etc.)
  • Sends the final PDF back instantly via WhatsApp or email

  Set up steps
  • ⏱ Estimated setup time: 45–60 minutes
  • ✅ You’ll need:
   ◦ WhatsApp Business Cloud API access (with webhook configured)
   ◦ OpenAI API key (Whisper + GPT)
   ◦ Airtable (to store service packs and client input)
   ◦ APITEMPLATE account (template with placeholders like {{nom}}, {{prix}}, {{lien_reservation}}, etc.)
   ◦ n8n instance (cloud or self-hosted)

  • 📦 Create your service packs in Airtable with associated links (Stripe, Calendly…)
  • 🔗 The proposal auto-includes these links dynamically inside the PDF
  • 🚀 Workflow orchestrates the end-to-end process: from WhatsApp input to PDF delivery

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.whatsAppTrigger","n8n-nodes-base.switch","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.whatsApp","@n8n/n8n-nodes-langchain.toolCalculator","n8n-nodes-base.airtableTool","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.apiTemplateIo","n8n-nodes-base.whatsApp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","communication","document-generation","AI-assistant","sales"],"complexity":"medium","use_cases":["Automatically convert WhatsApp voice/text leads into branded proposals","Extract prospect details and qualify leads","Match prospect needs to service packages and generate pricing","Deliver personalized PDFs with payment and booking links via WhatsApp or email","Maintain a record of proposals in Airtable"],"estimated_setup_minutes":50,"required_services":["WhatsApp Business Cloud API (webhook)","OpenAI API (Whisper + GPT)","Airtable","APITEMPLATE (HTML/PDF templates)","n8n instance (cloud or self‑hosted)","Optional: Stripe/Calendly or other payment/booking links"],"key_features":["Transcribe voice or process text messages (Whisper/GPT)","AI extraction of name, need, context, urgency","Match prospect need to Airtable service packs","Dynamically populate APITEMPLATE templates (HTML/PDF)","Include dynamic links (payment, calendar) in proposals automatically sent back via WhatsApp or email"],"target_audience":["Freelancers, consultants, and agencies","Sales teams and business development reps","Small business owners who send proposals frequently」「Automation engineers / DevOps who implement integrations"]}


name: Website Content Scraper & SEO Keyword Extractor with GPT-4o-mini and Airtable
author_name: Abhishek Patoliya
author_username: abhishekpatoliya
categories: []
created_at: 2025-07-03T18:55:58.316Z
updated_at: 2025-07-03T18:55:58.316Z
url: https://n8n.io/workflows/5657
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow allows you to scrape website content, clean the HTML, extract structured information using GPT-4o-mini, and store the results along with SEO keywords into Airtable. Ideal for building keyword lists and organizing web content for SEO research.

  Setup Instructions

  1. Prerequisites

  n8n Community or Cloud instance
  Airtable account with a base and table ready
  OpenAI API Key with access to GPT-4o-mini

  2. Airtable Structure

  Ensure your Airtable table has the following fields:

  | Field Name   | Type    | Notes                           |
  | ------------ | ------- | ------------------------------- |
  | Website Name | String  | Name or URL of the website      |
  | Data         | String  | Cleaned website text            |
  | Keyword      | String  | Extracted SEO keyword list      |
  | Status       | Options | Values: Todo, In progress, Done |

  3. Node Setup

  ✅ Form Trigger:
  Collects website URL from the user.

  ✅ HTTP Request:
  Fetches the website content.

  ✅ HTML Cleaner (Code Node):
  Strips out styles, tags, and whitespace to get clean text.

  ✅ Topic Extractor (AI Agent + GPT-4o-mini):
  Extracts topic-wise information from the cleaned website content.

  ✅ Text Cleaner (Code Node):
  Removes unwanted symbols like ### and **.

  ✅ Keyword Extractor (AI Agent + GPT-4o-mini):
  Generates a list of 90 important SEO keywords.

  ✅ Airtable Upsert:
  Stores the cleaned data, keywords, and status in Airtable.

  4. Key Features

   ✅ Automatic website content scraping
   ✅ Clean HTML and extract plain text
   ✅ Use GPT-4o-mini for topic-wise information extraction
   ✅ Generate 90-keyword SEO lists
   ✅ Store and manage data in Airtable

  5. Use Cases

  SEO Keyword Research
  Competitor Website Content Analysis
  Structured Website Data Collection

  Additional Workflow Recommendations

  ✅ Rename Nodes for Clarity

  | Current Name | Suggested Name                  |
  | ------------ | ------------------------------- |
  | Website Name | Website URL Input Form          |
  | HTTP Request | Fetch Website Content           |
  | Code         | HTML to Plain Text Cleaner      |
  | Split Out1   | Clean Text Splitter             |
  | AI Agent1    | Topic Extractor (GPT-4o-mini)   |
  | Code1        | Text Cleanup Formatter          |
  | Split Out2   | Final Text Splitter             |
  | AI Agent     | Keyword Extractor (GPT-4o-mini) |
  | Airtable     | Airtable Data Upsert            |
  | Wait1        | Delay Before Merge              |
  | Merge        | Combine Data for Airtable       |

nodes_used:
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metadata_json:
  {"categories":["automation","integration","data processing","web scraping","SEO"],"complexity":"medium","use_cases":["SEO keyword research","Competitor website content analysis","Structured website data collection","Content research and organization","Building keyword lists for SEO campaigns"],"estimated_setup_minutes":30,"required_services":["n8n (Community or Cloud instance)","Airtable (base + table)","OpenAI API (access to GPT-4o-mini)"],"key_features":["Automatic website content scraping","HTML cleaning and plain-text extraction","Topic-wise information extraction using GPT-4o-mini","Generation of a 90-item SEO keyword list","Upsert results into Airtable with status tracking"],"target_audience":["SEO specialists","Content marketers","Growth marketers/analysts doing competitive research and automation engineers"]}


name: Call Center Analytics with Dual-AI Verification using DeepSeek Models
author_name: Omar Akoudad
author_username: mediaplusma
categories: []
created_at: 2025-07-03T19:19:20.781Z
updated_at: 2025-07-03T19:19:20.781Z
url: https://n8n.io/workflows/5658
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  The workflow is well-designed for CRM analysis with a robust quality control mechanism. The dual-AI approach ensures reliable results, while the webhook integration makes it production-ready for real-time CRM data processing.


  Dual-AI Architecture: Uses DeepSeek Reasoner for analysis and DeepSeek Chat for verification.

  Flexible Input: Supports both manual testing and production webhook integration.

  Quality Assurance: Built-in verification system to ensure report accuracy.
  Comprehensive Analysis: Covers lead conversion, upsell metrics, agent ranking, and more.
  Professional Output: Generates structured markdown reports with actionable insights

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatDeepSeek","@n8n/n8n-nodes-langchain.lmChatDeepSeek","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm"]

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metadata_json:
  {"categories":["automation","integration","data analytics","AI/ML","CRM"],"complexity":"medium","use_cases":["Real-time CRM call center analytics","Automated report generation with QA verification","Agent performance and ranking","Lead conversion and upsell metric analysis","Webhook-driven production data processing"],"estimated_setup_minutes":45,"required_services":["n8n instance","DeepSeek Reasoner API","DeepSeek Chat API","CRM or any webhook-capable system (e.g., Salesforce, HubSpot, Zendesk)","Optional: storage or DB for logs/reports"],"key_features":["Dual-AI pipeline (analysis + independent verification)","Webhook support for real-time ingestion","Manual testing mode for validation","Structured Markdown report generation with actionable insights","Quality assurance step to verify report accuracy before output"],"target_audience":["Call center managers","Data analysts","CRM administrators and ops teams\",\"Customer success teams\",\"Developers/engineers responsible for automation"]}


name: Generate Personalized Language Learning News Digests with LLaMA-3.1 & DeepSeek AI
author_name: hippolyte-hu
author_username: hippolyte-hu
categories: []
created_at: 2025-07-03T20:51:28.594Z
updated_at: 2025-07-03T20:51:28.594Z
url: https://n8n.io/workflows/5660
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Automatically generate and email level-appropriate language learning content based on trending news.  
  This workflow reads learner preferences from Google Sheets (language, level, and topic of interest), uses an AI web search model to fetch relevant news, and formats the result into a structured HTML digest featuring grammar explanations and vocabulary highlights.  
  Emails are sent automatically to each learner in a clean, mobile-friendly format.

  ⚙️ What it does

  ⏰ Daily Trigger at 6 AM  
  📄 Pulls learner data from Google Sheets (Language, Level, Topic)  
  🔍 Fetches news using perplexity/llama-3.1-sonar-small-128k-online  
  ✨ Formats it into HTML using deepseek-chat, tailored to the learner's level  
  🧠 Adds grammar breakdowns and vocabulary highlights  
  📬 Sends personalized HTML email to each learner

  🧠 AI Models Used

  perplexity/llama-3.1-sonar-small-128k-online – web-connected LLM for up-to-date news  
  deepseek-chat – formatting and simplifying articles for language learners

  📚 Examples

  🔗 Technologies used

  Google Sheets** – Learner database  
  OpenRouter API** – AI access and online reasoning  
  LangChain AI Agent + Output Parser** – Clean HTML structuring  
  Gmail Node** – Email dispatch per user

  💡 Use Cases

  🧑‍🏫 Classroom-ready language micro-lessons  
  🌍 Personalized news digests for multilingual learners  
  ✉️ Daily practice delivery via email  
  📚 Reading + grammar + vocab in one workflow

nodes_used:
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metadata_json:
  {"categories":["automation","integration","education","content generation","personalization"],"complexity":"medium","use_cases":["Daily personalized language-learning news digests","Classroom micro-lessons and homework delivery","Automated reading + grammar + vocabulary practice","Delivering level-appropriate content via email"],"estimated_setup_minutes":60,"required_services":["Google Sheets (learner database)","OpenRouter API / perplexity/llama-3.1-sonar-small-128k-online (web-connected LLM)","DeepSeek AI (deepseek-chat)","Gmail or Google Workspace (email dispatch)","LangChain agent / Output parser (for structuring HTML)"],"key_features":["Scheduled daily trigger","Reads per-learner preferences from Google Sheets","Web-connected AI search for trending news","LLM-based simplification and level-appropriate formatting to HTML","Grammar explanations and vocabulary highlights added per article entrywise output parsing for clean HTML structure and mobile-friendly emails"],"target_audience":["Language teachers and tutors","EdTech developers and product teams","Curriculum designers/instructional coaches for language programs」「Self-directed language learners who want daily practice"]}


name: AI Image Nudity Detection Tool with Image Moderation API
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T21:35:42.502Z
updated_at: 2025-07-03T21:35:42.502Z
url: https://n8n.io/workflows/5661
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Complete MCP server exposing 1 Image Moderation 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 Image Moderation 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 Image Moderation 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.moderatecontent.com/moderate/
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Returns responses directly to the AI agent

  📋 Available Operations (1 endpoints)

  General (1 operation)
  Detect Nudity in Images

  🤖 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 Image Moderation 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]

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metadata_json:
  {"categories":["integration","automation","content-moderation","image-processing","ai"],"complexity":"simple","use_cases":["Automated image nudity detection","Content moderation for user uploads","Expose image-moderation as a tool for AI agents","Integrating moderation into chatbots or apps","Pre-filtering images before publishing or analysis"],"estimated_setup_minutes":20,"required_services":["ModerateContent Image Moderation API (https://api.moderatecontent.com/moderate/)","n8n instance (hosted or self-hosted)","AI agent or client that can call an MCP endpoint (e.g., Claude, Cursor, custom AI apps)"],"key_features":["MCP trigger exposes a server endpoint for AI agents","Single operation: Detect Nudity in Images via Image Moderation API","HTTP Request nodes call the external moderation API","Automatic parameter population via $fromAI() expressions","Returns native Image Moderation API responses to agents (full data structure)"],"target_audience":["developers","AI engineers","platform/product teams implementing safety filters or moderation pipelines"]}


name: Transform Voice Memos into Daily Journals & Tasks with OMI.ME & Gemini AI
author_name: Angel Menendez
author_username: djangelic
categories: []
created_at: 2025-07-04T00:29:40.455Z
updated_at: 2025-07-04T00:29:40.455Z
url: https://n8n.io/workflows/5662
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who’s it for

  This template is perfect for OMI pendant users or anyone with AI-generated memory transcripts who want to:

  Automatically create daily journals in Markdown
  Extract actionable tasks from conversations
  Store memories in Google Drive
  Sync action items to Google Tasks

  Great for creators, ADHD professionals, techies, or productivity hackers who want to build a second brain workflow with no manual data entry.

  What it does / How it works

  This workflow:

  Accepts POST data from the OMI AI pendant (via webhook)
  Extracts structured summaries, tasks, events, and raw transcript data
  Converts the transcript into Markdown using metadata like emoji, category, and overview
  Uses Google Gemini or an AI Agent to generate a high-quality journal entry
  Splits out action items and creates tasks in Google Tasks
  Uploads both the transcription and the final journal file into separate Google Drive folders for archival
  Deletes processed files if needed (cleanup path is included)

  How to set up

  Connect your OMI device to send daily summaries to the webhook endpoint
  Authenticate your Google Drive and Google Tasks accounts
  Replace any hardcoded values (like folder IDs or task list IDs) with your own
  Review the system prompt in the AI Agent node if you'd like to personalize your journal style

  ## Requirements

  OMI pendant or device that generates .md summaries via API or webhook
  Google Drive & Google Tasks credentials set up in n8n
  Optional: Google Gemini or OpenAI for natural language journal generation

  ## How to customize

  Change the output folder IDs for GDrive in the Upload Transcription and Upload Journal nodes. One folder is for long term storage and the other is short term, the contents of which are deleted every night to generate the journal entries. Ensure your workflow timezone is set correctly in the settings. 
  Replace Google Tasks with another todo app (e.g. Notion, Todoist) using HTTP or native nodes
  Customize the AI prompt in the AI Agent or Gemini Chat node to reflect your tone (e.g., poetic, minimalist, spiritual)
  Modify the Markdown format in the Build Markdown Transcription node for your preferred structure

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.noOp","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.splitInBatches","n8n-nodes-base.noOp","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.wait","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.convertToFile","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.sort","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.googleDrive","n8n-nodes-base.set","n8n-nodes-base.convertToFile","n8n-nodes-base.googleDrive","n8n-nodes-base.splitOut","n8n-nodes-base.googleTasks","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive"]

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metadata_json:
  {"categories":["automation","integration","data processing","AI","productivity"],"complexity":"medium","use_cases":["Automatically convert voice memo transcripts into daily Markdown journals","Extract actionable tasks and events from conversations","Archive transcripts and journals to Google Drive","Sync action items to Google Tasks (or other todo apps)","Build a 'second brain' memory workflow with minimal manual entry"],"estimated_setup_minutes":30,"required_services":["OMI pendant or any device that can POST transcript summaries to a webhook","n8n (self-hosted or cloud) with webhook endpoint","Google Drive (for storing transcripts and journals)","Google Tasks (for syncing action items)","Google Gemini or OpenAI (for AI journal generation)"],"key_features":["Receives POST data from OMI via webhook","Parses structured summaries, tasks, events, and raw transcripts","Converts transcripts into Markdown with metadata (emoji, category, overview)","Uses Gemini/AI Agent to generate high-quality journal entries","Extracts and creates Google Tasks for action items automatically"],"target_audience":["OMI pendant users","Creators and content producers","Productivity enthusiasts and 'second brain' builders"]}


name: Paginate Shopify Products with GraphQL Cursor-based Navigation
author_name: Richard Uren
author_username: elricho
categories: []
created_at: 2025-07-04T00:41:44.047Z
updated_at: 2025-07-04T00:41:44.047Z
url: https://n8n.io/workflows/5663
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:34
description:
  Shopify GraphQL cursor loop

  Many Shopify GraphQL queries have the ability to return a cursor which you can loop over, however the N8N GraphQL node does not natively have the ability to fetch pages.  

  This simple 3 node workflow displays how to setup a cursor to fetch all items in a collection. 

  Note : The pageSize in the "Shopify, products" node is set to 5 to illustrate how querying by cursor works. In production set this to a much larger value. 

  Also, Update the Endpoint in GraphQL node to reflect your Shopify store.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.graphql","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.wait"]

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metadata_json:
  {"categories":["integration","e-commerce","data processing","automation"],"complexity":"simple","use_cases":["Retrieve all products from a Shopify collection","Export or sync product catalogs","Backfill product data for analytics or migrations","Demonstrate GraphQL cursor pagination mechanics"],"estimated_setup_minutes":10,"required_services":["Shopify GraphQL API","n8n"],"key_features":["Cursor-based GraphQL pagination to iterate over all items","Configurable pageSize to control page payload","Loop control using an IF node to detect end cursor","Example GraphQL node endpoint that must be updated for your store","Minimal 3-node pattern illustrating pagination logic"],"target_audience":["n8n users","developers/engineers integrating with Shopify","E-commerce managers doing bulk exports or syncs"]}


name: Bulk Create Shopify Products with Inventory Management from Google Sheets
author_name: Richard Uren
author_username: elricho
categories: []
created_at: 2025-07-04T00:44:26.296Z
updated_at: 2025-07-04T00:44:26.296Z
url: https://n8n.io/workflows/5664
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Create Products in Shopify from a Google Sheet

  This workflow creates products in your Shopify store from a google sheet. It also enables inventory tracking and sets the quantity of an inventory item at your store's default location. 

  This is a great way to get test data into test or staging stores to try out apps, update templates or try out new designs. 

  This Automation will only import new products. It will skip existing products if the slug matches an existing product's handle (Shopify's term for a slug).
  Setup Notes

  The Google Sheet has the following columns :
  title - free text
  description - free text
  company - free text
  category - free text
  status - ACTIVE, DRAFT or ARCHIVE
  slug - used in the product url, text with no spaces, can also use hyphen.
  price - sale price of the products
  compare_at_price - compare at price for products
  sku - unique code for each product
  stock_on_hand - quantity of this item available for purchase.

  Use those labels in the first row of your sheet and N8N will create one object per row with the column names as object fields. 

  Update GraphQL nodes with your Shopify store URL

  1) Replace the URL in all GraphQL nodes with the URL for your Shopify store. 
  2) These GraphQL requests all use the Shopify 2025-04 GraphQL Admin API. 


  This flow is updated to use Airtable at Sync Products between Airtable and Shopify with Inventory Management

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.graphql","n8n-nodes-base.if","n8n-nodes-base.graphql","n8n-nodes-base.splitInBatches","n8n-nodes-base.graphql","n8n-nodes-base.graphql","n8n-nodes-base.graphql","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["integration","automation","data processing","e-commerce","inventory management"],"complexity":"medium","use_cases":["Bulk import products into a Shopify store from a spreadsheet","Populate test or staging stores with sample product data","Sync product records from a Google Sheet (or Airtable) to Shopify","Enable inventory tracking and set stock levels at default location","Skip existing products by handle to avoid duplicates"],"estimated_setup_minutes":20,"required_services":["Shopify Admin GraphQL API (Shopify store + API access token)","Google Sheets","n8n","Airtable (optional — template has updated variant using Airtable)"],"key_features":["Creates Shopify products from rows in a Google Sheet","Enables inventory tracking and sets inventory quantity at store default location","Skips rows when product handle/slug already exists","Uses Shopify 2025-04 GraphQL Admin API","Batch processing (splitInBatches) and conditional logic to handle duplicates/errors"],"target_audience":["e-commerce managers","developers / integrators","QA and staging teams needing test data for stores/ apps testing"]}


name: Book Cal.com Meetings from ElevenLabs Voice Agent Conversations
author_name: Eric
author_username: automation-wizard
categories: []
created_at: 2025-07-04T02:31:20.743Z
updated_at: 2025-07-04T02:31:20.743Z
url: https://n8n.io/workflows/5665
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  This is a specific use case. The ElevenLabs guide for Cal.com bookings is comprehensive but I was having trouble with the booking API request. So I built a simple workflow to validate the request and handle the booking creation.

  Who's this for?
  You have an ElevenLabs voice agent (or other external service) booking meetings in your Cal.com account and you want more control over the book_meeting tool called by the voice agent.

  How's it work?
  Request is received by the webhook trigger node
  Request sent from ElevenLabs voice agent, or other source
  Request body contains contact info for the user with whom a meeting will be booked in Cal.com
  Workflow validates input data for required fields in Cal.com
  If validation fails, a 400 bad request response is returned
  If valid, meeting is booked in Cal.com api

  How do I use this?
  Create a custom tool in the ElevenLabs agent setup, and connect it to the webhook trigger in this workflow. Add authorization for security.

  Instruct your voice agent to call this tool after it has collected the required information from the user.

  Expected input structure
  Note: Modify this according to your needs, but be sure to reflect your changes in all following nodes. Requirements here depend on required fields in your Cal.com event type. If you have multiple event types in Cal.com with varying required fields, you'll need to handle this in this workflow, and provide appropriate instructions in your *voice agent prompt*.
  "body": {
    "attendee_name": "Some Guy",
    "start": "2025-07-07T13:30:00Z",
    "attendee_phone": "+12125551234",
    "attendee_timezone": "America/New_York",
    "eventTypeId": 123456,
    "attendee_email": "someguy@example.com",
    "attendee_company": "Example Inc",
    "notes": "Discovery call to find synergies."
  }

  Modifications
  Note: ElevenLabs doesn't handle webhook response headers or body, and only recognizes the response code. In other words, if the workflow responds with 400 Bad request that's the only info the voice agent gets back; it doesn't get back any details, eg. "User email still needed".

  You can modify the structure of the expected webhook request body, and then you should reflect that structure change in all following nodes in the workflow. Ie. if you change attendee_name to attendeeFirstName and attendeeLastName then you need to make this change in the following nodes that use these properties. You can also require or make optional other user data for the Cal.com event type which would reduce or increase the data the voice agent must collect from the user.

  You can modify the authorization of this webhook to meet your security needs. ElevenLabs has some limitations and you should be mindful of those, but it also offers a secret feature with proves useful.

  An improvement to this workflow could include a GET request to a CRM or other db to get info on the user interacting with the voice agent. This could reduce some of the data collection needed from the voice agent, like if you already have the user's email address, for example. I believe you can also get the user's phone number if the voice agent is set up on a dial-in interface, so then the agent wouldn't need to ask for it. This all depends on your use case.

  A savvy step might be prompting the voice agent to get an email, and using the email in this workflow to pull enrichment data from Apollo.io or similar ;-)

nodes_used:
  ["n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.switch","n8n-nodes-base.webhook","n8n-nodes-base.httpRequest"]

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metadata_json:
  {"categories":["integration","automation","scheduling","voice assistant"],"complexity":"medium","use_cases":["Book Cal.com meetings from voice-agent conversations","Validate and sanitize incoming booking data","Expose a secure webhook for third‑party tools (ElevenLabs)","Return proper HTTP status for agent to handle success/failure","Optional enrichment from CRM before booking"],"estimated_setup_minutes":30,"required_services":["Cal.com API","ElevenLabs (or other voice agent)","n8n (workflow host)","Optional: CRM/enrichment API (e.g., Apollo.io)"],"key_features":["Webhook trigger to receive booking requests from a voice agent","Request-body validation with switch node and 400 responses on failure","Creates meeting via Cal.com API using eventTypeId and attendee details","Supports timezone and basic contact fields mapping (email, phone, name, company, notes)","Simple authable webhook for security and easy integration into ElevenLabs custom tool"],"target_audience":["Developers integrating voice agents with calendaring","SaaS/product teams automating booking flows","Sales/Customer success teams using voice agents to schedule meetings rapidly"]}


name: Transform Text into AI Videos with Google Veo3, Leonardo.ai and Claude 4
author_name: Alex Kim
author_username: alexk1919
categories: []
created_at: 2025-07-04T04:42:17.945Z
updated_at: 2025-07-04T04:42:17.945Z
url: https://n8n.io/workflows/5666
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  🎬 Google Veo 3 Prompt and Video Generator via Leonardo.ai + Claude 4

  Transform text descriptions into cinematic videos using Google's Veo 3 model through Leonardo.ai's platform!

  🚀 What This Workflow Does

  This advanced automation pipeline takes your creative ideas and turns them into professional-quality videos using Google's powerful Veo 3 model (accessed via Leonardo.ai), enhanced by Claude 4's sophisticated prompt engineering.

  ✨ Key Features

  🤖 AI-Powered Prompt Enhancement**: Uses Claude 4 Sonnet with Wikipedia integration to craft optimal Google Veo 3 prompts
  🎥 Professional Video Generation**: Leverages Google's Veo 3 model through Leonardo.ai for high-quality text-to-video conversion  
  ☁️ Automatic Cloud Storage**: Videos are automatically saved to your Google Drive
  📋 Structured Prompting**: Follows Google Veo3 best practices with 8 essential elements (Subject, Context, Action, Style, Camera Motion, Composition, Ambiance, Audio)
  ⚡ Hands-Off Processing**: Set it and forget it - the workflow handles the entire pipeline

  🔧 How It Works

  Input Your Concept - Describe your video idea in the "Video Context" node
  AI Enhancement - Claude 4 transforms your description into a cinematic Google Veo 3 prompt using advanced techniques
  Video Generation - Google's Veo 3 model (via Leonardo.ai) creates your video (720p resolution, ~8 seconds)
  Smart Waiting - 4-minute processing buffer ensures completion
  Auto-Download - Retrieves the finished video from Leonardo's servers
  Cloud Storage - Uploads directly to your Google Drive folder

  💡 Perfect For

  Content Creators** looking to automate video production
  Marketing Teams** needing quick promotional videos
  Educators** creating engaging visual content
  Social Media Managers** generating scroll-stopping content
  Creative Professionals** exploring AI-assisted filmmaking

  📋 Requirements

  Leonardo AI account with API access
  Anthropic API key (Claude 4 Sonnet)
  Google Drive integration
  N8N instance (cloud or self-hosted)

  👨‍💻 About the Creator

  Created by: AlexK1919 - AI-Native Workflow Automation Architect, n8n Ambassador and Verified Partner, Founder @ WotAI

  If you'd like to review more Google Veo 3 Prompts organized by business category, check out over 9,000+ free, pre-made prompts at: Google Veo 3 Prompts

  📄 License

  This workflow is available under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. You are free to use, adapt, and share this workflow for non-commercial purposes under the terms of this license.

  Full license details: https://creativecommons.org/licenses/by-nc-sa/4.0/

  🎯 Example Output

  Input: "Star Wars stormtrooper digging for uranium in desert, saying something funny"

  The AI generates a structured prompt with:
  Subject**: Detailed character description
  Context**: Desert environment specifics  
  Action**: Dynamic digging movements
  Style**: Cinematic vlog aesthetic
  Camera**: Appropriate angles and movement
  Audio**: Dialogue, sound effects, and music

  ⚙️ Setup Notes

  Character Limit**: Prompts are optimized for Leonardo's 1,500 character API limit
  Processing Time**: Allow 4+ minutes for Google Veo3 video generation
  Quality**: 720p resolution with native audio generation
  Consistency**: Uses advanced Google Veo3 prompting for reliable results

  🔄 Customization Options

  Modify the prompt engineering system message for different styles
  Adjust video resolution and model parameters
  Change storage destination (Google Drive folder)
  Add post-processing steps or notifications

  📈 Why This Workflow Rocks

  Unlike simple text-to-video tools, this workflow:
  Intelligently enhances** your prompts using AI for Google Veo 3
  Follows industry best practices** for Google Veo3 prompting
  Automates the entire pipeline** from idea to stored video
  Leverages multiple AI models** for superior results
  Handles technical details** like API limits and timing

  🚨 Pro Tips

  Be specific in your initial context - detail creates better videos
  The workflow includes comprehensive Google Veo3 prompting guidelines
  Videos are typically 5-8 seconds - plan accordingly for longer content
  Experiment with different styles and camera movements optimized for Veo 3
  The AI can access Wikipedia for factual enhancement

  Ready to revolutionize your video creation process? 

  Import this workflow and start generating professional videos with just a text description! Perfect for anyone looking to harness the power of AI for content creation.

  Tags: #veo3 #GoogleVeo3 #AI #VideoGeneration #Leonardo #Claude #Automation #ContentCreation #GoogleAI

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatAnthropic","n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWikipedia","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","AI-generated content","video production","integration"],"complexity":"complex","use_cases":["Automated text-to-video production from short descriptions","Rapid creation of promotional/social media videos (5–8s)","Generating educational/illustrative visual content","Prompt engineering and testing for Google Veo 3","Batch or hands-off video generation and cloud archival"],"estimated_setup_minutes":20,"required_services":["Leonardo.ai account with API access (Google Veo 3 model)","Anthropic API key (Claude 4)","Google Drive account/integration","n8n instance (cloud or self-hosted)","Wikipedia access (optional, used for factual enhancement)"],"key_features":["Claude 4 prompt enhancement (Sonnet) with Wikipedia integration","Text-to-video generation using Google Veo 3 via Leonardo.ai","Structured prompting following 8 Veo3 elements (Subject, Context, Action, Style, Camera Motion, Composition, Ambiance, Audio)","Automatic wait/retrieve flow and auto-download of finished videos","Automatic upload to Google Drive for cloud storage and archival and configurable storage destination/sample rate/resolution (720p)"],"target_audience":["Content creators","Marketing teams","Social media managers and agencies”，“Educators and instructional designers”,"]}


name: Track Top YouTube Videos by View Count with Google Sheets
author_name: Taiki
author_username: taiki
categories: []
created_at: 2025-07-04T04:51:14.579Z
updated_at: 2025-07-04T04:51:14.579Z
url: https://n8n.io/workflows/5668
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:34
description:
  Workflow Setup Guide

  This workflow collects the most-viewed videos from specified YouTube channels and saves the data to a Google Sheet. Follow these steps to set it up:

  1. Credentials Setup

  Google Sheets:** You need to have a Google Sheets credential configured in your n8n instance. If you don't have one, go to the 'Credentials' section in n8n and add a new credential for Google Sheets.
  YouTube API Key:** You need a YouTube Data API v3 key.
      Go to the Google Cloud Console.
      Create a new project or select an existing one.
      Go to 'APIs & Services' &gt; 'Library' and enable the YouTube Data API v3.
      Go to 'APIs & Services' &gt; 'Credentials', click 'Create Credentials', and choose 'API key'.
      Copy the generated API key.

  2. Google Sheet Setup

  You will need one Google Sheet with two separate sheets (tabs) inside it.

  Input Sheet
  Use Template
  This sheet provides the list of YouTube channels to process.
  Required Columns:** Create a sheet with the following two columns:
      ChannelID: The ID of the YouTube channel (e.g., T7M3PpjBZzw).
      video_num_to_get: The number of top videos to retrieve for that channel (e.g., 5).

  Output Sheet
  This sheet is where the results will be saved.
  Required Columns:** The workflow will automatically append data to the following columns. You can create them beforehand or let the workflow do it.
      channelName
      title
      videoId
      videoLink

  3. Node Configuration

  Read Channel Info from Sheet:**
      Select your Google Sheets credential.
      Enter your Spreadsheet ID.
      Enter the name of your Input Sheet.
  Fetch Most-Viewed Videos via YouTube API:**
      Replace YOUR_YOUTUBE_API_KEY with the API key you generated in Step 1.
  Append Video Details to Sheet:**
      Select your Google Sheets credential.
      Enter your Spreadsheet ID (the same one as before).
      Enter the name of your Output Sheet.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.splitOut","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.splitOut","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","data processing","social media analytics"],"complexity":"medium","use_cases":["Track top YouTube videos by view count","Monitor channel performance and trends","Generate content reports in Google Sheets","Build datasets for further analysis or dashboards","Automate periodic collection of video metadata"],"estimated_setup_minutes":20,"required_services":["Google Sheets (Google account)","YouTube Data API v3 (API key)","n8n instance"],"key_features":["Reads channel IDs and per-channel video count from an input Google Sheet","Calls YouTube Data API to fetch most-viewed videos","Appends video metadata (channelName, title, videoId, videoLink) to an output Google Sheet","Supports processing multiple channels and configurable number of videos per channel","Uses Google Sheets credentials and a YouTube API key for access"],"target_audience":["social media managers","content creators","digital marketers and growth teams\",\"data analysts\",\"automation engineers\"]}ictures of JSON invalid syntax? Wait remove stray characters. I must ensure JSON valid. I see an issue: in target_audience list one item has an extra quote: "]}


name: Voice-Based Appointment Booking System with ElevenLabs AI and Cal.com
author_name: InfyOm Technologies
author_username: infyom
categories: []
created_at: 2025-07-04T06:06:13.624Z
updated_at: 2025-07-04T06:06:13.624Z
url: https://n8n.io/workflows/5670
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  ✅ What problem does this workflow solve?
  Tired of the back-and-forth involved in scheduling meetings? This workflow lets you offer a seamless, voice-based appointment booking experience. It automatically checks your Cal.com availability and either books a meeting or helps the caller choose another time—powered by ElevenLabs for a human-like voice interaction.

  ⚙️ What does this workflow do?

  Receives an inbound voice call (e.g., from a website or IVR system).
  Uses ElevenLabs to drive the voice interaction with natural, AI-generated speech.
  Checks real-time availability from your Cal.com calendar.
  Books a meeting if a slot is available.
  If not, asks the user to suggest a new time and checks availability again.
  Confirms the appointment with a verbal response and optional email or SMS.

  🔧 Setup

  🧠 ElevenLabs Custom Tools Setup

  Add two tools in Custom Tools in ElevenLabs with the following details.

  Name: bookSlot

  Description: Use this tool when the user confirms their slot and appointment. When you have the proper name and email of theirs. 

  POST: {n8n_webhook_url}

  Name: checkAvailableSlot

  Description: Use this slot to check Available slots in our calendar.

  POST: {n8n_webhook_url}

  🗣 ElevenLabs Prompt Configuration

  First Message:
  Thanks for calling InfyOm Technologies. How can I help you?

  Use the following System Prompt:

  1. Personality
  You are a clear, helpful, and respectful assistant focused solely on booking appointments for clients.
  Identity**: A virtual appointment scheduler.
  Core Traits**: Polite, efficient, conversational, respectful.
  Role**: Guide users through choosing a time, checking availability, and finalizing the booking.

  2. Tone
  Your tone is polite, professional, and engaging—friendly enough to feel human, but focused enough to stay on task.
  Use conversational cues like “Okay,” “Got it,” “Sounds good,” etc.  
  Maintain a warm but efficient pace.  
  Speak clearly and respectfully at all times.  
  Ensure the conversation is on both topics.

  3. Goal
  Your task is to book an appointment for the client.

  Step-by-step Conversation Flow
  Greeting & Purpose
     Greet politely and state the purpose.
     Example: “Hi! I’m here to help you book an appointment.”
  Request Preferred Time
     Ask: “Can you please tell me your preferred time slot for the appointment?”
     Understand the user's date, and if it is not clear, then ask for the full date with month and year.
  Check Availability
     Use the checkAvailableSlot tool with the user’s preferred time.
     If the slot is available:
       Confirm with the user: “That slot is available. Should I go ahead and book it for you?”
       If the user agrees, → Use bookSlot.
     If the slot is not available:
       Say: “It looks like that time isn’t available... Would you like to look for the same time on the next day?”
  Handle Next-Day Option
     If the user agrees, check availability for the same time on the next day using checkAvailableSlot.
       If available, → confirm and use bookSlot.
       If not, → politely inform and ask for a different time.

  Close the Call
     Confirm the booking if done.
     Example: “Great! Your appointment is booked. Thank you and have a wonderful day!”

  4. Guardrails
  Do not** discuss anything unrelated to appointment booking.
  If the user asks for something outside your scope:
    Say: “I’m only here to help with appointment bookings. For other questions, please contact our support team.”
  Never speculate about unavailable data or functions.
  Never ask for a date format from the User, like Say date in Day Month and Year format. If you can't understand the user's date, then say Please speak the full date.

  5. Tools
  You can use the following tools to help book appointments:
  checkAvailableSlot: Use this to check if the user’s requested time is open.
  bookSlot: Use this to confirm the appointment after the user agrees.

  End call
  Always says Thanks for reaching out to us. Have a nice day.

  📅 Cal.com API Setup
  Go to cal.com and generate an API Key.
  Create new Cal API credentials in n8n.
  Set this API Key in the credentials.

  🧠 How it Works

  ☎️ 1. Incoming Call
  An inbound call is received by the system, and the user begins the conversation with your voice AI agent.

  🧏 2. Voice Interaction via ElevenLabs
  The caller is greeted and asked for their preferred appointment time. All conversations are powered by natural AI speech from ElevenLabs.

  🗓 3. Availability Check (Cal.com)
  The requested time is validated against your Cal.com availability:
  ✅ If available, the appointment is booked instantly.
  ❌ If unavailable, the agent informs the caller and asks for another time.

  🔁 4. Retry Loop (If Slot Unavailable)
  If the initial slot is unavailable:
  The agent asks for a new preferred time.
  The process repeats until a valid slot is found or a fallback message is delivered.

  ✅ 5. Appointment Confirmation
  Once booked, the AI confirms the appointment verbally. You may also configure it to send:
  📧 Email confirmations
  📱 SMS reminders (optional)

  👤 Who can use it?

  This is perfect for:
  🧑‍⚕️ Clinics or Therapists
  🧑‍💼 Consultants & Coaches
  🏢 Sales Teams
  🧠 AI-first SaaS Tools

  If your business relies on scheduled meetings and you'd like to automate bookings using a conversational voice experience, this is your go-to no-code solution.

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

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metadata_json:
  {"categories":["automation","integration","voice-based-scheduling"],"complexity":"medium","use_cases":["Voice-driven appointment booking","IVR-to-calendar scheduling","Automating appointment confirmations","Reducing scheduling back-and-forth for customers","Retry flow when requested slot unavailable"],"estimated_setup_minutes":45,"required_services":["ElevenLabs (voice AI & Custom Tools)","Cal.com (scheduling API)","n8n (workflow/orchestration)","Telephony/IVR provider (e.g., Twilio) for inbound calls/webhooks","Optional Email/SMS provider for confirmations/reminders"],"key_features":["Natural, AI-generated voice interaction via ElevenLabs","Real-time availability checks against Cal.com","Automatic booking when a slot is available","Retry loop to propose/check alternate times (next day or new time)","Verbal booking confirmation and optional email/SMS notification via webhooks/HTTP nodes"],"target_audience":["Clinics and therapists","Consultants and coaches","Sales teams and appointment-driven businesses of any size (including SaaS)"]}


name: YouTube to Multilingual Blogs: Convert Videos to SEO-Friendly Google Doc Articles
author_name: Evoort Solutions
author_username: evoortsolutions
categories: []
created_at: 2025-07-04T09:17:44.883Z
updated_at: 2025-07-04T09:17:44.883Z
url: https://n8n.io/workflows/5671
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  🎬 YouTube Video to Blog – Multilingual Blog Generator

  Convert YouTube videos into SEO-friendly blog posts in just seconds using this fully automated n8n workflow. Perfect for content creators, marketers, educators, and bloggers looking to repurpose video content without manual transcription or formatting.

  🔧 What It Does

  📥 Accepts a YouTube video URL and preferred language via a simple form
  🧠 Uses a third-party API to convert the video into a blog-style article
  📄 Automatically inserts the generated content into a Google Docs document

  🌍 Supported Languages

  Supports all major languages, including but not limited to:

  English  
  Hindi  
  French  
  German  
  Gujarati  

  🎯 The workflow is flexible and can generate blog content in any language supported by the API. Just select your language when submitting the form.

  🚀 Benefits

  ⏱️ Time-Saving: Eliminate manual video transcription and formatting  
  🌐 Multilingual: Easily generate blogs in multiple languages  
  📚 Centralized Storage: Store all generated blogs in a single Google Docs file  
  🔧 Customizable: Extend the flow to auto-publish, email, or analyze content  

  🧠 Use Cases

  Repurpose YouTube content into keyword-rich blog posts  
  Generate multilingual content for global reach  
  Convert educational videos into study guides or summaries  
  Create email newsletters or social media posts from video content  

  🛠️ Requirements

  ✅ An n8n instance (self-hosted or cloud)  
  🔑 RapidAPI key for youtube-to-blog.p.rapidapi.com  
  🧾 A Google Docs account with API access  

  🚨 Note: Be sure to update the API key and Google Docs URL with your own credentials before activating the workflow.

  Create your free n8n account and set up the workflow in just a few minutes using the link below:

  👉 Start Automating with n8n

  Save time, stay consistent, and grow your LinkedIn presence effortlessly!

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

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metadata_json:
  {"categories":["automation","integration","content-repurposing","multilingual"],"complexity":"medium","use_cases":["Repurpose YouTube videos into SEO-friendly blog posts","Generate multilingual articles from video content","Create summaries or study guides from educational videos","Produce content for newsletters or social media from videos"],"estimated_setup_minutes":15,"required_services":["n8n instance (self-hosted or cloud)","RapidAPI (youtube-to-blog.p.rapidapi.com) API key","Google account with Google Docs API access (OAuth credentials)"],"key_features":["Accepts YouTube URL and preferred language via form","Uses third-party API to convert video to blog-style article","Automatically creates and inserts content into Google Docs","Supports multiple languages (multilingual generation)","Centralized storage of generated articles in Google Docs file(s)"],"target_audience":["content creators","marketers","bloggers/SEO specialists」、「educators"]}


name: Daily Task Reminder System: Airtable to Slack Automated Notifications
author_name: Baptiste Fort
author_username: baptistefort
categories: []
created_at: 2025-07-04T09:57:59.369Z
updated_at: 2025-07-04T09:57:59.369Z
url: https://n8n.io/workflows/5672
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Still reminding people about their tasks manually every morning?

  Let’s be honest — who wants to start the day chasing teammates about what they need to do?

  What if Slack could do it for you — automatically, at 9 a.m. every day — without missing anything, and without you lifting a finger?



  In this tutorial, you’ll build a simple automation with n8n that checks Airtable for active tasks and sends reminders in Slack, daily.

  Here’s the flow you’ll build:

  Schedule Trigger → Search Records (Airtable) → Send Message (Slack)

  STEP 1 : Set up your Airtable base



  Create a new base called Tasks

  Add a table (for example: Projects, To-Do, or anything relevant)

  Add the following fields:

  | Field    | Type              | Example                                     |
  | -------- | ----------------- | ------------------------------------------- |
  | Title    | Text              | Finalize quote for Client A                 |
  | Assignee | Text              | Baptiste Fort                               |
  | Email    | Email             | claire@email.com |
  | Status   | Single select     | In Progress / Done                          |
  | Due Date | Date (dd/mm/yyyy) | 05/07/2025                                  |

  Add a few sample tasks with the status In Progress so you can test your workflow later.

  STEP 2 Create the trigger in n8n

  In n8n, add a Schedule Trigger node

  Set it to run every day at 9:00 a.m.:

  Trigger interval: Days

  Days Between Triggers: 1

  Trigger at hour: 9

  Trigger at minute: 0

  This is the node that kicks off the workflow every morning.

  STEP 3 : Search for active tasks in Airtable

  This step is all about connecting n8n to your Airtable base and pulling the tasks that are still marked as "In Progress".

  1. Add the Airtable node

  In your n8n workflow, add a node called:

  Airtable → Search Records

  You can find it by typing "airtable" in the node search.

  2. Create your Airtable Personal Access Token



  If you haven’t already created your Airtable token, here’s how:

  🔗 Go to: https://airtable.com/create/tokens

  Then:

  Name your token something like TACHES

  Under Scopes, check:

  ✅ data.records:read

  Under Access, select only the base you want to use (e.g. “Tâches”)

  Click “Save token”

  Copy the personal token

  3. Set up the Airtable credentials in n8n

  In the Airtable node:

  Click on the Credentials field

  Select: Airtable Personal Access Token

  Click Create New

  Paste your token

  Give it a name like: My Airtable Token

  Click Save

  4. Configure the node



  Now fill in the parameters:

  Base: Tâches

  Table: Produits (or Tâches, depending on what you called it)

  Operation: Search

  Filter By Formula:

  {Statut} = "En cours"

  Return All: ✅ Yes (make sure it’s enabled)

  Output Format: Simple

  5. Test the node

  Click “Execute Node”.

  You should now see all tasks with Statut = "En cours" show up in the output (on the right-hand side of your screen), just like in your screenshot.

  STEP 4: Send each task to Slack

  Now that we’ve fetched all the active tasks from Airtable, let’s send them to Slack — one by one — using a loop.

  Add the Slack node
  Drag a new node into your n8n workflow and select:

  Slack → Message

  Name it something like Send Slack Message

  You can find it quickly by typing "Slack" into the node search bar.

  Connect your Slack account
  If you haven't already connected your Slack credentials:

  Go to n8n → Credentials

  Select Slack API

  Click Create new

  Paste your Slack Bot Token (from your Slack App OAuth settings)

  Give it a clear name like Slack Bot n8n

  Choose the workspace and save

  Then, in the Slack node, choose this credential from the dropdown.

  Configure the message
  Set these parameters:

  Operation: Send

  Send Message To: Channel

  Channel: your Slack channel (e.g. #tous-n8n)

  Message Type: Simple Text Message

  Message template
  Paste the following inside the Message Text field:

  Message template



  Paste the following inside the Message Text field: New task for {{ $json.name }}: {{ $json["Titre"] }} 👉 Deadline: {{ $json["Date limite"] }}

  Example output:

  New task for Jeremy: Relancer fournisseur X 👉 Deadline: 2025-07-04

  Test it

  Click Execute Node to verify the message is correctly sent in Slack.

  If the formatting works, you’re ready to run it on schedule 🚀

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.airtable","n8n-nodes-base.slack","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","notifications","task management"],"complexity":"simple","use_cases":["Daily task reminders","Automated team follow-ups","Notify assignees of due tasks","Surface Airtable tasks in Slack"],"estimated_setup_minutes":20,"required_services":["Airtable (Personal Access Token)","Slack (Bot/OAuth Token)","n8n"],"key_features":["Daily schedule trigger at 9:00 AM","Search Airtable records with a filter formula (e.g. Status = In Progress)","Loop over results and send templated Slack messages","Simple text templating with record fields (assignee, title, due date)","Return all matching records option"],"target_audience":["team leads","project managers","operations/ops teams in small-to-medium businesses\",\"n8n users and automation builders"]}


name: Comprehensive SSL Certificate Monitoring with Discord Alerts and Notion Integration
author_name: Tom Cao
author_username: tomcao
categories: []
created_at: 2025-07-04T11:04:11.414Z
updated_at: 2025-07-04T11:04:11.414Z
url: https://n8n.io/workflows/5673
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  🔐 Advanced SSL Health Monitor
  👤 Who is this for?
  This workflow is designed for DevOps engineers, IT administrators, and security professionals who need comprehensive SSL certificate monitoring and health assessment across multiple domains — featuring dual verification and professional reporting without relying on expensive monitoring services.

  🧩 What It Does
  Daily Trigger runs the workflow every morning for proactive monitoring.
  URL Collection fetches the list of website URLs to monitor from your data source.
  Dual SSL Analysis:
     Free SSL Assessment Script — Get from sysadmin-toolkit on Github 
     SSL-Checker.io API — External verification for cross-validation
  Comprehensive Health Check:
     Certificate expiration monitoring (customizable threshold)
     SSL configuration security assessment
     Protocol support analysis (TLS 1.3, 1.2, deprecated protocols)
     Cipher suite strength evaluation
     Vulnerability scanning (POODLE, BEAST, etc.)
     Compliance checking (PCI DSS, NIST, FIPS)
  Smart Alert System sends Discord notifications when:
     Certificates expire within threshold (default: 30 days)
     SSL configuration issues detected (weak ciphers, deprecated protocols)
     Security vulnerabilities found
     Compliance standards not met
     Grade drops below acceptable level (configurable)

  🎯 Key Features
  🔄 Dual Verification**: Cross-checks results between internal scanner and external API
  📊 SSL Labs-Style Grading**: A+ to F rating system with detailed analysis
  🛡️ Security Assessment**: Vulnerability detection and compliance checking
  📱 Discord Integration**: Rich embed notifications with color-coded alerts
  ⚙️ Setup Instructions
  Data Source:  
     Configure your URL source from Notion
     Ensure it contains a URL column with domains to monitor
  Credentials:  
     Set up Discord webhook for alert notifications
     Configure any required API credentials for data sources
  Customize Thresholds:  
     Expiration Alert: Days before expiry (default: 30 days)
     Grade Threshold: Minimum acceptable SSL grade (default: B)
     Alert Severity: Choose which issues trigger notifications
  Advanced Configuration:
     Modify vulnerability checks based on your security requirements
     Adjust compliance standards for your industry needs
     Customize Discord message formatting and alert channels

  🧠 Technical Notes
  Dual-Check Reliability**: Combines custom Bubobot scanner with ssl-checker.io for maximum accuracy
  No Vendor Lock-in**: Uses free public APIs and open-source tools
  Professional Reporting**: Generates SSL Labs-quality assessments
  Security-First Approach**: Comprehensive vulnerability and compliance checking
  Flexible Alerting**: Discord integration with rich formatting and conditional logic


  This workflow provide a comprehensive SSL security monitoring solution that rivals enterprise-grade tools while remaining completely open-source and free.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.ssh","n8n-nodes-base.discord","n8n-nodes-base.discord","n8n-nodes-base.notion","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["security monitoring","infrastructure monitoring","alerting","integration"],"complexity":"complex","use_cases":["SSL certificate expiration monitoring and alerting","Cross-validated SSL health checks (internal scanner + external API)","Protocol, cipher and vulnerability assessment for compliance","Automated incident notifications via Discord","Centralized URL management via Notion and scheduled scans"],"estimated_setup_minutes":60,"required_services":["Notion (URL data source)","Discord (webhook for alerts)","ssl-checker.io API (external verification)","GitHub / sysadmin-toolkit (internal SSL assessment script)","Host or VM reachable by SSH to run internal scanner"],"key_features":["Daily scheduled scans with customizable trigger","Dual verification using internal scanner and external API","Certificate expiration alerts with configurable threshold","Protocol and cipher suite analysis (TLS 1.3, 1.2, deprecated)","Vulnerability detection (POODLE, BEAST, etc.) and compliance checks (PCI, NIST, FIPS option-based checks)"],"target_audience":["DevOps engineers","IT administrators","Security engineers / analysts / SREs"]}


name: Generate Trend-Based Marketing Videos with Seedance AI, Perplexity, and GPT
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2025-07-04T11:17:39.230Z
updated_at: 2025-07-04T11:17:39.230Z
url: https://n8n.io/workflows/5674
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  🎬 Seedance Video Marketing AI Agent
  Description:
  This AI-powered marketing automation workflow takes a user prompt, researches trending topics, generates a compelling short-form video prompt, and sends it to the Seedance API via Wavespeed to create a ready-to-use video ad — all from a single Telegram message.

  Built for marketers, founders, and content creators who want to turn trend-based ideas into visual video content without touching a video editor.

  For the step-by-step video tutorial guide on how to build this workflow, check out:
  https://youtu.be/2oZ5NhosKgo

  🤖 How It Works:
  📲 Telegram Trigger
   Kick off the workflow by messaging a short prompt (e.g., “Create a 5-second IG ad for my new perfume”) via Telegram.

  📈 Trend Research with Perplexity AI (Sonar Pro)
   An AI agent scans the latest 14-day trends and selects the top marketing angle based on the product/niche input.

  🧠 Video Prompt Engineer (ChatGPT)
   Crafts a concise, visually rich video generation prompt — optimized for Seedance — based on the trend insight and product.

  🎥 Video Generation (Wavespeed + Seedance API)
   Sends the AI-generated prompt to Seedance via Wavespeed to generate a 5-second short-form video ad.

  🔁 Status Loop & Response
   The workflow checks if the video is ready. Once complete, it sends the final video output URL back to you in Telegram.

  🔧 Tools Used:
  Telegram Trigger & Response

  Perplexity AI (Sonar Pro)

  OpenAI

  Seedance API (via Wavespeed)

  n8n HTTP Request, Wait, and Loop nodes

  💡 Use Cases:
  Auto-generate TikTok/Instagram ads from current trends

  Scale creative content generation with zero design work

  Plug into your marketing chatbot or campaign assistant

  Use trends as visual inspiration for ad creatives

  If you like the build, check out my channel and consider subscribing: https://www.youtube.com/@Automatewithmarc

nodes_used:
  ["n8n-nodes-base.telegramTrigger","n8n-nodes-base.perplexity","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","marketing","integration","content creation"],"complexity":"complex","use_cases":["Auto-generate short-form ads (TikTok/Instagram) from trends","Scale creative content generation without manual editing","Integrate trend-driven video creation into chatbots/campaign workflows","Use trend insights as inspiration for ad creatives"],"estimated_setup_minutes":45,"required_services":["n8n self-hosted (community nodes)","Telegram Bot API","Perplexity AI (Sonar Pro)","OpenAI (ChatGPT)","Wavespeed (to call Seedance API)","Seedance API"],"key_features":["Trigger via single Telegram message","14-day trend research with Perplexity AI","AI prompt engineering (ChatGPT) to create video-generation prompts","Send prompts to Seedance via Wavespeed to generate short-form video ads","Polling/loop to check generation status and return final video URL in Telegram"],"target_audience":["marketers","founders","content creators/social media managers','growth teams','digital agencies"]}


