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simple-asr-mcp

by Selentar

simple-asr-mcp

Minimal MCP server for local speech recognition using faster-whisper. Runs on CPU, no cloud required.

Русская версия

Installation

pipx install simple-asr-mcp

Or with pip:

pip install simple-asr-mcp

Related MCP server: claude-voice-input

Requirements

  • Python 3.10+

  • ffmpeg (required by faster-whisper for audio decoding)

On Windows, install ffmpeg via winget:

winget install Gyan.FFmpeg

Quick Setup (for Claude Code agents)

Run these two commands — no user interaction required:

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

# 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:

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 Formats

Any format supported by ffmpeg: wav, mp3, flac, ogg, m4a, wma, etc.

License

MIT

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