glennlzl/youtube-crawler-mcp
3.2
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A Model Context Protocol (MCP) server designed for YouTube data crawling with AI-powered summarization capabilities.
Tools
3
Resources
0
Prompts
0
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.
🚀 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 stdio
Remote 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 agents
Docker
# 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-mcp
MCP 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 up
Deploy to AWS Fargate
See for detailed AWS Fargate deployment instructions.
Testing
# Test with specific channel
python test_m2story.py
Cost Estimates
- Transcription: ~$0.18 per 30-min video (Whisper API)
- Summary: ~$0.004 per video (DeepSeek)
- Total: ~$0.184 per video
License
MIT