pmerwin/audio-transcription-mcp

Audio Transcription MCP Server

Real-time audio transcription using OpenAI Whisper. Capture and transcribe system audio (meetings, videos, music) automatically with AI assistance through Cursor or Claude Desktop.

✨ Features

• 🎤 Real-time transcription - Captures and transcribes audio as it plays
• 🔄 Zero installation - Use with npx, no global install needed
• 🤖 AI-powered - Uses OpenAI's Whisper API for accurate transcription
• 📝 Timestamped transcripts - Every entry is timestamped in markdown format
• 🔒 Session isolation - Each session gets its own unique transcript file
• ⚡ Smart silence detection - Automatically pauses when no audio detected
• 🎯 Automated setup - One command sets up audio routing
• 🧪 Built-in testing - Verify your setup before starting

🚀 Quick Start (5 Minutes)

Step 1: Run Automated Setup

The setup script installs everything you need and guides you through configuration:

npx audio-transcription-mcp setup

What this does:

• ✅ Installs Homebrew (if needed)
• ✅ Installs ffmpeg for audio processing
• ✅ Installs BlackHole virtual audio driver
• ✅ Guides you through creating a Multi-Output Device (or does it automatically!)
• ✅ Takes 5 minutes, mostly automated

First time? The script will walk you through everything with clear instructions. Don't worry if it asks for your Mac password - that's normal for installing software!

Step 2: Test Your Setup

Verify everything works before using it:

npx audio-transcription-mcp test

This captures 5 seconds of audio and shows you if it's working correctly.

Step 3: Configure Your AI Assistant

Add to your Cursor or Claude Desktop config:

{
  "mcpServers": {
    "audio-transcription": {
      "command": "npx",
      "args": ["-y", "audio-transcription-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-your-key-here",
        "INPUT_DEVICE_NAME": "BlackHole"
      }
    }
  }
}

{
  "mcpServers": {
    "audio-transcription": {
      "command": "npx",
      "args": ["-y", "audio-transcription-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-your-key-here",
        "INPUT_DEVICE_NAME": "BlackHole",
        "OUTFILE_DIR": "/Users/yourname/Documents/Transcripts"
      },
      "allowedDirectories": [
        "/Users/yourname/Documents/Transcripts"
      ]
    }
  }
}

Step 4: Set System Output

Go to System Settings > Sound > Output and select "Multi-Output Device"

This routes audio to both your speakers (so you can hear) and BlackHole (for transcription).

Step 5: Start Transcribing!

In Cursor or Claude Desktop, just ask:

"Start transcribing audio"

Your AI assistant will start capturing and transcribing audio in real-time!

📖 What You Need

• macOS 10.15+ (Catalina or later)
• OpenAI API key - Get one here (pay-as-you-go, ~$0.36/hour - see detailed costs)
• 5 minutes for setup

🎯 Use Cases

• Meeting transcription - Zoom, Google Meet, Teams calls
• Content creation - Transcribe videos, podcasts, or music
• Accessibility - Real-time captions for any audio
• Note-taking - Automatic transcripts of lectures or presentations
• Research - Transcribe interviews or focus groups

🔧 Troubleshooting

Audio Not Being Captured

Problem: Test shows silent or very low audio levels

Solution:

1. Check System Settings > Sound > Output is set to "Multi-Output Device"
2. Open Audio MIDI Setup and verify both outputs are checked:
   • ☑ Built-in Output
   • ☑ BlackHole 2ch
3. Play some audio and run npx audio-transcription-mcp test again

BlackHole Not Showing Up

Problem: BlackHole doesn't appear in device list

Solution: Restart your Mac. Audio drivers require a restart to be recognized by the system.

Setup Script Fails

Problem: Automated setup doesn't work

Solution: The script will fall back to manual mode with clear instructions. This is normal on first run if accessibility permissions aren't granted. Just follow the 4-step guide shown.

Want to Start Over?

If you need to remove everything and start fresh:

# Uninstall BlackHole and ffmpeg
brew uninstall blackhole-2ch ffmpeg

# Delete Multi-Output Device
# 1. Open Audio MIDI Setup
# 2. Select "Multi-Output Device" in left sidebar
# 3. Press Delete key

# Then run setup again
npx audio-transcription-mcp setup

Need More Help?

• 📖
• 🐛 Report an Issue
• 💬 Discussions

📚 Additional Documentation

🛠️ Advanced Usage

Standalone CLI Mode

You can use this as a standalone CLI without MCP:

# Start transcription (saves to meeting_transcript.md)
npx audio-transcription-mcp start

# Press Ctrl+C to stop

Configure via .env file:

OPENAI_API_KEY=sk-your-key-here
INPUT_DEVICE_NAME=BlackHole
CHUNK_SECONDS=8
OUTFILE=meeting_transcript.md

MCP Server Tools

When used with Cursor or Claude Desktop, these tools are available:

• start_transcription - Start capturing and transcribing audio
• pause_transcription - Pause transcription temporarily
• resume_transcription - Resume after pause
• stop_transcription - Stop and get session stats
• get_status - Check if transcription is running
• get_transcript - Retrieve current transcript content
• clear_transcript - Clear and start fresh
• cleanup_transcript - Delete transcript file

Configuration Options

Environment variables you can customize:

🏗️ How It Works

1. Audio Routing: Multi-Output Device sends system audio to both your speakers and BlackHole
2. Capture: ffmpeg captures audio from BlackHole in 8-second chunks
3. Processing: Audio is converted to WAV format suitable for Whisper API
4. Transcription: Each chunk is sent to OpenAI Whisper for transcription
5. Output: Timestamped text is appended to a markdown file in real-time
6. Silence Detection: Automatically pauses after 32 seconds of silence to save API costs

💰 Costs & Performance

What You're Paying For

You ONLY pay for OpenAI Whisper API calls - everything else runs locally for free!

✅ FREE (runs locally on your machine):

• Audio capture with ffmpeg
• Audio processing and buffer management
• Silence detection and level analysis
• File operations (writing/reading transcripts)
• All MCP server operations

💰 PAID (OpenAI API):

• Only the transcription API calls to OpenAI Whisper
• $0.006 per minute of audio transcribed
• Silent chunks are automatically skipped to save money

Actual Costs

With default 8-second chunks:

Cost per chunk: ~$0.0008 (less than a tenth of a cent!)

Built-in Cost Savings

The tool includes smart silence detection that saves you money:

• 🔇 Silent audio chunks are NEVER sent to OpenAI
• 💰 Automatically tracks cost savings in the debug log
• ⏸️ Auto-pauses after 32 seconds of silence
• 📊 View statistics with get_status to see chunks skipped

Example: In a 1-hour meeting with 15 minutes of silence, you save ~$0.09 automatically!

Performance

• Memory usage: 50-100 MB per session
• CPU usage: Minimal (ffmpeg handles audio processing)
• API latency: 1-3 seconds per chunk
• Accuracy: 90-95% for clear speech
• Network: Only during transcription API calls

Cost Optimization Tips

1. Increase chunk size - Fewer API calls (set CHUNK_SECONDS=15)
2. Use silence detection - Enabled by default, saves money automatically
3. Pause when not needed - Use pause_transcription during breaks
4. Monitor usage - Check OpenAI dashboard for actual costs

Bottom line: Transcription is cheap (~36¢/hour), runs mostly locally, and automatically saves money by skipping silence. You're only charged when actual speech is being transcribed.

🧪 Development & Testing

For contributors and developers:

📖 See for complete setup instructions

Just add to your config and restart - that's it!

See the npx configuration at the top of this README for Cursor and Claude Desktop.

For Standalone CLI (Local Development)

📖 See for complete setup instructions

# Install dependencies
npm install
npm run build

# Configure environment
cp env.example .env  # Then add your OpenAI API key

# Run standalone CLI
npm start

📄 License & Contributing

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

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

Development Resources

• 📖
• 🧪
• 📋
• 🔧

Made with ❤️ for transcribing meetings, content, and conversations.

Star ⭐ this repo if you find it useful!