YouTube
Search YouTube videos and retrieve their transcripts using the YouTube API.
YouTube MCP Server
A Model Context Protocol (MCP) server that enables Claude Desktop (and other applications) to interact with YouTube, providing search and transcript functionality.
Features
- Search YouTube Videos: Search for videos with customizable result counts
- Get Video Transcripts: Extract transcripts from YouTube videos using URLs or video IDs
- AI-Ready Integration: Seamlessly integrates with Claude Desktop for YouTube content analysis
Tools Available
1. search_youtube_videos
- Purpose: Search YouTube for videos based on a query
- Parameters:
search_term(string): The search querynum_videos(int): Number of videos to return (default: 5, max: 50)
- Returns: List of video information including titles, channels, descriptions, URLs, and metadata
2. get_youtube_transcript
- Purpose: Extract transcript from a YouTube video
- Parameters:
video_url_or_title(string): YouTube video URL or video ID
- Returns: Full transcript with timestamps and metadata
3. analyze_youtube_content_prompt
- Purpose: AI prompt template for comprehensive YouTube content analysis
- Parameters:
search_term(string): Topic to analyzenum_videos(int): Number of videos to analyze
Setup
1. Install Dependencies
# Create virtual environment
python3 -m venv .venv
# Activate virtual environment
source .venv/bin/activate
# Install dependencies
pip install -r requirements.txt
2. Get YouTube API Key
- Go to Google Cloud Console
- Create a new project or select existing one
- Enable YouTube Data API v3
- Create credentials (API Key)
- Copy the API key
3. Configure Environment
# Copy example environment file
cp .env.example .env
# Edit .env and add your YouTube API key
YOUTUBE_API_KEY=your_actual_api_key_here
4. Test the Server
# Activate virtual environment
source .venv/bin/activate
# Run the server
python youtube_server.py
Integration with Claude Desktop
Add this configuration to your Claude Desktop MCP settings:
{
"mcpServers": {
"youtube": {
"command": "local/path/to/uv",
"args": [
"run",
"--directory",
"/Path/to/your/project",
"youtube_server.py"
],
"env": {
"YOUTUBE_API_KEY": "your_key_here"
}
}
}
Usage Examples
Once integrated with Claude Desktop, you can:
- "Search for videos about machine learning and get transcripts"
- "Find the latest videos on climate change and analyze their content"
- "Get the transcript of this YouTube video: https://www.youtube.com/watch?v=..."
- "Compare different perspectives on AI ethics from YouTube videos"
Error Handling
- Missing API Key: Server will warn and search functionality will be limited
- Invalid Video IDs: Clear error messages for transcript requests
- API Limits: Respects YouTube API quotas and rate limits
- Missing Transcripts: Handles videos without available captions
Dependencies
fastmcp: MCP server frameworkgoogle-api-python-client: YouTube Data API accessyoutube-transcript-api: Transcript extraction
License
This project is open source and available under standard licensing terms.
Máy chủ liên quan
arXiv Search
A server for searching academic papers and preprints on arXiv.org.
Grok Search
Comprehensive web, news, and social media search and analysis using xAI's Grok API.
MCP Tavily
Advanced web search and content extraction using the Tavily API.
BigGo MCP Server
A server for product search, price history tracking, and specification search using the BigGo API.
Parquet MCP Server
An MCP server for web and similarity search, designed for Claude Desktop. It integrates with various external embedding and API services.
Manalink MCP Server
An MCP server implementation for Manalink that allows AI assistants to use functions like teacher search.
Handaas Enterprise Big Data Service
Provides comprehensive enterprise information query and analysis, including business info, risk analysis, intellectual property, and operational insights.
Google PSE/CSE
A Model Context Protocol (MCP) server providing access to Google Programmable Search Engine (PSE) and Custom Search Engine (CSE).
Qdrant RAG MCP Server
A semantic search server for codebases using Qdrant, featuring intelligent GitHub issue and project management.
Local RAG
Privacy-first local RAG server for semantic document search without external APIs