MCP YouTube Extract

A Model Context Protocol (MCP) server for YouTube operations, demonstrating core MCP concepts including tools and logging.

✨ No API Key Required! Works out of the box using yt-info-extract for video metadata and yt-ts-extract for transcripts.

Features

• MCP Server: A fully functional MCP server with:

  • Tools: Extract information from YouTube videos including metadata and transcripts

  • Comprehensive Logging: Detailed logging throughout the application

  • Error Handling: Robust error handling with fallback logic for transcripts

• YouTube Integration: Built-in YouTube capabilities using yt-info-extract and yt-ts-extract:

  • Extract video information (title, description, channel, publish date, view count)

  • Get video transcripts with intelligent fallback logic

  • Support for both manually created and auto-generated transcripts

  • No API key required for basic functionality

📦 Available on PyPI

This package is now available on PyPI! You can install it directly with:

Visit the package page: mcp-youtube-extract on PyPI

Installation

Quick Start (Recommended)

The easiest way to get started is to install from PyPI:

Or using pipx (recommended for command-line tools):

This will install the latest version with all dependencies. You can then run the MCP server directly:

Using uv (Development)

For development or if you prefer uv:

From source

1. Clone the repository:

   git clone https://github.com/sinjab/mcp_youtube_extract.git cd mcp_youtube_extract

2. Install in development mode:

   uv sync --dev

Configuration

Environment Variables

No configuration required! The server works out of the box using yt-info-extract for metadata extraction.

Optional: For enhanced functionality, you can optionally set a YouTube API key:

Optional:

• YOUTUBE_API_KEY: Your YouTube Data API key (optional, provides additional fallback for metadata extraction)

Getting Your YouTube API Key (Optional)

While not required, you can optionally set up a YouTube Data API key for enhanced functionality. Here's how to get one:

Step 1: Create a Google Cloud Project

1. Go to the Google Cloud Console

2. Click "Select a project" at the top of the page

3. Click "New Project" and give it a name (e.g., "MCP YouTube Extract")

4. Click "Create"

Step 2: Enable the YouTube Data API

1. In your new project, go to the API Library

2. Search for "YouTube Data API v3"

3. Click on it and then click "Enable"

Step 3: Create API Credentials

1. Go to the Credentials page

2. Click "Create Credentials" and select "API Key"

3. Your new API key will be displayed - copy it immediately

4. Click "Restrict Key" to secure it (recommended)

Step 4: Restrict Your API Key (Recommended)

1. In the API key settings, click "Restrict Key"

2. Under "API restrictions", select "Restrict key"

3. Choose "YouTube Data API v3" from the dropdown

4. Click "Save"

Step 5: Set Up Billing (Required)

1. Go to the Billing page

2. Link a billing account to your project

3. Note: YouTube Data API has a free tier of 10,000 units per day, which is typically sufficient for most use cases

API Key Usage Limits

• Free Tier: 10,000 units per day

• Cost: $5 per 1,000 units after free tier

• Note: API key is only used as a fallback when yt-info-extract fails

• Most users won't need an API key as yt-info-extract handles most requests

Security Best Practices

• Never commit your API key to version control

• Use environment variables as shown in the configuration section

• Restrict your API key to only the YouTube Data API

• Monitor usage in the Google Cloud Console

Usage

Running the MCP Server

Using PyPI Installation (Recommended)

Using Development Setup

Running Tests

Note: The tests/ directory contains 4 files:

• test_context_fix.py - Pytest test for context API fallback functionality

• test_with_api_key.py - Pytest test for full functionality with API key

• test_youtube_unit.py - Unit tests for core YouTube functionality

• test_inspector.py - Standalone inspection script (not a pytest test)

Test Coverage: The project currently has 62% overall coverage with excellent coverage of core functionality:

• youtube.py: 81% coverage (core business logic)

• logger.py: 73% coverage (logging utilities)

• server.py: 22% coverage (MCP protocol handling)

• __init__.py: 100% coverage (package initialization)

Running the Inspection Script

The test_inspector.py file is a standalone script that connects to the MCP server and validates its functionality:

This script will:

• Connect to the MCP server

• List available tools, resources, and prompts

• Test the get_yt_video_info tool with a sample video

• Validate that the server is working correctly

Using the YouTube Tool

The server provides one main tool: get_yt_video_info

This tool takes a YouTube video ID and returns:

• Video metadata (title, description, channel, publish date, view count) via yt-info-extract

• Video transcript (with fallback logic for different transcript types) via yt-ts-extract

Example Usage:

Client Configuration

To use this MCP server with a client, add the following configuration to your client's settings:

Using PyPI Installation (Recommended)

With optional API key:

Using Development Setup

With optional API key:

Development

Project Structure

Testing Strategy

The project uses a comprehensive testing approach:

1. Unit Tests (test_youtube_unit.py): Test core YouTube functionality with mocked yt-info-extract

2. Integration Tests (test_context_fix.py, test_with_api_key.py): Test full server functionality

3. Manual Validation (test_inspector.py): Interactive server inspection tool

Error Handling

The project includes robust error handling:

• Graceful extraction failures: Returns appropriate error messages instead of crashing

• Multiple fallback strategies: yt-info-extract provides automatic fallback between YouTube Data API, yt-dlp, and pytubefix

• Transcript fallback logic: Multiple strategies for transcript retrieval via yt-ts-extract

• Consistent error responses: Standardized error message format

• Comprehensive logging: Detailed logs for debugging and monitoring

Building

License

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

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Getting Started

1. Fork the repository

2. Create a feature branch (git checkout -b feature/amazing-feature)

3. Commit your changes (git commit -m 'Add some amazing feature')

4. Push to the branch (git push origin feature/amazing-feature)

5. Open a Pull Request

Support

If you encounter any issues or have questions, please:

1. Check the existing issues

2. Create a new issue with detailed information about your problem

3. Include logs and error messages when applicable