YouTube MCP Server

A comprehensive Model Context Protocol server for the YouTube Data API v3, Analytics API, and Reporting API. Gives AI assistants full access to your YouTube channel — analytics, video management, comments, and more.

40 tools covering:

• Channel & video data

• YouTube Analytics (performance, audience, retention, revenue)

• Video publishing & playlist management

• Transcript extraction

• YouTube SEO (search suggestions, trending)

• Comments

• Bulk reporting

Why This Server?

Existing YouTube MCP servers focus narrowly on transcript scraping or basic search. This server covers three YouTube APIs and is the only open-source MCP server that provides:

• YouTube Analytics API — channel performance, top videos/Shorts, audience retention curves, traffic sources, demographics, revenue, day-of-week analysis

• YouTube Reporting API — schedule and download bulk CSV reports

• Full Data API coverage — not just read, but also upload videos, manage playlists, post comments, set thumbnails

• YouTube SEO tools — autocomplete suggestions, trending videos, category discovery

• Dual transcript strategy — official captions API for your own videos, youtube-transcript-api fallback for any public video

• Quota tracking — client-side tracking with hard-fail protection so you don't silently exhaust your daily quota

Prerequisites

• Python 3.11+

• A Google Cloud project with YouTube APIs enabled

• OAuth 2.0 credentials

Google Cloud Setup

1. Create a Google Cloud Project

1. Go to Google Cloud Console

2. Create a new project (or use an existing one)

2. Enable APIs

Enable all three APIs in APIs & Services > Library:

• YouTube Data API v3

• YouTube Analytics API

• YouTube Reporting API

3. Configure OAuth Consent Screen

1. Go to APIs & Services > OAuth consent screen

2. Set User Type to External

3. Fill in the app name and required fields

4. Add the Google account that owns your YouTube channel as a test user

Important: You must sign in with the Google account that owns the YouTube channel, not a manager. Only the owner account can access Analytics data.

4. Create OAuth Credentials

1. Go to APIs & Services > Credentials

2. Click Create Credentials > OAuth client ID

3. Application type: Desktop app

4. Download the JSON file

5. Save it as ~/.youtube-mcp/client_secret.json

Alternatively, set the YOUTUBE_MCP_CLIENT_SECRET environment variable to the path of your credentials file.

Installation

pip install youtube-studio-mcp

Or with uv:

uv pip install youtube-studio-mcp

MCP Client Configuration

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "youtube": {
      "command": "youtube-studio-mcp"
    }
  }
}

Claude Code

Add to your MCP settings:

{
  "mcpServers": {
    "youtube": {
      "command": "youtube-studio-mcp"
    }
  }
}

With environment variables

{
  "mcpServers": {
    "youtube": {
      "command": "youtube-studio-mcp",
      "env": {
        "YOUTUBE_MCP_CLIENT_SECRET": "/path/to/client_secret.json",
        "YOUTUBE_API_KEY": "your-api-key-for-public-data"
      }
    }
  }
}

First Run

On first use, the server will open a browser window for Google OAuth consent. Sign in with the account that owns your YouTube channel and grant the requested permissions. The token is saved to ~/.youtube-mcp/token.json and auto-refreshes.

Tools Reference

Auth & Setup (2 tools)

Channel & Video (3 tools)

Search & SEO (4 tools)

Transcripts (2 tools)

Analytics — Performance (4 tools)

Analytics — Audience (3 tools)

Analytics — Schedule & Reach (3 tools)

Analytics — Revenue & Retention (3 tools)

Publishing (4 tools)

Playlists (4 tools)

Comments (3 tools)

Bulk Reporting (5 tools)

Quota Management

The YouTube Data API v3 has a default daily quota of 10,000 units. This server tracks quota usage client-side and hard-fails when the quota is exhausted.

Key costs:

• Most read operations: 1 unit

• Search: 100 units

• Write operations: 50 units

• Video upload: 1,600 units

Use youtube_auth_status to check current quota usage.

Environment Variables

Development

git clone https://github.com/pauling-ai/youtube-studio-mcp.git
cd youtube-studio-mcp
uv venv && uv pip install -e ".[dev]"
.venv/bin/python -m pytest tests/ -v

License

MIT