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YouTube Knowledge MCP

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

Available Tools

10 tools
analyze_comment_intentsC

Analyze YouTube comments to extract user intents and actionable insights

Inputs: videoId (required), maxComments, intentCategories.

analyze_video_contentC

Get AI-powered analysis and insights from video content

Inputs: videoId (required), analysisType, includeComments.

generate_knowledge_graphC

Create cross-video knowledge graphs showing concept relationships

Inputs: videoIds (required), graphDepth, focusTopics, includeTranscripts.

generate_learning_pathC

Generate AI-powered learning paths from YouTube content with difficulty assessment

Inputs: query (required), targetLevel, maxVideos, includeQuizzes.

generate_video_chaptersB

Generate AI-powered video chapters with timestamps and descriptions

Inputs: videoId (required), maxChapters, minChapterLength, includeDescriptions.

get_video_detailsB

Get comprehensive information about a specific YouTube video

Inputs: videoId (required), includeTranscript, includeComments, maxComments, +1 more.

search_channelsC

Find and analyze YouTube channels

Inputs: query (required), maxResults, includeStats, order.

simplify_video_transcriptB

Create age-appropriate simplified versions of video transcripts (ELI5 mode)

Inputs: videoId (required), targetAge, outputFormat, includeDefinitions.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.4/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose targeting specific YouTube operations: content analysis, search, metadata retrieval, and content transformation. There is no overlap in functionality; for example, analyze_video_content focuses on video insights while simplify_video_transcript handles transcript simplification, making misselection unlikely.

    Naming Consistency4/5

    The naming follows a consistent verb_noun pattern with snake_case throughout, such as analyze_comment_intents and generate_video_chapters. The only minor deviation is youtube_search, which uses the platform name as a prefix instead of a verb, but it still fits the overall readable convention.

    Tool Count5/5

    With 10 tools, the count is well-scoped for a YouTube knowledge server, covering a broad range of functionalities from search and analysis to content generation. Each tool earns its place by addressing distinct aspects of video and channel processing without feeling excessive or insufficient.

    Completeness4/5

    The tool set provides comprehensive coverage for YouTube knowledge extraction, including search, analysis, metadata retrieval, and content transformation. Minor gaps exist, such as the lack of tools for managing playlists or user interactions, but core workflows for learning and insights are well-supported.

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