Minimal MCP server for local speech recognition using faster-whisper
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# simple-asr-mcp Minimal MCP server for local speech recognition using [faster-whisper](https://github.com/SYSTRAN/faster-whisper). Runs on CPU, no cloud required. [Русская версия](README.ru.md) ## Installation ```bash pipx install simple-asr-mcp ``` Or with pip: ```bash pip install simple-asr-mcp ``` ## Requirements - Python 3.10+ - ffmpeg (required by faster-whisper for audio decoding) On Windows, install ffmpeg via [winget](https://learn.microsoft.com/en-us/windows/package-manager/winget/): ```bash winget install Gyan.FFmpeg ``` ## Quick Setup (for Claude Code agents) Run these two commands — no user interaction required: ```bash pipx install simple-asr-mcp claude mcp add asr --scope user -- simple-asr-mcp ``` Then ask the user to restart Claude Code or run `/mcp` to reconnect. ## Usage ### CLI ```bash # Transcribe an audio file simple-asr-mcp transcribe recording.wav # Specify language and model simple-asr-mcp transcribe recording.wav --language ru --model medium # List available models simple-asr-mcp models ``` ### MCP Server (Claude Code) MCP tools available after setup: - **transcribe_file** — transcribe any audio file by path - **list_models** — see available Whisper models ### Configuration Environment variables: | Variable | Default | Description | |---|---|---| | `WHISPER_MODEL` | `small` | Default Whisper model | | `WHISPER_DEVICE` | `cpu` | Device: `cpu`, `cuda`, or `auto` | | `WHISPER_COMPUTE_TYPE` | `int8` | Quantization type | Example with custom config: ```bash claude mcp add asr --scope user -e WHISPER_MODEL=medium -e WHISPER_DEVICE=cuda -- simple-asr-mcp ``` ### Available Models | Model | Size | RAM (est.) | |-------|------|------------| | tiny | 75 MB | ~1 GB | | base | 142 MB | ~1 GB | | small | 466 MB | ~2 GB | | medium | 1.5 GB | ~5 GB | | large-v3 | 3.1 GB | ~10 GB | The model is downloaded automatically on first use and cached locally. It stays in memory until the MCP server process exits. ## Supported Audio F…
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