tube-bridge MCP server

tube-bridge

<!-- mcp-name: io.github.TheWhiteWater/tube-bridge -->

Self-hosted YouTube research for AI agents.

Search videos and channels, read transcripts and comments, extract timestamped frames, and build private semantic-search corpora — through 17 MCP tools.

• 14 of 17 tools need no YouTube API key.
• Local-first corpus: transcripts, vectors, and indexes stay on your machine.
• Useful research output: titles, similarity scores, canonical video URLs, and timestamp links.
• One tool for one frame: return visual evidence near a transcript finding without keeping media files.
• Self-hosted and MIT: no account, hosted intermediary, managed storage, or vendor lock-in.

Thanks to everyone already using tube-bridge. If it saves you time, consider starring the repository — it helps others discover the project and signals that publishing more work like this is worthwhile.

Connect in a minute

The simplest setup uses uvx, which runs the published PyPI package in an isolated environment:

uvx tube-bridge

Normally your MCP client launches that command for you. Choose your client below.

[!NOTE]

tube-bridge requires Python 3.12 or newer. An API key is optional. ffmpeg is needed only for youtubegetframe, and the first embedding operation may download the local model.

Claude Desktop

Open Settings → Developer → Edit Config and add:

{
  "mcpServers": {
    "tube-bridge": {
      "command": "uvx",
      "args": ["tube-bridge"]
    }
  }
}

Restart Claude Desktop after saving the configuration.

Claude Code

claude mcp add --scope user tube-bridge -- uvx tube-bridge

Cursor

Create .cursor/mcp.json in your project, or add the server to your user-level MCP configuration:

{
  "mcpServers": {
    "tube-bridge": {
      "command": "uvx",
      "args": ["tube-bridge"]
    }
  }
}

VS Code

Create .vscode/mcp.json:

{
  "servers": {
    "tube-bridge": {
      "type": "stdio",
      "command": "uvx",
      "args": ["tube-bridge"]
    }
  }
}

Codex CLI

codex mcp add tube-bridge -- uvx tube-bridge

Pi package

Pi can load the package-relative adapter and the canonical tube-bridge-research skill from the same Git source:

python3 -m pip install tube-bridge==1.1.6
pi install git:github.com/TheWhiteWater/tube-bridge@v1.1.6
pi list

This registers one status tool plus all 17 MCP tools with the tubebridge prefix. The adapter reads the existing plugin.json and mcp.json, launches only the local stdio runtime, preserves bounded text and image content, and forwards only an allowlisted child-process environment.

The Pi package manager installs the Node adapter dependency but does not install Python or ffmpeg. Ensure the python3 visible to Pi is Python 3.12+ with the tube-bridge dependencies installed; install ffmpeg separately to use youtubegetframe. By default, Pi-managed state lives under the platform data directory; set TUBEBRIDGEPIDATA to move that root. An explicit TUBEBRIDGE_CACHE still takes precedence for the runtime databases. The optional live frame gate is /tube-bridge-selftest frame.

Remove the package with:

Shortened. The full README is on GitHub.