A
licenseA
qualityB
maintenanceMCP server for audio transcription using local faster-whisper or OpenAI Whisper API, enabling multilingual transcription with optional GPT post-processing.
3
160 PyPI
MIT
simple-asr-mcp
by Selentar
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
simple-asr-mcp
Minimal MCP server for local speech recognition using faster-whisper. Runs on CPU, no cloud required.
Installation
pipx install simple-asr-mcpOr with pip:
pip install simple-asr-mcpRelated 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.FFmpegQuick 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-mcpThen 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 modelsMCP 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 |
|
| Default Whisper model |
|
| Device: |
|
| Quantization type |
Example with custom config:
claude mcp add asr --scope user -e WHISPER_MODEL=medium -e WHISPER_DEVICE=cuda -- simple-asr-mcpAvailable 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.
Links
License
MIT
Tool Schema Changelog
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This server cannot be deployed
Maintenance
ActivityInactive
ResponsivenessNo recent community issues
Related MCP Connectors
MCP server for Speech-to-Text
MCP server exposing the AceDataCloud Fish Audio API (text-to-speech with voice conditioning)
MCP server for AI dialogue using various LLM models via AceDataCloud
MCP server for Text-to-Speech
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