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Voice Recorder MCP Server

by DefiBax
GitHub
Python
MIT License
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local-only server

The server can only run on the client’s local machine because it depends on local resources.

Integrations

  • Provides installation support via GitHub repository, allowing users to clone and install the voice-recorder-mcp from DefiBax's GitHub account

  • Uses OpenAI's Whisper model for audio transcription, enabling conversion of recorded voice to text with different model sizes for varying accuracy and performance needs

Voice Recorder MCP Server

An MCP server for recording audio and transcribing it using OpenAI's Whisper model. Designed to work as a Goose custom extension or standalone MCP server.

Features

  • Record audio from the default microphone
  • Transcribe recordings using Whisper
  • Integrates with Goose AI agent as a custom extension
  • Includes prompts for common recording scenarios

Installation

# Install from source git clone https://github.com/DefiBax/voice-recorder-mcp.git cd voice-recorder-mcp pip install -e .

Usage

As a Standalone MCP Server

# Run with default settings (base.en model) voice-recorder-mcp # Use a specific Whisper model voice-recorder-mcp --model medium.en # Adjust sample rate voice-recorder-mcp --sample-rate 44100

Testing with MCP Inspector

The MCP Inspector provides an interactive interface to test your server:

# Install the MCP Inspector npm install -g @modelcontextprotocol/inspector # Run your server with the inspector npx @modelcontextprotocol/inspector voice-recorder-mcp

With Goose AI Agent

  1. Open Goose and go to Settings > Extensions > Add > Command Line Extension
  2. Set the name to voice-recorder
  3. In the Command field, enter the full path to the voice-recorder-mcp executable:
    /full/path/to/voice-recorder-mcp
    Or for a specific model:
    /full/path/to/voice-recorder-mcp --model medium.en
    To find the path, run:
    which voice-recorder-mcp
  4. No environment variables are needed for basic functionality
  5. Start a conversation with Goose and introduce the recorder with: "I want you to take action from transcriptions returned by voice-recorder. For example, if I dictate a calculation like 1+1, please return the result."

Available Tools

  • start_recording: Start recording audio from the default microphone
  • stop_and_transcribe: Stop recording and transcribe the audio to text
  • record_and_transcribe: Record audio for a specified duration and transcribe it

Whisper Models

This extension supports various Whisper model sizes:

ModelSpeedAccuracyMemory UsageUse Case
tiny.enFastestLowestMinimalTesting, quick transcriptions
base.enFastGoodLowEveryday use (default)
small.enMediumBetterModerateGood balance
medium.enSlowHighHighImportant recordings
largeSlowestHighestVery HighCritical transcriptions

The .en suffix indicates models specialized for English, which are faster and more accurate for English content.

Requirements

  • Python 3.12+
  • An audio input device (microphone)

Configuration

You can configure the server using environment variables:

# Set Whisper model export WHISPER_MODEL=small.en # Set audio sample rate export SAMPLE_RATE=44100 # Set maximum recording duration (seconds) export MAX_DURATION=120 # Then run the server voice-recorder-mcp

Troubleshooting

Common Issues

  • No audio being recorded: Check your microphone permissions and settings
  • Model download errors: Ensure you have a stable internet connection for the initial model download
  • Integration with Goose: Make sure the command path is correct
  • Audio quality issues: Try adjusting the sample rate (default: 16000)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

This server cannot be installed

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

Enables recording audio from a microphone and transcribing it using OpenAI's Whisper model. Works as both a standalone MCP server and a Goose AI agent extension.

  1. Features
    1. Installation
      1. Usage
        1. As a Standalone MCP Server
          1. Testing with MCP Inspector
            1. With Goose AI Agent
            2. Available Tools
              1. Whisper Models
                1. Requirements
                  1. Configuration
                    1. Troubleshooting
                      1. Common Issues
                      2. Contributing
                        1. License

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