YouTube Crawler MCP Server
Supports deployment to AWS Fargate for serverless containerized hosting.
Provides Docker deployment for containerized execution of the MCP server.
Cloud-ready deployment option to Fly.io for remote HTTP access.
Cloud-ready deployment option to Google Cloud Run for remote HTTP access.
Uses OpenAI's Whisper API for video transcription and supports GPT-4 models for AI-powered summarization as one of the AI providers.
Provides tools to crawl YouTube channel metadata, retrieve videos, generate AI summaries, and transcribe videos using Whisper, enabling integration with YouTube's data.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@YouTube Crawler MCP Serversummarize latest videos from @mkbhd"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
YouTube Crawler MCP Server
A Model Context Protocol (MCP) server for YouTube data crawling with AI-powered summarization. Built with FastMCP for easy deployment as both local and remote MCP server.
✨ Features
Channel metadata retrieval
AI video summaries with automatic transcription (Whisper API)
Time-range queries for videos
Supports videos with/without subtitles
Multi-language support with smart language detection
Dual transport: stdio (local) and Streamable HTTP (remote)
Cloud-ready: Deploy to AWS, Google Cloud Run, Fly.io, etc.
Related MCP server: YouTube Insights MCP Server
🚀 Quick Start
Local Usage (stdio)
# Install dependencies
pip install -e .
# Configure environment
export YOUTUBE_API_KEY=your_youtube_key
export OPENAI_API_KEY=your_openai_key
export DEEPSEEK_API_KEY=your_deepseek_key
# Run with stdio (for Claude Desktop)
python main.py stdioRemote Server (Streamable HTTP)
# Run HTTP server
python main.py streamable-http
# Server will start on http://0.0.0.0:8080
# Use with Claude API, Lambda, or other cloud agentsDocker
# Build
docker build -t youtube-crawler-mcp .
# Run
docker run -p 8080:8080 \
-e YOUTUBE_API_KEY=your_key \
-e OPENAI_API_KEY=your_key \
-e DEEPSEEK_API_KEY=your_key \
youtube-crawler-mcpMCP Tools
1. Get Channel Metadata
{
"username": "@channel_name"
}2. Get Latest Videos Summary
{
"username": "@channel_name",
"n": 5,
"include_transcript": false
}3. Get Videos by Time Range
{
"username": "@channel_name",
"start_date": "2024-01-01",
"end_date": "2024-01-31",
"max_videos": 10
}Configuration
AI Providers
DeepSeek (recommended): $0.28/1M tokens input, $0.42/1M output
OpenAI: GPT-4 models
Anthropic: Claude models
Set AI_PROVIDER in .env to switch providers.
Transcription
Uses OpenAI Whisper API ($0.006/minute) with automatic language detection from YouTube metadata.
Claude Desktop Integration
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"youtube-crawler": {
"command": "python",
"args": ["-m", "src.server"],
"cwd": "/path/to/youtubeCrawlerMcp"
}
}
}Docker Deployment
Build and Run Locally
# Build image
docker build -t youtube-crawler-mcp .
# Run with docker-compose
docker-compose upDeploy to AWS Fargate
See DEPLOY.md for detailed AWS Fargate deployment instructions.
Testing
# Test with specific channel
python test_m2story.pyCost Estimates
Transcription: ~$0.18 per 30-min video (Whisper API)
Summary: ~$0.004 per video (DeepSeek)
Total: ~$0.184 per video
License
MIT
This server cannot be installed
Maintenance
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