Skip to main content
Glama
efikuta

YouTube Knowledge MCP

by efikuta

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

Install Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/efikuta/youtube-knowledge-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server