YouTube Knowledge MCP

Production-ready Model Context Protocol (MCP) server that turns YouTube into a queryable knowledge source. Search, fetch details, analyze transcripts/comments, and power AI workflows with optional LLMs. Built for Claude Desktop and other MCP clients.

Why this is special

Fast + quota-aware YouTube API access with caching
Batteries-included tools for search, details, trending, channels
Optional AI superpowers (OpenAI/Anthropic) for summaries, topics, chapters, learning paths, comment intents, and knowledge graphs
Zero noise: minimal config, clear logs, safe defaults

Requirements

Node.js 18+
YouTube Data API v3 key
Optional: OpenAI and/or Anthropic API keys for AI tools

Install

npm install

Configure environment

Create .env (or set variables in your MCP client config). You can start from the example:

cp env.example .env

Then set values in .env:

# Required
YOUTUBE_API_KEY=your_youtube_api_key

# Optional AI providers (enables AI tools: analyze_video_content, generate_learning_path, analyze_comment_intents, simplify_video_transcript, generate_video_chapters, generate_knowledge_graph)
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key

# Optional tuning
LOG_LEVEL=info
MAX_DAILY_QUOTA=8000
REDIS_URL= # e.g. redis://localhost:6379
REDIS_HOST=
REDIS_PORT=
REDIS_PASSWORD=

An env.example with placeholders is provided. Do not commit your .env.

Build and run

# Development (watch)
npm run dev

# Production
npm run build
npm start

Connect to Claude Desktop (example)

Add to your Claude Desktop configuration with absolute paths:

{
  "mcpServers": {
    "youtube-knowledge": {
      "command": "node",
      "args": ["/absolute/path/to/youtube-knowledge-mcp/build/index.js"],
      "env": {
        "YOUTUBE_API_KEY": "your_youtube_api_key",
        "OPENAI_API_KEY": "optional_openai",
        "ANTHROPIC_API_KEY": "optional_anthropic",
        "LOG_LEVEL": "info"
      }
    }
  }
}

Restart Claude Desktop after editing the config.

Available tools

youtube_search — Search videos with filters
get_video_details — Video metadata, transcript (best-effort), comments
get_trending_videos — Most popular by region/category
search_channels — Channel search with optional stats
analyze_video_content — AI topics/sentiment/questions/summary/keywords
generate_learning_path — AI learning path for a topic
analyze_comment_intents — Classify viewer intents
simplify_video_transcript — ELI5-style simplification
generate_video_chapters — AI chapters with timestamps
generate_knowledge_graph — Cross-video concept graph

Note: AI tools are available only if an AI provider key is configured.

Quotas and safety

Enforces daily quota (default 8000 units) and cost-aware AI usage
Logs to stderr (does not break MCP stdio)
Caching reduces API and token spend; optional Redis supported

Troubleshooting

Missing key: ensure YOUTUBE_API_KEY is set
Quota exceeded: lower usage, enable caching, or raise MAX_DAILY_QUOTA
Claude cannot connect: verify absolute path to build/index.js and restart

License

MIT By Efi Kuta

This server cannot be installed

security - not tested

license - not found

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Transforms YouTube into a queryable knowledge source with search, video details, transcript analysis, and AI-powered tools for summaries, learning paths, and knowledge graphs. Features quota-aware API access with caching and optional OpenAI/Anthropic integration for advanced content analysis.

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