概要
What is YouTube MCP Server?
A Model Context Protocol (MCP) server that integrates with the YouTube Data API, allowing AI language models to retrieve video details, search content, fetch transcripts, analyze channels, and compare performance metrics through a standardized tool interface.
How to use YouTube MCP Server?
Install via npm or Smithery, set the required YOUTUBE_API_KEY environment variable (and optional YOUTUBE_TRANSCRIPT_LANG), then add the server to your MCP client configuration. Invoke any of the nine provided tools (e.g., getVideoDetails, searchVideos, getTrendingVideos) to interact with YouTube content.
Key features of YouTube MCP Server
- Retrieve detailed video information and statistics
- Search videos by keywords with configurable results
- Fetch multi‑language, time‑stamped video transcripts
- Get related videos based on YouTube's recommendation algorithm
- View detailed channel statistics (subscribers, views, count)
- Obtain a channel's most viewed videos
- Calculate engagement ratios (views, likes, comments)
- Discover trending videos by region and category
- Compare statistics across multiple videos simultaneously
Use cases of YouTube MCP Server
- Research video performance and engagement for content analysis
- Extract transcripts and captions for accessibility or summarization
- Discover trending content per region or category for trend analysis
- Analyze channel growth and top‑performing videos for marketing
- Compare metrics across several videos to benchmark performance
FAQ from YouTube MCP Server
What runtime is required?
Node.js 18.0.0 or higher.
How do I obtain a YouTube API key?
Access the Google Cloud Console, create or select a project, enable the YouTube Data API v3, and generate an API key under credentials.
What environment variables must be set?
YOUTUBE_API_KEY is required; YOUTUBE_TRANSCRIPT_LANG (default 'ko') is optional.
How are transcripts retrieved?
Use the getTranscripts tool with video IDs and an optional language parameter; the server returns time‑stamped captions.
How should I keep my API key secure?
Never commit the key to version control; manage it through environment variables or configuration files and set usage limits in the Google Cloud Console.
