YouTube MCP Server

YouTube MCP Server

Enables AI language models to interact with YouTube content through a standardized interface, providing tools for retrieving video information, transcripts, channel analytics, and trend analysis.

icraft2170

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YouTube MCP Server

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A Model Context Protocol (MCP) server implementation utilizing the YouTube Data API. It allows AI language models to interact with YouTube content through a standardized interface.

Key Features

Video Information

  • Retrieve detailed video information (title, description, duration, statistics)
  • Search for videos by keywords
  • Get related videos based on a specific video
  • Calculate and analyze video engagement ratios

Transcript/Caption Management

  • Retrieve video captions with multi-language support
  • Specify language preferences for transcripts
  • Access time-stamped captions for precise content reference

Channel Analysis

  • View detailed channel statistics (subscribers, views, video count)
  • Get top-performing videos from a channel
  • Analyze channel growth and engagement metrics

Trend Analysis

  • View trending videos by region and category
  • Compare performance metrics across multiple videos
  • Discover popular content in specific categories

Available Tools

The server provides the following MCP tools:

Tool Name Description Required Parameters
getVideoDetails Get detailed information about multiple YouTube videos including metadata, statistics, and content details videoIds (array)
searchVideos Search for videos based on a query string query, maxResults (optional)
getTranscripts Retrieve transcripts for multiple videos videoIds (array), lang (optional)
getRelatedVideos Get videos related to a specific video based on YouTube's recommendation algorithm videoId, maxResults (optional)
getChannelStatistics Retrieve detailed metrics for multiple channels including subscriber count, view count, and video count channelIds (array)
getChannelTopVideos Get the most viewed videos from a specific channel channelId, maxResults (optional)
getVideoEngagementRatio Calculate engagement metrics for multiple videos (views, likes, comments, and engagement ratio) videoIds (array)
getTrendingVideos Get currently popular videos by region and category regionCode (optional), categoryId (optional), maxResults (optional)
compareVideos Compare statistics across multiple videos videoIds (array)

Installation

Automatic Installation via Smithery

Automatically install YouTube MCP Server for Claude Desktop via Smithery:

npx -y @smithery/cli install @icraft2170/youtube-data-mcp-server --client claude

Manual Installation

# Install from npm
npm install youtube-data-mcp-server

# Or clone repository
git clone https://github.com/icraft2170/youtube-data-mcp-server.git
cd youtube-data-mcp-server
npm install

Environment Configuration

Set the following environment variables:

  • YOUTUBE_API_KEY: YouTube Data API key (required)
  • YOUTUBE_TRANSCRIPT_LANG: Default caption language (optional, default: 'ko')

MCP Client Configuration

Add the following to your Claude Desktop configuration file:

{
  "mcpServers": {
    "youtube": {
      "command": "npx",
      "args": ["-y", "youtube-data-mcp-server"],
      "env": {
        "YOUTUBE_API_KEY": "YOUR_API_KEY_HERE",
        "YOUTUBE_TRANSCRIPT_LANG": "ko"
      }
    }
  }
}

YouTube API Setup

  1. Access Google Cloud Console
  2. Create a new project or select an existing one
  3. Enable YouTube Data API v3
  4. Create API credentials (API key)
  5. Use the generated API key in your environment configuration

Development

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build
npm run build

Network Configuration

The server exposes the following ports for communication:

  • HTTP: 3000
  • gRPC: 3001

System Requirements

  • Node.js 18.0.0 or higher

Security Considerations

  • Always keep your API key secure and never commit it to version control systems
  • Manage your API key through environment variables or configuration files
  • Set usage limits for your API key to prevent unauthorized use

License

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

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