Py MCP Youtube Toolbox MCP Server

An MCP server that provides AI assistants with powerful tools to interact with YouTube, including video searching, transcript extraction, comment

Local serverstdioPython

What is the Py MCP Youtube Toolbox MCP server?

An MCP server that provides AI assistants with powerful tools to interact with YouTube, including video searching, transcript extraction, comment retrieval, and more. That is what the py mcp youtube toolbox mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

The short version

py-mcp-youtube-toolbox provides the following YouTube-related functionalities:

The tools it exposes

The server publishes 11 tools. What each one is for:

  • search_videos — Search for YouTube videos with advanced filtering options (channel, duration, region, etc.)
  • get_video_details — Get detailed information about a specific YouTube video (title, channel, views, likes, etc.)
  • get_video_comments — Retrieve comments from a YouTube video with sorting options
  • get_related_videos — Find videos related to a specific YouTube video
  • get_trending_videos — Get trending videos on YouTube by region
  • get_channel_details — Get detailed information about a YouTube channel (name, subscribers, views, etc.)
  • get_video_transcript — Extract transcripts/captions from YouTube videos in specified languages
  • get_video_enhanced_transcript — Advanced transcript extraction with filtering, search, and multi-video capabilities
  • transcript_summary — Generate summaries of YouTube video content based on transcripts with customizable options
  • youtube — //available-youtube-tools: Get a list of all available YouTube tools
  • Configuration — 1. Install UV package manager: bash curl -LsSf https://astral.sh/uv/install.sh | sh

What it needs from you

Configuration is passed through the environment: YOUTUBE_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.

  1. Python: Install Python 3.12 or higher 2. YouTube API Key: - Go to Google Cloud Console - Create a new project or select an existing one - Enable the YouTube Data API v3: 1. Go to "APIs & Services" > "Library" 2. Search for and enable "YouTube Data API v3" - Create credentials: 1. Go to "APIs & Services" > "Credentials" 2. Click "Create Credentials"

Getting it running

The server ships on npm as @smithery/cli, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.

How it compares

Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Py MCP Youtube Toolbox's toolset — search_videos, get_video_details, get_video_comments and 8 more — is a fair guide to whether it matches your workflow. It is maintained by jikime; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against Py MCP Youtube Toolbox's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Things to watch

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 11 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Py MCP Youtube Toolbox.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

Available tools

ToolWhat it does
search_videosSearch for YouTube videos with advanced filtering options (channel, duration, region, etc.)
get_video_detailsGet detailed information about a specific YouTube video (title, channel, views, likes, etc.)
get_video_commentsRetrieve comments from a YouTube video with sorting options
get_related_videosFind videos related to a specific YouTube video
get_trending_videosGet trending videos on YouTube by region
get_channel_detailsGet detailed information about a YouTube channel (name, subscribers, views, etc.)
get_video_transcriptExtract transcripts/captions from YouTube videos in specified languages
get_video_enhanced_transcriptAdvanced transcript extraction with filtering, search, and multi-video capabilities
transcript_summaryGenerate summaries of YouTube video content based on transcripts with customizable options
youtube//available-youtube-tools: Get a list of all available YouTube tools
Configuration1. Install UV package manager: bash curl -LsSf https://astral.sh/uv/install.sh | sh

How to install the Py MCP Youtube Toolbox MCP server

#### for Docker
```json
{
  "mcpServers": {
    "YouTube Toolbox": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e", "YOUTUBE_API_KEY=your_youtube_api_key",
        "py-mcp-youtube-toolbox"
      ]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  1. Python: Install Python 3.12 or higher 2. YouTube API Key: - Go to Google Cloud Console - Create a new project or select an existing one - Enable the YouTube Data API v3: 1. Go to "APIs & Services" > "Library" 2. Search for and enable "YouTube Data API v3" - Create credentials: 1. Go to "APIs & Services" > "Credentials" 2. Click "Create Credentials"
VariableDescriptionRequired
YOUTUBE_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use Py MCP Youtube Toolbox to search videos.
  • Use Py MCP Youtube Toolbox to get video details.
  • Use Py MCP Youtube Toolbox to get video comments.

Frequently asked questions

It connects Py MCP Youtube Toolbox to MCP-compatible AI assistants such as Claude and Cursor, exposing 11 tools (search_videos, get_video_details, get_video_comments, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Py MCP Youtube Toolbox directly.