Audio Transcription MCP

Audio Transcription MCP

An MCP server for local audio and video transcription with local Whisper or the OpenAI transcription API.

Package and CLI name: audio-transcription-mcp.

Requirements

• Python 3.11+
• ffmpeg available on PATH
• For local transcription: install the local extra of cykk-audio-transcriber
• For OpenAI transcription: install the api extra and set OPENAI_API_KEY

Install ffmpeg separately if it is not already available on your PATH. On Debian/Ubuntu, use sudo apt install ffmpeg; on macOS with Homebrew, use brew install ffmpeg; on Windows, install an FFmpeg build and add its bin directory to PATH.

Install from source

git clone https://github.com/cykk/audio-transcription-mcp.git
cd audio-transcription-mcp
pip install ".[local]"

To use the OpenAI transcription API instead:

pip install ".[api]"

Install from PyPI

After the package is published to PyPI, install it directly:

pip install "audio-transcription-mcp[local]"

For the OpenAI transcription API:

pip install "audio-transcription-mcp[api]"

Installing without an extra does not install either transcription backend. Local Whisper may download the selected model on first use and requires sufficient disk space and memory.

Run

audio-transcription-mcp

For backward compatibility, audiototext-mcp remains available as an alias.

The server uses MCP stdio transport. Configure the command in an MCP client such as Claude Desktop, Cursor, or another compatible host:

{
  "mcpServers": {
    "audio-transcription": {
      "command": "audio-transcription-mcp"
    }
  }
}

Tool

transcribe_file accepts a local file_path and optional model, language, task, prompt, and api_key arguments. It returns JSON containing the detected language, full text, and timestamped segments.

The server reads local files, so only configure it in clients you trust. API keys should preferably be supplied through OPENAI_API_KEY rather than tool arguments. With an API key, the selected audio is sent to the OpenAI API. Without one, transcription runs locally using Whisper; the model may be downloaded on first use.

Verify

After adding the server to an MCP client, call transcribe_file with a readable local audio or video file path. A successful response contains the detected language, full transcript, and timestamped segments.

To verify the package before configuring an MCP client, run:

python -c "import asyncio; from audiototext_mcp.server import mcp; print([tool.name for tool in asyncio.run(mcp.list_tools())])"

The command should include transcribe_file. A real transcription also requires an installed local Whisper extra or a valid OPENAI_API_KEY for the API extra.

Related Product

MP3ToText is a browser-based audio and video transcription product. This MCP server runs independently and does not use the MP3ToText service.

License

MIT