YouTube Video Summarizer MCP Server

An MCP (Model Context Protocol) server that enables AI assistants to analyze and summarize YouTube videos by extracting captions, descriptions, and metadata.

Features

• Extract video captions/subtitles in multiple languages
• Retrieve comprehensive video metadata (title, description, duration)
• Provide structured data to AI assistants for comprehensive video summarization
• Works with any MCP-compatible client through MCP integration
• Support for multiple YouTube URL formats
• Language-specific caption extraction

Integrating with MCP Clients

To add the MCP server to your MCP client:

1. Install the package globally: npm install -g youtube-video-summarizer-mcp
2. Add the following to your MCP client configuration file:

{
  "mcpServers": {
    "youtube-video-summarizer": {
      "command": "youtube-video-summarizer",
      "args": []
    }
  }
}

Available Tools

When integrated with an MCP client, the following commands become available:

• get-video-info-for-summary-from-url: Extract video information and captions from a YouTube URL
• get-video-captions: Get captions/subtitles for a specific video
• get-video-metadata: Retrieve comprehensive video metadata

Usage Examples

Once integrated with your MCP client, you can use natural language to request video summaries:

"Can you summarize this YouTube video: https://youtube.com/watch?v=VIDEO_ID"
"What are the main points from this video's captions?"
"Extract the key information from this YouTube link"

Installation

npm install -g youtube-video-summarizer-mcp

Development

git clone https://github.com/nabid-pf/youtube-video-summarizer-mcp.git
cd youtube-video-summarizer-mcp
npm install
npm run build

How It Works

1. URL Parsing: Extracts video IDs from various YouTube URL formats
2. Caption Extraction: Uses youtube-caption-extractor to get subtitles
3. Metadata Retrieval: Fetches video title, description, and other details
4. MCP Integration: The Model Context Protocol (MCP) to communicate with AI assistants

Contributing

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

License

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