vunm-youtube-mcp

A custom, quota-efficient Model Context Protocol (MCP) server that empowers AI assistants (Antigravity, Claude Desktop, Cursor, Cline) to interact directly with your YouTube channel.

Built with Python and FastMCP, it supports channel analytics, video metadata updates (SEO), high-speed subtitle/transcript extraction, and comment management via official Google APIs with OAuth 2.0.

Key Capabilities

• Channel Analytics: Query private metrics directly via YouTube Analytics API v2 (watch time, viewer retention, subscriber gain/loss, demographics).

• Video Management: Update titles, descriptions, keyword tags, category, and privacy status (public, unlisted, private) on YouTube Studio.

• Quota Efficiency: Uses channel upload playlist indexing (1 API unit) instead of expensive global searches (100 API units).

• Zero-Quota Transcripts: Extracts timestamped captions across multiple languages without consuming YouTube Data API quota.

• Audience Feedback: Fetches and evaluates recent video comments for sentiment analysis and drafting responses.

Related MCP server: YouTube MCP Server

Tools Catalog

Quick Start

1. Prerequisites

• Python 3.10 or higher.

• A Google Cloud Project with:

  • YouTube Data API v3 enabled.

  • YouTube Analytics API enabled.

2. Google OAuth 2.0 Credentials Setup

1. Open Google Cloud Console.

2. Create or select a project.

3. Enable YouTube Data API v3 and YouTube Analytics API under APIs & Services $\rightarrow$ Library.

4. Configure OAuth consent screen (User type: External, add your channel email under Test users).

5. Go to Credentials $\rightarrow$ Create Credentials $\rightarrow$ OAuth client ID (Application type: Desktop app).

6. Download the client secret JSON, rename it to client_secret.json, and place it in:

   vunm-youtube-mcp/credentials/client_secret.json

   (Note: The credentials/ folder is strictly ignored by .gitignore and will never be committed).

3. Installation & First-Time Authentication

# Clone the repository
git clone https://github.com/vunm-io/vunm-youtube-mcp.git
cd vunm-youtube-mcp

# Create virtual environment and install dependencies
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

# Run initial authorization (opens browser to grant permissions)
python authenticate.py

Upon successful login, credentials/token.json is generated and automatically refreshed on subsequent runs.

Integration with AI Clients

Antigravity (Gemini CLI / Antigravity IDE)

Add the server to ~/.gemini/config/mcp_config.json:

{
  "mcpServers": {
    "vunm-youtube-mcp": {
      "command": "/absolute/path/to/vunm-youtube-mcp/.venv/bin/python",
      "args": ["-m", "src.server"],
      "cwd": "/absolute/path/to/vunm-youtube-mcp"
    }
  }
}

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "vunm-youtube-mcp": {
      "command": "/absolute/path/to/vunm-youtube-mcp/.venv/bin/python",
      "args": ["-m", "src.server"],
      "cwd": "/absolute/path/to/vunm-youtube-mcp"
    }
  }
}

Security & Privacy

• All credentials (client_secret.json, token.json) remain 100% local on your machine.

• Scopes requested are strictly limited to YouTube management and read-only analytics.

• For security questions or vulnerability reports, please see SECURITY.md.

Contributing & License

Contributions are welcome! Please review CONTRIBUTING.md before submitting a pull request.

Released under the MIT License.