mcp_server

FunASR MCP Server

Model Context Protocol server that gives AI assistants the ability to transcribe audio.

Setup

1. Install dependencies

pip install funasr

2. Configure your AI tool

Claude Code (~/.claude.json):

{
    "mcpServers": {
        "funasr": {
            "command": "python",
            "args": ["/path/to/examples/mcp_server/funasr_mcp.py"],
            "env": {"FUNASR_DEVICE": "cuda"}
        }
    }
}

Claude Desktop (claude_desktop_config.json):

{
    "mcpServers": {
        "funasr": {
            "command": "python",
            "args": ["/path/to/funasr_mcp.py"],
            "env": {"FUNASR_DEVICE": "cpu"}
        }
    }
}

Cursor (Settings → MCP Servers → Add):

• Command: python /path/to/funasr_mcp.py
• Environment: FUNASR_DEVICE=cuda

Tools

transcribe_audio

Transcribe a speech audio file to text.

Parameters:

Name	Type	Required	Description
audio_path	string	Yes	Path to audio file (wav, mp3, flac, m4a, ogg)
language	string	No	Language hint (auto-detected by default)

Returns: Transcribed text with timestamps and speaker labels (when available).

Example Usage

Once configured, ask your AI assistant:

• "Transcribe the meeting recording at ~/Downloads/meeting.wav"
• "What was said in this audio file? /path/to/interview.mp3"
• "Convert this voice memo to text: ~/voice_note.m4a"

Environment Variables

Variable	Default	Description
FUNASR_DEVICE	cpu	Device: cuda, cpu, or mps
FUNASR_MODEL	iic/SenseVoiceSmall	ASR model to use

Features

• 50+ languages with automatic detection
• Speaker diarization — identifies who said what
• Timestamps — per-segment timing
• 170x realtime on GPU, 17x on CPU
• No API key needed — fully local inference
• MIT licensed, privacy-friendly (audio never leaves your machine)

Verified Compatibility

Tool	Status
Claude Code	✅ Tested
Claude Desktop	✅ Compatible
Cursor	✅ Compatible
Windsurf	✅ Compatible
Any MCP client	✅ Standard protocol