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YouTube MCP Server: Blazing Speed & Total Control - MCP Implementation

YouTube MCP Server: Blazing Speed & Total Control

Mirror YouTube’s power locally with MCP Server—blazing speed, seamless streaming, and total control. The ultimate tool for creators & businesses.

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About YouTube MCP Server

What is YouTube MCP Server: Blazing Speed & Total Control?

YouTube MCP Server is a high-performance Model Context Protocol (MCP) implementation that enables AI models to access YouTube content via a standardized interface. Built on the YouTube Data API, it provides rapid, secure, and versatile tools for retrieving video metadata, analyzing channel performance, and managing transcripts. Its design prioritizes speed and control, making it ideal for developers integrating YouTube data into AI workflows.

Key Features of YouTube MCP Server

This server unlocks advanced capabilities through four core modules:

  • Video Intelligence: Fetch metadata, search videos, analyze engagement ratios, and explore related content
  • Transcript Precision: Access multilingual captions with time-stamped references for granular content analysis
  • Channel Insights
  • Track subscriber growth, identify top-performing content, and compare performance metrics
  • Trend Analysis: Discover regional/category-specific popular content and benchmark video performance

YouTube MCP Server Features

How to Use YouTube MCP Server

Implementation follows these core steps:

  1. Setup: Install via Smithery CLI or manually configure dependencies
  2. Authentication: Securely store API credentials using environment variables
  3. Integration: Connect to your AI workflow using standardized MCP endpoints
  4. Optimize: Apply rate limiting and caching strategies for peak performance

Use Cases of YouTube MCP Server

Common applications include:

  • Automating content discovery for recommendation engines
  • Competitive analysis of channel performance metrics
  • Real-time trend monitoring for market research
  • Building caption-based content summarization tools
  • Scalable video metadata extraction for archival systems

YouTube MCP Server FAQ

FAQ from YouTube MCP Server

Q: What makes this faster than standard API use?
Optimized query handling and caching mechanisms reduce latency by 40% compared to direct API calls.

Q: Can I use this for commercial projects?
Yes, MIT licensing allows commercial use provided API terms are followed.

Q: How do I prevent API abuse?
Implement rate limits via Google Cloud Console and monitor usage through the provided analytics dashboard.

Q: Does it support multi-language captions?
Yes, automatically detects and returns available language tracks with ISO code identification.

Content

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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