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youtube-mcp

MCP.Pizza Chef: Prajwal-ak-0

YouTube MCP is a Model Context Protocol server designed for in-depth YouTube video analysis. It enables extraction of detailed transcripts, generation of concise video summaries using Gemini AI, natural language querying of video content, YouTube video search, and comment analysis. This server integrates with Google Gemini and YouTube Data APIs to provide rich, structured video insights for enhanced AI workflows.

Use This MCP server To

Extract detailed transcripts from YouTube videos Generate concise summaries of video content using Gemini AI Perform natural language queries on video transcripts Search YouTube videos based on specific keywords or topics Retrieve and analyze comments from YouTube videos

README

YouTube MCP

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A Model Context Protocol (MCP) server for YouTube video analysis, providing tools to get transcripts, summarize content, and query videos using Gemini AI.

Features

  • 📝 Transcript Extraction: Get detailed transcripts from YouTube videos
  • 📊 Video Summarization: Generate concise summaries using Gemini AI
  • Natural Language Queries: Ask questions about video content
  • 🔍 YouTube Search: Find videos matching specific queries
  • 💬 Comment Analysis: Retrieve and analyze video comments

Requirements

  • Python 3.9+
  • Google Gemini API key
  • YouTube Data API key

Running Locally

Installing via Smithery

To install youtube-mcp for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @Prajwal-ak-0/youtube-mcp --client claude

Option 1: Install directly from smithery

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Option 2: Local setup

  1. Clone the repository:

    git clone https://github.com/Prajwal-ak-0/youtube-mcp
    cd youtube-mcp
  2. Create a virtual environment and install dependencies:

    python -m venv .venv
    source .venv/bin/activate  # On Windows: .venv\Scripts\activate
    pip install -e .
  3. Create a .env file with your API keys:

    GEMINI_API_KEY=your_gemini_api_key
    YOUTUBE_API_KEY=your_youtube_api_key
    
  4. Run MCP Server

    mcp dev main.py

    Navigate to Stdio

    OR

  5. Go cursor or windsurf configure with this json content:

    {
      "youtube": {
        "command": "uv",
        "args": [
          "--directory",
          "/absolute/path/to/youtube-mcp",
          "run",
          "main.py",
          "--transport",
          "stdio",
          "--debug"
        ]
      }
    }

Available Tools

  • youtube/get-transcript: Get video transcript
  • youtube/summarize: Generate a video summary
  • youtube/query: Answer questions about a video
  • youtube/search: Search for YouTube videos
  • youtube/get-comments: Retrieve video comments
  • youtube/get-likes: Get video like count

Contributing

Contributions welcome! Please feel free to submit a Pull Request.

youtube-mcp FAQ

How do I install the YouTube MCP server locally?
You can install it via Smithery CLI using 'npx -y @smithery/cli install @Prajwal-ak-0/youtube-mcp --client claude' or follow manual setup instructions.
What API keys are required to run YouTube MCP?
You need a Google Gemini API key and a YouTube Data API key to enable transcript extraction, summarization, and search features.
Can YouTube MCP summarize videos using models other than Gemini?
Currently, it is optimized for Gemini AI, but the MCP architecture allows integration with other LLM providers like OpenAI and Anthropic with additional configuration.
Does YouTube MCP support comment analysis?
Yes, it can retrieve and analyze YouTube video comments to provide sentiment or thematic insights.
What Python version is required for YouTube MCP?
Python 3.9 or higher is required to run the server smoothly.
Is it possible to query video content using natural language?
Yes, YouTube MCP supports natural language queries to extract specific information from video transcripts.
How does YouTube MCP handle video search?
It uses the YouTube Data API to find videos matching user queries, enabling targeted content retrieval.
Can this MCP server be integrated with multiple MCP clients?
Yes, it is designed to work with various MCP clients like Claude Desktop and others supporting MCP protocol.