# templates

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: 2025-12-24 13:02:45
description:
  🎯 What This Does
  This n8n workflow is a comprehensive crypto intelligence system that monitors multiple data sources simultaneously to identify alpha opportunities, whale movements, and emerging trends before they become mainstream. 

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

  Installment payment plan available on the link
  ⚡ Key Features

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

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

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

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

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

  📨 Smart Telegram Alerts: Beautifully formatted alerts with actionable insights

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

  🚀 What Makes This Special

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

  📈 Real-World Use Cases
  For Traders

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

  For Researchers

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

  For Portfolio Managers

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

  🛠️ Setup Requirements
  Required (Free Tier Available)

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

  Optional Upgrades

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

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

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

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

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

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

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

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

  2️⃣ Customize Configuration

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

  3️⃣ Test & Deploy

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

  🎯 Who This Is For
  ✅ Perfect For:

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

  ❌ Not Ideal For:

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

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

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

  🆘 Support & Community
  Support is available on the Discord channel

  ✅ Complete setup documentation
  ✅ Troubleshooting guide
  ✅ Configuration examples

  📚Community Resources

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

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

  N8N Link to get you started

nodes_used:
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name: Transform Images into AI Videos with MiniMax Hailuo 02. Upload to YouTube/TikTok
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-07-03T13:43:09.677Z
updated_at: 2025-07-03T13:43:09.677Z
url: https://n8n.io/workflows/5633
scraped_at: 2025-12-24 13:02:44
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:
  [encoded data, 6344 characters]


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: 2025-12-24 13:02:42
description:
  Platform: n8n (Telegram Bot Integration)
  Purpose: Let users fetch top meme coin prices in real-time using a simple /memecoin Telegram command 
   How It Works (Logic Breakdown)
  This flow listens for a Telegram command and fetches data from the CoinGecko API to respond with live memecoin prices.

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

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

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

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

  If true ➝ continue to fetch data from CoinGecko.

  If false ➝ nothing happens.

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

  Fetches top 5 meme tokens by market cap.

  Data includes:

  Name

  Symbol

  Current price (USD)

  Coin ID (for URL linking)

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

  Builds a clean message like:

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

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

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

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

  🤖 Bot fetches meme coin prices

  📬 Bot replies with live prices + links

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

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name: EPA Environmental Compliance Data API for AI Agents with MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-07-03T16:19:25.557Z
updated_at: 2025-07-03T16:19:25.557Z
url: https://n8n.io/workflows/5636
scraped_at: 2025-12-24 13:02:46
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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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: 2025-12-24 13:02:46
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:
  ["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","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool"]

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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: 2025-12-24 13:02:46
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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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: 2025-12-24 13:02:45
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"]

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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: 2025-12-24 13:02:46
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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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: 2025-12-24 13:02:46
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:
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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: 2025-12-24 13:02:45
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:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote"]

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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: 2025-12-24 13:02:46
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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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: 2025-12-24 13:02:42
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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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: 2025-12-24 13:02:44
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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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: 2025-12-24 13:02:46
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:
[cell repeats an earlier one in this file: 156 characters]

workflow_json_compressed:
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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: 2025-12-24 13:02:46
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:
  [encoded data, 5332 characters]


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: 2025-12-24 13:02:46
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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


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: 2025-12-24 13:02:46
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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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: 2025-12-24 13:02:45
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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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: 2025-12-24 13:02:41
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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name: Website Content Scraper & SEO Keyword Extractor with GPT-5-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: 2025-12-24 13:02:42
description:
  This workflow allows you to scrape website content, clean the HTML, extract structured information using GPT-5-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-5-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-5-mini):
  Extracts topic-wise information from the cleaned website content.

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

  ✅ Keyword Extractor (AI Agent + GPT-5-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-5-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-5-mini)   |
  | Code1        | Text Cleanup Formatter          |
  | Split Out2   | Final Text Splitter             |
  | AI Agent     | Keyword Extractor (GPT-5-mini) |
  | Airtable     | Airtable Data Upsert            |
  | Wait1        | Delay Before Merge              |
  | Merge        | Combine Data for Airtable       |

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.formTrigger","n8n-nodes-base.wait","n8n-nodes-base.splitOut","n8n-nodes-base.splitOut","n8n-nodes-base.airtable","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code"]

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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: 2025-12-24 13:02:43
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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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: 2025-12-24 13:02:44
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:
  ["n8n-nodes-base.cron","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitInBatches"]

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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: 2025-12-24 13:02:43
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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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: 2025-12-24 13:02:44
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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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: 2025-12-24 13:02:43
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:
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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: 2025-12-24 13:02:42
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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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: 2025-12-24 13:02:42
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:
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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: 2025-12-24 13:02:43
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.

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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: 2025-12-24 13:02:41
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:
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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: 2025-12-24 13:02:42
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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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: 2025-12-24 13:02:44
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 🚀

  Want to scale your workflows? Visit 0vni – Agence automatisation.

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

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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: 2025-12-24 13:02:41
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:
  [encoded data, 8436 characters]


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: 2025-12-24 13:02:41
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:
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name: Transform Markdown Content into Structured Notion Blocks
author_name: Tom
author_username: mutedjam
categories: []
created_at: 2025-07-04T15:07:06.141Z
updated_at: 2025-07-04T15:07:06.141Z
url: https://n8n.io/workflows/5675
scraped_at: 2025-12-24 13:02:41
description:
  Markdown to Notion Blocks Converter

  Transform markdown-formatted text into properly structured Notion page content with this comprehensive workflow.

  Overview
  This workflow automatically converts markdown text into Notion's block format and inserts it directly into a Notion page. Perfect for content creators, documentation teams, and anyone who needs to migrate markdown content to Notion.

  Features
  Complete Markdown Support**: Handles headers (H1-H4), paragraphs, lists, quotes, code blocks, and horizontal rules
  Rich Text Formatting**: Preserves bold, italic, and link formatting
  Smart Text Processing**: Generates plain text excerpts and maintains original content structure
  Direct Notion Integration**: Automatically inserts converted blocks into your specified Notion page
  Batch Processing**: Efficiently handles large content blocks

  What It Does
  Takes markdown-formatted text as input
  Parses and converts it to Notion's block structure
  Handles complex formatting including:
     Headers and subheaders
     Bulleted and numbered lists
     Code blocks with syntax highlighting
     Blockquotes
     Bold and italic text
     Links
     Horizontal dividers
  Uploads the converted content directly to your Notion page

  Use Cases
  Content Migration**: Move existing markdown documentation to Notion
  Automated Publishing**: Convert blog posts or articles from markdown to Notion
  Documentation Workflows**: Streamline technical documentation processes
  Content Syndication**: Publish the same content across multiple platforms

  Requirements
  Notion API credentials
  Target Notion page ID
  Markdown-formatted source content

  Setup
  Configure your Notion API credentials
  Replace the page ID in the HTTP request node with your target Notion page
  Connect your markdown data source (replace the mock data node)
  Execute the workflow

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

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name: Customer Onboarding Automation with HubSpot, Email Sequences and Team Alerts
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-07-04T15:12:39.741Z
updated_at: 2025-07-04T15:12:39.741Z
url: https://n8n.io/workflows/5676
scraped_at: 2025-12-24 13:02:41
description:
  Learn Customer Onboarding Automation with n8n

  ✅ How It Works
  This smart onboarding automation handles new customer signups by:

  Receiving signup data via webhook
  Validating required customer info
  Creating a contact in HubSpot CRM
  Sending a personalized welcome email
  Delivering onboarding documents after 2 hours
  Sending a personal check-in email after 1 day
  Sending a Week 1 success guide after 3 days
  Updating CRM status and notifying the team at each milestone
  It’s designed for professional onboarding, with built-in timing, CRM integration, and smart notifications to improve engagement and retention.

  🛠️ Setup Steps
  Create Webhook
  Add a Webhook node in n8n with POST method — this triggers when a new customer signs up.
  Validate Customer Data
  Add an IF node to check if email and customerName are present.
  Create CRM Contact
  Use a HubSpot node to create a new contact, map fields (e.g., split name into first/last).
  Send Notifications
  Add a Telegram or Slack node to alert your team instantly.
  Send Welcome Email
  Use an Email Send node for a warm welcome, customized with customer details.
  Wait 2 Hours
  Add a Wait node to delay next steps and avoid overwhelming the customer.
  Send Onboarding Documents
  Use another Email Send node to deliver helpful PDFs or guides.
  Wait 1 Day & Send Check-in
  Another Wait node, followed by a personal check-in email using the customer’s name.
  Wait 2 More Days & Send Success Guide
  Deliver Week 1 content via email to reinforce engagement.
  Update CRM & Notify Team
  Use HubSpot to update status and Telegram/Slack to notify your team of completion.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.hubspot","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.hubspot","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.hubspot","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.telegram"]

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name: Extract & Transform HackerNews Data to Google Docs using Gemini 2.0 Flash
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2025-07-04T15:25:11.039Z
updated_at: 2025-07-04T15:25:11.039Z
url: https://n8n.io/workflows/5677
scraped_at: 2025-12-24 13:02:41
description:
  Description
  This workflow automates the process of scraping the latest discussions from HackerNews, transforming raw threads into human readable content using Google Gemini, and exporting the final content into a well-formatted Google Doc.

  Overview
  This n8n workflow is responsible for extracting trending posts from the HackerNews API. It loops through each item, performs HTTP data extraction, utilizes Google Gemini to generate human-readable insights, and then exports the enriched content into Google Docs for distribution, archiving, or content creation.

  Who this workflow is for

  Tech Newsletter Writers**:
  Automate the collection and summarization of trending HackerNews posts for inclusion in weekly or daily newsletters.

  Content Creators & Bloggers**:
  Quickly generate structured summaries and insights from HackerNews threads to use as inspiration or supporting content for blog posts, videos, or social media.

  Startup Founders & Product Builders**:
  Monitor HackerNews for discussions relevant to your niche or competitors, and keep a pulse on the community’s opinions.

  Investors & Analysts**:
  Surface early signals from the tech ecosystem by identifying what’s trending and how the community is reacting.

  Researchers & Students**:
  Analyze popular discussions and emerging trends in technology, programming, and startups—enriched with AI-generated insights.

  Digital Agencies & Consultants**:
  Offer HackerNews monitoring and insight reports as a value-added service to clients interested in the tech space.

  Tools Used
  n8n**: The core automation engine that manages the trigger, transformation, and export.

  HackerNews API**: Provides access to trending or new HN posts.

  Google Gemini**: Enriches HackerNews content with structured insights and human-like summaries.

  Google Docs**: Automatically creates and updates a document with the enriched content, ready for sharing or publishing.

  How to Install
  Import the Workflow**: Download the .json file and import it into your n8n instance.

  Set Up HackerNews Source**: Choose whether to use the HN API (via HTTP Request node) or RSS Feed node.

  Configure Gemini API**: Add your Google Gemini API key and design the prompt to extract pros/cons, key themes, or insights.

  Set Up Google Docs Integration**: Connect your Google account and configure the Google Docs node to create/update a document.

  Test and Deploy**: Run a test job to ensure data flows correctly and outputs are formatted as expected.

  Use Cases
  Tech Newsletter Authors**: Generate ready-to-use summaries of trending HackerNews threads.

  Startup Founders**: Stay informed on key discussions, product launches, and community feedback.

  Investors & Analysts**: Spot early trends, technical insights, and startup momentum directly from HN.

  Researchers**: Track community reactions to new technologies or frameworks.

  Content Creators**: Use the enriched data to spark blog posts, YouTube scripts, or LinkedIn updates.

  Connect with Me

  Email: ranjancse@gmail.com

  LinkedIn: https://www.linkedin.com/in/ranjan-dailata/

  Get Bright Data: Bright Data (Supports free workflows with a small commission)

  #n8n #automation #hackernews #contentcuration #aiwriting #geminiapi #googlegemini #techtrends #newsletterautomation #googleworkspace #rssautomation #nocode #structureddata #webscraping #contentautomation #hninsights #aiworkflow #googleintegration #webmonitoring #hnnews #aiassistant #gdocs #automationtools #gptlike #geminiwriter

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.hackerNews","n8n-nodes-base.splitInBatches","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleDocs","n8n-nodes-base.googleDocs","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.httpRequest"]

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name: Automate Email Filtering & AI Summarization. 100% free & effective, works 7/24
author_name: ARRE
author_username: arre
categories: []
created_at: 2025-07-04T16:45:16.027Z
updated_at: 2025-07-04T16:45:16.027Z
url: https://n8n.io/workflows/5678
scraped_at: 2025-12-24 13:02:41
description:
  Good to know:
  This workflow automatically processes incoming emails (you can filter them base on your needs) and creates concise AI-powered summaries, then logs them to a Google Sheets spreadsheet for easy tracking and analysis.

  Who is this for?

  ➖Business professionals who receive many emails and need quick summaries
  ➖Customer service teams tracking email communications
  ➖Project managers monitoring email correspondence
  ➖Anyone who wants to automatically organize and summarize their email communications

  What problem is this workflow solving?

  This workflow solves the problem of email overload by automatically reading incoming emails, generating concise summaries using AI, and organizing them in a structured format. It eliminates the need to manually read through every email to understand the key points and maintains a searchable record of communications.

  What this workflow does:

  ✅Monitors your Gmail inbox for new emails
  ✅Filters emails based on specific criteria (sender validation)
  ✅Extracts key information (sender, date, subject, content)
  ✅Uses AI to generate concise summaries of email content
  ✅Automatically logs all data including the AI summary to a Google Sheets spreadsheet

  How it works:

  1️⃣Gmail trigger monitors for new emails at specified intervals
  2️⃣Email data is processed and formatted using JavaScript
  3️⃣A conditional check validates the sender
  4️⃣AI agent (powered by Groq's language model) reads the email content and generates a summary
  5️⃣All information is automatically appended to a Google Sheets document

  How to use:

  Set up Gmail OAuth2 credentials in n8n
  Configure Google Sheets OAuth2 credentials
  Set up Groq API credentials for AI processing
  Create a Google Sheets document and update the document ID
  Customize the sender validation criteria as needed
  Activate the workflow

  Requirements:

  ✅n8n instance (cloud or self-hosted)
  ✅Gmail account with OAuth2 access
  ✅Google Sheets account
  ✅AI API
  ✅Basic understanding of n8n workflow

  Customizing this workflow:

  🟢Modify the Gmail trigger filters to target specific labels or criteria
  🟢Adjust the sender validation logic in the conditional node
  🟢Customize the AI prompt to change summary style or focus
  🟢Add additional data fields to the Google Sheets output
  🟢Change the polling frequency for checking new emails
  🟢Switch to different AI models by replacing the Groq node

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.gmailTrigger","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatGroq","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: RAG Chatbot with Supabase + TogetherAI + Openrouter
author_name: iamvaar
author_username: iamvaar
categories: []
created_at: 2025-07-04T18:23:28.386Z
updated_at: 2025-07-04T18:23:28.386Z
url: https://n8n.io/workflows/5680
scraped_at: 2025-12-24 13:02:41
description:
  ⚠️ RUN the FIRST WORKFLOW ONLY ONCE 
  (as it will convert your content in Embedding format and save it in DB and is ready for the RAG Chat)

  📌 Telegram Trigger

  Type:** telegramTrigger
  Purpose:** Waits for new Telegram messages to trigger the workflow.
  Note:** Currently disabled.

  📄 Content for the Training

  Type:** googleDocs
  Purpose:** Fetches document content from Google Docs using its URL.
  Details:** Uses Service Account authentication.

  ✂️ Splitting into Chunks

  Type:** code
  Purpose:** Splits the fetched document text into smaller chunks (1000 chars each) for processing.
  Logic:** Loops over text and slices it.

  🧠 Embedding Uploaded Document

  Type:** httpRequest
  Purpose:** Calls Together AI embedding API to get vector embeddings for each text chunk.
  Details:** Sends JSON with model name and chunk as input.

  🛢 Save the embedding in DB

  Type:** supabase
  Purpose:** Saves each text chunk and its embedding vector into the Supabase embed table.

  SECOND WORKFLOW EXPLAINATION:

  💬 When chat message received

  Type:** chatTrigger
  Purpose:** Starts the workflow when a user sends a chat message.
  Details:** Sends an initial greeting message to the user.

  🧩 Embend User Message

  Type:** httpRequest
  Purpose:** Generates embedding for the user’s input message.
  Details:** Calls Together AI embeddings API.

  🔍 Search Embeddings

  Type:** httpRequest
  Purpose:** Searches Supabase DB for the top 5 most similar text chunks based on the generated embedding.
  Details:** Calls Supabase RPC function matchembeddings1.

  📦 Aggregate

  Type:** aggregate
  Purpose:** Combines all retrieved text chunks into a single aggregated context for the LLM.

  🧠 Basic LLM Chain

  Type:** chainLlm
  Purpose:** Passes the user's question + aggregated context to the LLM to generate a detailed answer.
  Details:** Contains prompt instructing the LLM to answer only based on context.

  🤖 OpenRouter Chat Model

  Type:** lmChatOpenRouter
  Purpose:** Provides the actual AI language model that processes the prompt.
  Details:** Uses qwen/qwen3-8b:free model via OpenRouter and you can use any of your choice.

nodes_used:
  ["n8n-nodes-base.googleDocs","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.supabase","n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Simulate Debates Between AI Agents Using Mistral to Optimize Answers
author_name: Hybroht
author_username: hybroht
categories: []
created_at: 2025-07-04T19:59:57.854Z
updated_at: 2025-07-04T19:59:57.854Z
url: https://n8n.io/workflows/5682
scraped_at: 2025-12-24 13:02:41
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  AI Arena - Debate of AI Agents to Optimize Answers and Simulate Diverse Scenarios

  Overview 
  Version: 1.0

  The AI Arena Workflow is designed to facilitate a refined answer generation process by enabling a structured debate among multiple AI agents. This workflow allows for diverse perspectives to be considered before arriving at a final output, enhancing the quality and depth of the generated responses.

  ✨ Features
  Multi-Agent Debate Simulation**: Engage multiple AI agents in a debate to generate nuanced responses.
  Configurable Rounds and Agents**: Easily adjust the number of debate rounds and participating agents to fit your needs.
  Contextualized AI Responses**: Each agent operates based on predefined roles and characteristics, ensuring relevant and focused discussions.
  JSON Output**: The final output is structured in JSON format, making it easy to integrate with other systems or workflows.

  👤 Who is this for?
  This workflow is ideal for developers, data scientists, content creators, and businesses looking to leverage AI for decision-making, content generation, or any scenario requiring diverse viewpoints. It is particularly useful for those who need to synthesize information from multiple personalities or perspectives.

  💡 What problem does this solve?
  The workflow addresses the challenge of generating nuanced responses by simulating a debate among AI agents. This approach ensures that multiple perspectives are considered, reducing bias and enhancing the overall quality of the output. Use-Case examples:
  🗓️ Meeting/Interview Simulation
  ✔️ Quality Assurance
  📖 Storywriter Test Environment
  🏛️ Forum/Conference/Symposium Simulation

  🔍 What this workflow does
  The workflow orchestrates a debate among AI agents, allowing them to discuss, critique, and suggest rewrites for a given input based on their roles and predefined characteristics. This collaborative process leads to a more refined and comprehensive final output.

  🔄 Workflow Steps
  Input & Setup: The initial input is provided, and the AI environment is configured with necessary parameters.
  Round Execution: AI agents execute their roles, providing replies and actions based on the input and their individual characteristics.
  Round Results: The results of each round are aggregated, and a summary is created to capture the key points discussed by the agents.
  Continue to Next Round: If more rounds are defined, the process repeats until the specified number of rounds is completed.
  Final Output: The final output is generated based on the agents' discussions and suggestions, providing a cohesive response.

  ⚡ How to Use/Setup
  🔐 Credentials
  Obtain an API key for the Mistral API or another LLM API. This key is necessary for the AI agents to function properly.

  🔧 Configuration
  Set up the workflow in n8n, ensuring all nodes are correctly configured according to the workflow requirements. This includes setting the appropriate input parameters and defining the roles of each AI agent.
  This workflow uses a custom node for Global Variables called 'n8n-nodes-globals.' Alternatively, you can use the 'Edit Field (Set)' node to achieve the same functionality.

  ✏️ Customizing this workflow
  To customize the workflow, adjust the AI agent parameters in the JSON configuration. This includes defining their roles, personalities, and preferences, which will influence how they interact during the debate.
  One of the notes includes a ready-to-use example of how to customize the agents and the environment. You can simply edit it and insert it as your credential in the Global Variables node.

  📌 Example







  An example with both input and final output is provided in a note within the workflow.

  🛠️ Tools Used

  n8n: A workflow automation tool that allows users to connect various applications and services.
  Mistral API: A powerful language model API used for generating AI responses. (You can replace it with any LLM API of your choice)
  Podman: A container management tool that allows users to create, manage, and run containers without requiring a daemon. (It serves as an alternative to Docker for container orchestration.)

  ⚙️ n8n Setup Used
  n8n Version**: 1.100.1
  n8n-nodes-globals**: 1.1.0
  Running n8n via**: Podman 4.3.1
  Operating System**: Linux

  ⚠️ Notes, Assumptions & Warnings

  Ensure that the AI agents are configured with clear roles to maximize the effectiveness of the debate. Each agent's characteristics should align with the overall goals of the workflow.
  The workflow can be adapted for various use cases, including meeting simulations, content generation, and brainstorming sessions.
  This workflow assumes that users have a basic understanding of n8n and JSON configuration.
  This workflow assumes that users have access to the necessary API keys and permissions to utilize the Mistral API or other LLM APIs.
  Ensure that the input provided to the AI agents is clear and concise to avoid confusion in the debate process. Ambiguous inputs may lead to unclear or irrelevant outputs.
  Monitor the output for relevance and accuracy, as AI-generated content may require human oversight to ensure it meets standards and expectations before being used in production.

  ℹ️ About Us

  This workflow was developed by the Hybroht team of AI enthusiasts and developers dedicated to enhancing the capabilities of AI through collaborative processes. Our goal is to create tools that harness the possibilities of AI technology and more.

nodes_used:
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workflow_json_compressed:
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name: One-Click YouTube Shorts Generator with Leonardo AI, GPT and ElevenLabs
author_name: Huzaifa Tahir
author_username: huzaifa404
categories: []
created_at: 2025-07-04T21:25:54.145Z
updated_at: 2025-07-04T21:25:54.145Z
url: https://n8n.io/workflows/5683
scraped_at: 2025-12-24 13:02:41
description:
  🎬 What it does  
  This workflow creates an engaging YouTube Short with a single click — from script to voiceover, to visuals and background music.  
  It combines several AI tools to automate content creation and final video assembly.

  ⚙️ How it works  
  Accepts an input prompt or topic  
  Generates script using GPT  
  Converts script to voiceover using ElevenLabs  
  Generates b-roll style images via Leonardo.Ai  
  Matches background music  
  Assembles a vertical 1080×1920 MP4 video using JSON render config  
  Optionally uploads to YouTube or saves to Cloudinary

  🧰 Setup steps  
  Add your credentials:  
    Leonardo API (image generation)  
    ElevenLabs (voiceover)  
    Cloudinary (upload destination)  
    Any GPT-based text generator

  Drop your audio/music file in the right node  
  Replace API expressions with your own credentials

  &gt; 🟨 Full step-by-step instructions are in sticky notes inside the workflow.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.wait"]

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name: Track WhatsApp Group Message Activity with Airtable Database
author_name: David w/ SimpleGrow
author_username: davidxai
categories: []
created_at: 2025-07-04T23:08:16.287Z
updated_at: 2025-07-04T23:08:16.287Z
url: https://n8n.io/workflows/5684
scraped_at: 2025-12-24 13:02:43
description:
  This n8n workflow tracks user engagement in a specific WhatsApp group by capturing incoming messages via a Whapi webhook. 

  It first filters messages to ensure they come from the correct group, then identifies the message type—text, emoji reaction, voice, or image. The workflow searches for the user in an Airtable database using their WhatsApp ID and increments their message count by one. It updates the Airtable record with the new count and the date of the last interaction. 

  This automated process helps measure user activity and supports engagement initiatives like weekly raffles or rewards. The system is flexible and can be expanded to include more message types or additional actions. 

  Overall, it provides a seamless way to encourage and track user participation in your WhatsApp community.

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.airtable","n8n-nodes-base.code","n8n-nodes-base.airtable","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: WhatsApp Group Onboarding with Automated Welcome Messages & Airtable Point System
author_name: David w/ SimpleGrow
author_username: davidxai
categories: []
created_at: 2025-07-04T23:16:16.482Z
updated_at: 2025-07-04T23:16:16.482Z
url: https://n8n.io/workflows/5686
scraped_at: 2025-12-24 13:02:42
description:
  Receive Webhook Notification
  The workflow starts when a webhook receives a POST request from Whapi, notifying that a new participant has joined a WhatsApp group.

  Filter the Event
  The workflow checks two conditions:

  The event is for the correct WhatsApp group (matching the specific group ID).

  The action type is "add" (meaning a user was added to the group).

  Send Welcome Message
  If both conditions are met, the workflow sends a personalized welcome message to the new participant via Whapi.
  The message explains the group rules and how the user can earn points and participate in weekly raffles.

  Create Airtable Record
  After sending the welcome message, the workflow creates a new record in the Airtable database for the new participant.
  The record includes:

  The participant’s WhatsApp ID

  An initial engagement count of 100 points

  The date of the last interaction (set to today)

  Result
  Every new group member is automatically welcomed and registered in your engagement database with starter points, ready to participate in your group’s activities and rewards.

  This workflow ensures new users are greeted, informed, and instantly included in your engagement tracking system.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Automated US Stock Portfolio Analysis with Telegram, Perplexity AI & PDF Reports
author_name: Solido AI
author_username: solidoai
categories: []
created_at: 2025-07-04T23:24:27.232Z
updated_at: 2025-07-04T23:24:27.232Z
url: https://n8n.io/workflows/5687
scraped_at: 2025-12-24 13:02:41
description:
  System Architecture
  Two integrated N8N workflows providing automated US stock portfolio management through Telegram:

  FLOW 1: Conversational Portfolio Manager
  Telegram bot for interactive portfolio management
  PDF upload & analysis via LlamaIndex Cloud API
  Natural language portfolio updates via GPT-4.1-mini
  Real-time user registration and data management

  FLOW 2: Automated Weekly Reports
  Schedule-triggered weekly analysis (every 7 days)
  Perplexity AI sonar-deep-research for market analysis
  Professional PDF report generation via PDFco
  Automatic Telegram delivery to all registered users

nodes_used:
  ["n8n-nodes-base.html","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.perplexity","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-pdfco.PDFco Api","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.supabase","n8n-nodes-base.telegramTrigger","n8n-nodes-base.supabase","n8n-nodes-base.if","n8n-nodes-base.supabase","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.supabase","@n8n/n8n-nodes-langchain.memoryPostgresChat","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.supabase","n8n-nodes-base.supabase","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.supabase","n8n-nodes-base.supabase","n8n-nodes-base.supabaseTool","n8n-nodes-base.httpRequest","n8n-nodes-base.html","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.perplexity","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-pdfco.PDFco Api","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5032 characters]


name: Send Weekly Engagement Stats & Raffle Updates via WhatsApp using Airtable
author_name: David w/ SimpleGrow
author_username: davidxai
categories: []
created_at: 2025-07-04T23:24:36.938Z
updated_at: 2025-07-04T23:24:36.938Z
url: https://n8n.io/workflows/5688
scraped_at: 2025-12-24 13:02:42
description:
  Scheduled Trigger:
  Every X day at Y pm, the workflow is automatically triggered.

  Fetch User Data:
  The workflow retrieves all user records from the "WhatsApp Engagement Database" in Airtable. Each record contains the user’s WhatsApp ID, current points, and the number of raffle vouchers.

  Personalized Message Preparation:
  For each user, a personalized WhatsApp message is prepared. The message includes:

  The user’s current point total

  The number of raffle vouchers they have for the week

  Encouragement to keep engaging for more chances to win

  Information about the weekly raffle and available prizes

  Send WhatsApp Message:
  The workflow sends this personalized message to each user via the Whapi API, using their WhatsApp ID.

  Result:
  Every active user receives a weekly update about their engagement status, raffle tickets, and a motivational message to encourage further participation. This helps boost engagement and keeps users informed about their progress and chances in the weekly raffle.

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

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name: Extract and Store YouTube Video Comments in Google Sheets
author_name: Agent Circle
author_username: agentcircle
categories: []
created_at: 2025-07-05T03:24:01.617Z
updated_at: 2025-07-05T03:24:01.617Z
url: https://n8n.io/workflows/5690
scraped_at: 2025-12-24 13:02:41
description:
  This n8n template demonstrates how to use the tool to crawl comments from a YouTube video and simply get all the results in a linked Google Sheet.

  Use cases are many: Whether you're a YouTube creator trying to understand your audience, a marketer running sample analysis, a data analyst compiling engagement metrics, or part of a growth team tracking YouTube or social media campaign performance, this workflow helps you extract real, actionable insights from YouTube video comments at scale.

  How It Works
  The workflow starts when you manually click Test Workflow or Execute Workflow in N8N.
  It reads the list of YouTube video URLs from the Video URLs tab in the connected YouTube – Get Video Comments Google Sheet. Only the URLs marked with the Ready status will be processed.
  The tool loops through each video and sends an HTTP request to the YouTube API to fetch comment data.
  Then, it checks whether the request is successful before continuing.
  If comments are found, they are split and processed.
  Each comment is then inserted in the Results tab of the connected YouTube – Get Video Comments Google Sheet.
  Once a URL has been finished, its status in the Video URLs tab of the YouTube – Get Video Comments Google Sheet is updated to Finished.

  How To Use
  Download the workflow package. 
  Import the workflow package into your N8N interface.
  Duplicate the "YouTube - Get Video Comments" Google Sheet template into your Google Sheets account.
  Set up Google Cloud Console credentials in the following nodes in N8N, ensuring enabled access and suitable rights to Google Sheets and YouTube services:
      For Google Sheets access, ensure each node is properly connected to the correct tab in your connected Google Sheet template: 
           Node Google Sheets - Get Video URLs → connected to the Video URLs tab; 
           Node Google Sheets - Insert/Update Comment → connected to the Results tab; 
           Node Google Sheets - Update Status connected to the Video URLs tab.
      For YouTube access: Set up a GET method in Node HTTP Request - Get Comments.
  Open the template in your Google Sheets account. In the tab Video URLs, fill in the video URLs you want to crawl in Column B and update the status for each row in Column A to Ready.
  Return to the N8N interface and click Execute Workflow.
  Check the results in the Results tab of the template - the collected comments will appear there.

  Requirements
  Basic setup in Google Cloud Console (OAuth or API Key method enabled) with enabled access to YouTube and Google Sheets.

  How To Customize
  By default, the workflow is manually triggered in N8N. However, you can automate the process by adding a Google Sheets trigger that monitors new entries in your connected YouTube – Get Video Comments template and starts the workflow automatically.

  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

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name: Generate Personalized Sales Emails with LinkedIn Data & Claude 3.7 via OpenRouter
author_name: Adam Janes
author_username: adamjanes
categories: []
created_at: 2025-07-05T06:27:01.963Z
updated_at: 2025-07-05T06:27:01.963Z
url: https://n8n.io/workflows/5691
scraped_at: 2025-12-24 13:02:41
description:
  How it works
  The automation loads rows from a Google Sheet of leads that you want to contact.
  It makes a Google search via Apify for LinkedIn links based on the First name / Last name / Company.
  Another Apify actor fetches the right LinkedIn profile based on the first profile which is retuned
  The same process is done for the company that the lead works for, giving extra context. If the lead has a current company listed on their LinkedIn, we use that URL to do the lookup, rather than doing a separate Google search.
  A call is made to OpenRouter to get an LLM to generate an email based on a prompt designed to do personalized outreach.
  An email is sent via a Gmail node.

  Set up steps
  Connect your Google Sheets + Gmail accounts to use these APIs.
  Make an account with Apify and enter your credentials.
  Set your details in the "Set My Data" node to customize the workflow to revolve around your company + value proposition. 

  I would recommend changing the prompt in the "Generate Personalized Email" node to match the tone of voice that you want your agent to have. 

  You can change the guidelines to e.g. change whether the agent introduces itself, and give more examples in the style you want to make the output better.

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name: Automatic Lead Export from Fluentform to Google Sheets with Form Categorization
author_name: Khairul Muhtadin
author_username: khmuhtadin
categories: []
created_at: 2025-07-05T09:00:56.355Z
updated_at: 2025-07-05T09:00:56.355Z
url: https://n8n.io/workflows/5692
scraped_at: 2025-12-24 13:02:42
description:
  ❓ What Problem Does It Solve?

  Manual exporting or copying of leads and newsletter signups from web forms to spreadsheets is time-consuming, error-prone, and delays follow-ups or marketing activities. Traditional workflows can lose data due to mistakes or lack of automation.  The Fluentform Export workflow automates the capture and organization of form submissions and newsletter signups into Google Sheets

  💡 Why Use this workflow?

  Save Time:** Automate tedious manual data entry for form leads and newsletter signups
  Avoid Data Loss:** Ensure all submissions are reliably logged with real-time updates
  Organized Data:** Separate sheets for newsletter and contact form data maintain clarity
  Easy Integration:** Works seamlessly with Fluentform submissions and Google Sheets
  Flexible & Scalable:** Quickly adapt to changes in form structure or spreadsheet columns

  ⚡ Who Is This For?

  Marketers & Growth Teams:** Automatically gather leads and newsletter contacts to fuel campaigns
  Small to Medium Businesses:** Reduce overhead from manual data management and errors
  Customer Support Teams:** Keep track of form submissions in a centralized, accessible place
  Website Admins:** Simplify data workflow from Fluentform plugins without coding

  🔧 What This Workflow Does

  ⏱ Trigger:** Listens for incoming POST requests from Fluentform via webhook
  📎 Step 2:** Evaluates if the submission is a newsletter signup or a form based on a specific token
  🔄 Step 3 (Newsletter Path):** Maps email from newsletter submissions and appends/updates Google Sheets "News Letter" tab
  🔄 Step 3 (Form Path):** Extracts full name, email, phone, subject, and message fields and appends/updates the Google Sheets "form" tab
  💌 Step 4:** Sends a JSON success response back to Fluentform confirming receipt

  🔐 Setup Instructions

  Import the provided .json workflow file into your n8n instance
  Set up credentials:
     Google Sheets OAuth2 credential with access to your target spreadsheets
  Customize workflow elements:
     Update Fluentform webhook URL in your Fluentform settings to the n8n webhook URL generated
     Adjust field names or spreadsheet columns if your form structure changes
  Update spreadsheet IDs and sheet names used in the Google Sheets nodes to match your own Sheets
  Test workflow thoroughly with actual Fluentform submissions to verify data flows correctly

  🧩 Pre-Requirements

  Running n8n instance (Cloud or self-hosted)
  Google account with access to Google Sheets and OAuth credentials
  Fluentform installed on your website with ability to set webhook URL
  Target Google Sheets prepared with tabs named "News Letter" and "form" with expected columns

  🧠 Nodes Used

  Webhook (POST - Retrieve Leads)
  If (Form or newsletter?)
  Set (newsletter and form data preparation)
  Google Sheets (Append/update for newsletter and form sheets)
  Respond to Webhook

  📞 Support

  Made by: khaisa Studio  
  Tag: automation, Google Sheets, Fluentform, Leads 
  Category: Marketing  
  Need a custom? Contact Me

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name: Automate Newsletter Creation & Client Delivery with GPT-4O, Google Sheets
author_name: Amit Mehta
author_username: amitswba
categories: []
created_at: 2025-07-05T10:36:50.555Z
updated_at: 2025-07-05T10:36:50.555Z
url: https://n8n.io/workflows/5694
scraped_at: 2025-12-24 13:02:41
description:
  How it Works

  This workflow automates the complete newsletter management process from content creation to client delivery, using Google Sheets, AI content generation, Google Drive, and Gmail.

  Whether you're a content creator, marketing agency, or small business owner, this workflow helps you automate newsletter creation and manage client communications with built-in approval workflows — all triggered from a simple spreadsheet.

  🎯 Use Case

  Ideal for:
  Marketing Teams** streamlining newsletter distribution
  Agencies** managing multiple client newsletters  
  Content Creators** automating regular communications
  Small Businesses** maintaining customer engagement

  Setup Instructions

  1. Upload the Spreadsheet

  File name: Newsletter_Management
  Sheet structure:
    | ID | Topic | Client Name | Client Email | Status | Created Date | Send Date |
  Add newsletter topics and set their Status as Pending

  2. Configure Google Sheets Nodes

  Connect your Google account to:
  Get topic from newsletter sheet
  Pick records to send email to client
  Get Client email address
  Update Status as Generated
  Update status as Sent

  3. Add API Credentials

  OpenAI API Key** → for AI content generation
  Google Drive Access** → for document storage
  Gmail Account** → for sending newsletters and notifications

  4. Activate the Workflow

  Once live, the workflow will:
  Manual Path: Generate newsletter content from pending topics
  Scheduled Path: Send approved newsletters to clients automatically
  Track status updates throughout the entire process
  Store generated content in Google Drive
  Send admin notifications and client emails

  🔁 Workflow Logic

  Main Workflow (Content Generation)
  Trigger: Manual activation for newsletter creation
  Retrieve: Pending topics from Google Sheets
  Validate: Status confirmation (Pending only)
  Generate: AI-powered HTML newsletter content
  Store: Upload to Google Drive
  Notify: Send completion email to admin
  Update: Mark status as "Generated"

  Scheduled Workflow (Client Distribution)
  Trigger: Schedule-based activation
  Retrieve: Approved newsletters from Google Sheets
  Validate: Status confirmation (Approved only)
  Lookup: Client email addresses
  Loop: Process multiple recipients
  Send: Personalized newsletters via Gmail
  Update: Mark status as "Sent"

  🧩 Node Descriptions

  | Node Name | Description |
  |-----------|-------------|
  | When clicking 'Test workflow' | Manual trigger to start newsletter generation |
  | Get topic from newsletter sheet | Retrieves pending newsletter topics from Google Sheets |
  | Validate Status as Pending | Checks whether status is 'Pending' for processing |
  | Create HTML for Newsletter | AI-powered content generation using OpenAI |
  | Prepare Data to create word doc | Formats generated content for document creation |
  | Upload doc to google drive | Stores completed newsletters in Google Drive |
  | Send an email to admin | Notifies administrators of completion |
  | Update Status as Generated | Marks processed items as 'Generated' |
  | Schedule Trigger | Automated trigger for client email distribution |
  | Pick records to send email to client | Retrieves approved newsletters for sending |
  | Validate Status as Approved | Ensures only approved content is processed |
  | Get Client email address | Fetches client contact information |
  | Loop Over Items | Processes multiple newsletter recipients |
  | Send email to client | Delivers personalized newsletters via Gmail |
  | Update status as Sent | Marks newsletters as successfully delivered |

  🛠️ Customization Tips

  Modify AI prompts for different content styles and tones
  Add Slack notifications instead of or alongside Gmail
  Export to different formats (PDF, Word, etc.)
  Schedule multiple sending times for different client segments
  Add approval workflows with webhook triggers
  Integrate with CRM systems for client management

  📒 Suggested Sticky Notes for Workflow

  | Node/Section | Sticky Note Content |
  |--------------|---------------------|
  | Manual Trigger | "Click to start newsletter generation process" |
  | AI Content Generation | "Customize prompts here for different newsletter styles" |
  | Google Drive Upload | "Organized storage - change folder structure as needed" |
  | Gmail Admin Notification | "Update admin email addresses and notification templates" |
  | Schedule Trigger | "Set optimal sending times for your audience" |
  | Client Email Loop | "Handles bulk sending - monitors for delivery errors" |
  | Status Updates | "Maintains audit trail - prevents duplicate processing" |

  📎 Required Files

  | File Name | Purpose |
  |-----------|---------|
  | Newsletter_Management.xlsx | Google Sheet to manage topics, clients, and status tracking |
  | Client_Database.xlsx | Client contact information and preferences |
  | Newsletter_Workflow.json | Main n8n workflow export for this automation |

  🧪 Testing Tips

  Add one test topic with status = Pending and run manual trigger
  Verify AI content generation produces quality HTML
  Check Google Drive upload and folder organization
  Test admin email delivery and formatting
  Add test client with valid email for scheduled workflow
  Monitor workflow logs for API responses and errors
  Confirm status updates occur at each step

  🏷 Suggested Tags & Categories

  #Newsletter
  #EmailMarketing
  #ContentGeneration
  #ClientCommunication
  #Automation
  #GoogleWorkspace
  #AIContent
  #MarketingAutomation
  #WorkflowManagement
  #BusinessProcess

  🔧 Prerequisites

  Google Workspace account (Sheets, Drive, Gmail)
  OpenAI API account with GPT-4 access
  n8n instance (Cloud or self-hosted)
  Basic understanding of Google Sheets and email marketing

  📊 Expected Performance

  Setup Time**: 30-45 minutes
  Monthly Executions**: 100-500 (varies by newsletter frequency)
  Processing Time**: 2-5 minutes per newsletter
  Scalability**: Handles 100+ clients efficiently

  🚨 Important Notes

  Ensure proper Google API permissions are configured
  Monitor OpenAI API usage and rate limits
  Set up error handling for failed email deliveries
  Regularly backup your Google Sheets data
  Test thoroughly before production deployment

  💡 Advanced Features

  Approval Workflows**: Add manual approval steps between generation and sending
  A/B Testing**: Create multiple versions and track performance
  Analytics Integration**: Connect with Google Analytics for tracking
  Multi-language Support**: Generate content in different languages
  Dynamic Personalization**: Use client data for personalized content

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.googleDrive","n8n-nodes-base.gmail","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
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name: Auto-Extract & Distribute Video Clips to Multiple Social Platforms with Klap AI
author_name: Sebastian/OptiLever
author_username: lewxiangang
categories: []
created_at: 2025-07-05T12:55:05.282Z
updated_at: 2025-07-05T12:55:05.282Z
url: https://n8n.io/workflows/5698
scraped_at: 2025-12-24 13:02:46
description:
  Overview of the Workflow
  The automation process consists of four main steps:
  Get Longform: Retrieve the long-form video data (e.g., from Google Sheets).
  Analyze Longform: Use Clap to analyze the video and generate short clips.
  Produce Shorts: Export the generated clips.
  Publish Shorts: Update the status in Google Sheets and publish the clips to social media platforms.

  Each step is handled by specific nodes in n8n, a no-code automation tool, making the entire process accessible even if you’re not tech-savvy. The workflow is visually represented in the provided n8n screenshot, with nodes connected to show the flow of data and actions.

  Step 1: Get Longform
  Purpose
  Start the automation and retrieve the long-form video data.

  Tips
  Test the node with a sample row to ensure it retrieves the correct data.
  Use a consistent sheet structure to avoid errors in future runs.

  Why It Matters
  This step ensures the automation starts automatically and pulls the correct video for processing, saving you from manual intervention.

  Step 2: Analyze Longform
  Purpose
  Use Clap to analyze the long-form video and generate short clips.

  Tips
  Pin the Get Shorts Details Node**: Right-click and pin it to retain data for testing across sessions.
  Test with a Sample Video**: Run the workflow with a short video to verify Clap’s output.

  Why It Matters
  Clap’s AI identifies key moments and generates clips, saving hours of manual editing. The wait and status nodes ensure the workflow progresses only when ready.

  Step 3: Produce Shorts
  Purpose
  Export the generated clips for publishing.

  Tips
  Preview the clips after export to ensure quality.
  Adjust wait times based on export duration observed during testing.

  Why It Matters
  This step finalizes the clips, making them ready for publishing, with wait nodes preventing premature progression.

  Step 4: Publish Shorts
  Purpose
  Update the video’s status in Google Sheets and publish the clips to social media.

  Tips
  Add an If Node**: Before updating, check if the status is already "done" to skip processed videos.
  Organize Clips**: Use Google Sheets columns (e.g., "TikTok," "YouTube") to assign clips to platforms.

  Why It Matters
  This step automates publishing across multiple platforms and keeps your workflow organized by updating statuses.

  Additional Tips for Efficiency
  No-Code Simplicity**: n8n’s drag-and-drop interface requires no coding—adjust nodes visually to suit your needs.
  Handle Processing Times**: Use wait nodes to manage delays in analysis and export steps.
  Monetization Ideas**:
    Offer this automation as a service to businesses or creators.
    Submit clips to platforms like "Wop" for earnings based on views.
  Testing**: Run the workflow with a sample video, pinning nodes to retain data for debugging.

  Benefits of AI Automation
  Time Savings**: Automate clipping and publishing, freeing you for creative tasks.
  Scalability**: Produce 100+ shorts from one video, boosting reach.
  Consistency**: Maintain a regular posting schedule effortlessly.
  Cost-Effective**: Reduce reliance on manual editing or expensive tools.

  This workflow leverages n8n and Klap to streamline short-form content creation, making it ideal for content creators looking to maximize their long-form videos. If you need further clarification or help with specific nodes, let me know!

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

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name: 🚀 Automated Stripe Payment Recovery: Track Failures & Follow-Up Emails
author_name: iamvaar
author_username: iamvaar
categories: []
created_at: 2025-07-05T16:27:30.617Z
updated_at: 2025-07-05T16:27:30.617Z
url: https://n8n.io/workflows/5702
scraped_at: 2025-12-24 13:02:41
description:
  🚀 Automated Stripe Payment Recovery Workflow (n8n)

  Detect failed payments, log them, and send polite follow-up emails to recover revenue — all automated with n8n.

  ✅ Part A – Detect & log failed payments

  What it does:

  Listens for failed Stripe payments.
  Extracts customer & payment info.
  Logs them neatly in Google Sheets for follow-up.

  🧩 Nodes:

  1️⃣ Stripe Trigger

  Listens to:

      payment_intent.payment_failed
    
  2️⃣ Set node

  Extracts & maps fields:

    Name, Email, Amount (in cents), Currency
    payment\_intent\_id
    added\_at → {{ $now }}
    email\_sent\_count → 0

  3️⃣ Remove Duplicates

  Keeps the sheet clean (avoids duplicate rows).

  4️⃣ Google Sheets node

  Append or update row:

    Name, Email, Amount/100, Currency, payment\_intent\_id, added\_at, email\_sent\_count

  &gt; 📌 This builds your “failed payments queue” to drive the follow-up emails later.

  🔁 Part B – Daily follow-up emails

  What it does:

  Runs daily.
  Checks which users haven’t received 2 emails yet.
  Sends reminder emails and tracks how many were sent.

  🧩 Nodes:
  1️⃣ Schedule Trigger

  Runs every day at 10 AM (0 10 * * *)

  2️⃣ Get Payment Failure Leads

  Reads rows from Google Sheet.

  3️⃣ Switch node (Check for no. of emails sent)

  If email_sent_count &lt; 1 → send first email.
  Else if email_sent_count &lt; 2 → send second email.
  Else → mark as "quit sending emails".

  4️⃣ Send First Email

  Sends a gentle reminder with billing page button.

  5️⃣ Update Email Count

  Increments email_sent_count by +1 in Google Sheets.

  6️⃣ Send Second Email

  Sends final, urgent reminder.

  7️⃣ Quit Sending Emails to these Leads

  Marks that no more emails should be sent.

  📝 Headline

  &gt; 🚀 Automated Stripe Payment Recovery: Track Failures & Send Follow-Up Emails via n8n

  ✅ Why this matters:

  Catch failed payments automatically.
  Log every attempt & follow-up count.
  Recover lost revenue while staying polite and respectful.
  Avoid spamming by capping follow-ups to 2 emails.

nodes_used:
  ["n8n-nodes-base.stripeTrigger","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.removeDuplicates","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.switch","n8n-nodes-base.sendInBlue","n8n-nodes-base.sendInBlue","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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