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MCP-Audio Plugin

by AIO-2030

MCP-Audio Plugin

mcp-audio is an AIO-2030 compliant MCP plugin that performs voice-to-text transcription using the Audio speech recognition API.

It exposes the identify_voice method via both multipart/form-data and base64 formats, supports the AIO tools.call protocol, and returns JSON-RPC structured outputs.


Features

  • Fully AIO-compliant MCP plugin (/tools.call, /help)
  • Converts .wav/.mp3 audio files to transcripts using SiliconFlow
  • API key managed securely via .env file
  • Docker-compatible and minimal dependencies
  • Registration-ready for AIO endpoint registry

Setup (Local)

1. Clone and Install

git clone git@github.com:AIO-2030/mcp-audio.git cd mcp-audio python -m venv venv && source venv/bin/activate pip install -r requirements.txt

2. Add .env file

cp .env.example .env

Set your audio URL and API key:

AUDIO_URL=https--xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

3. Run the MCP server

python src/mcp_server.py

4. Docker

4.1 Build and Run
docker build -t mcp-audio . docker run --env-file .env -p 8080:8080 mcp-audio

API Overview

POST /api/v1/mcp/voice_model

Upload audio file directly. Response:

{ "transcript": "hello world", "confidence": 0.91, "audio_hash": "a1b2c3..." }

POST /api/v1/mcp/tools.call (AIO Protocol)

JSON-RPC format with base64-encoded audio. Response:

{ "method": "tools.call", "params": { "method": "identify_voice", "inputs": [ { "type": "audio", "value": "<base64-audio>" } ] } }

GET /api/v1/mcp/help

Auto-serves contents of mcp_audio_registration.json. Used by Queen AI for MCP discovery and service indexing.

Testing Tools

Base64 Voice Test

python test/test_audio_base64.py

Health Check

python health_check.py

MCP Registration (to AIO Endpoint Canister)

./register_mcp.sh

Requires jq, dfx, and a running endpoint_registry canister.

-
security - not tested
A
license - permissive license
-
quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A voice-to-text transcription service that converts audio files to transcripts using SiliconFlow, supporting both multipart/form-data and base64 formats.

  1. Features
    1. Setup (Local)
      1. 1. Clone and Install
      2. 2. Add .env file
      3. 3. Run the MCP server
      4. 4. Docker
    2. API Overview
      1. POST /api/v1/mcp/voice_model
      2. POST /api/v1/mcp/tools.call (AIO Protocol)
      3. GET /api/v1/mcp/help
    3. Testing Tools
      1. Base64 Voice Test
      2. Health Check
    4. MCP Registration (to AIO Endpoint Canister)

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