YouTube MCP Server

- Go toGoogle Cloud Console
- Create a new project
- Enable YouTube Data API v3
- Create credentials (OAuth 2.0 Client ID)
- Download the credentials and save asclient_secrets.json

# Install development dependencies uv pip install -e ".[dev]" # Install pre-commit hooks pre-commit install

# Required environment variables YOUTUBE_API_KEY=your_api_key_here # Optional configuration YOUTUBE_API_QUOTA_LIMIT=10000 # Daily quota limit YOUTUBE_API_REGION=US # Default region

# Check if credentials are properly set up ls -l credentials.json # Should exist and be readable ls -l .env # Should exist and be readable ls -l token.pickle # Should exist after first authentication # Test the server python mcp_videos.py

@mcp.tool() async def get_videos(search: str, max_results: int)

@mcp.tool() async def get_video_info(video_id: str)

@mcp.tool() async def get_channel_details(channel_id: str)

@mcp.tool() async def get_video_comments_tool(video_id: str, max_results: int = 100)

@mcp.tool() async def get_trending_videos_tool(region_code: str = "US", max_results: int = 50)

@mcp.tool() async def get_related_videos_tool(video_id: str, max_results: int = 25)

@mcp.tool() async def summarize_video(video_id: str, include_comments: bool = True)

@mcp.tool() async def generate_video_flashcards( video_id: str, max_cards: int = 10, categories: Optional[List[str]] = None, difficulty: Optional[str] = None )

This tool generates educational flash cards from video content:

- Creates different types of cards (Fill in the blank, Q&A, Definition)
- Includes timestamps for video reference
- Categorizes cards by type and difficulty
- Provides card statistics

# Generate 15 flash cards from a video cards = generate_video_flashcards( video_id="dQw4w9WgXcQ", max_cards=15, categories=["Q&A", "Definition"], difficulty="Medium" ) # Generate all types of cards cards = generate_video_flashcards( video_id="dQw4w9WgXcQ", max_cards=20 )

- Fill in the blank: Tests recall of specific terms or concepts
- Q&A: Questions about key points in the video
- Definition: Explains important concepts

- Easy: Basic recall and understanding
- Medium: Application of concepts
- Hard: Complex concepts and relationships

@mcp.tool() async def generate_video_quiz(video_id: str) -> str

This tool generates a comprehensive quiz from video content:

- Creates multiple choice questions
- Generates true/false statements
- Includes fill-in-the-blank questions
- Uses video metadata, transcript, and description
- Provides answers and explanations

# Generate a quiz from a video quiz = generate_video_quiz("dQw4w9WgXcQ")

- Based on video content
- Includes video metadata
- Tests understanding of key concepts

- Tests factual knowledge
- Based on video statistics
- Verifies understanding of claims

- Tests recall of specific terms
- Uses transcript content
- Focuses on key concepts

=== Video Quiz === Title: [Video Title] Channel: [Channel Name] URL: [Video URL] Question 1 (Multiple Choice): [Question text] 1. [Option 1] 2. [Option 2] 3. [Option 3] 4. [Option 4] Answer: [Correct answer] ------------------ Question 2 (True/False): [Statement] Answer: True/False ------------------ Question 3 (Fill in the blank): [Question with blank] Answer: [Correct answer] ------------------

- Generates exactly 10 questions
- Mixes different question types
- Includes video context
- Provides immediate feedback
- Uses video metadata for questions
- Incorporates transcript content
- Tests different levels of understanding

The project follows a modular architecture:

graph TD A[LLM Client] --> B[MCP Client] B --> C[MCP Server] C --> D[YouTube API] C --> E[Tool Registry] C --> F[Data Formatter] subgraph "Tools" E --> E1[Video Tools] E --> E2[Channel Tools] E --> E3[Comment Tools] E --> E4[Analysis Tools] end

youtube-mcp-server/ ├── mcp_videos.py # Main server implementation ├── youtube_api.py # YouTube API client ├── yt_helper.py # Helper functions ├── requirements.txt # Project dependencies ├── .env # Environment variables ├── .gitignore # Git ignore rules └── README.md # This file

- Create a new async function inmcp_videos.py
- Decorate it with@mcp.tool()
- Implement the tool logic
- Add appropriate error handling
- Update documentation

{ "title": str, "channel_title": str, "duration": str, "description": str, "view_count": int, "like_count": int, "comment_count": int, "url": str, "published_at": str }

{ "author": str, "text": str, "like_count": int, "published_at": str }

- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request

This project is licensed under the MIT License - see theLICENSEfile for details.

- FastMCPfor the MCP framework
- YouTube Data APIfor the API
- All contributors and users of this project
- Check thedocumentation
- Open anissue
- Contact the maintainers

- Watch the repository
- Check thereleases
- Follow thechangelog

git rm --cached token.pickle git rm --cached client_secrets.json

- VisitClaude Desktop
- Download the appropriate version for your OS: