audiogen-mcp 0.2.1

MCP server for generating sound effects using Meta's AudioGen

AudioGen MCP Server

An MCP server that generates sound effects from text descriptions using Meta's AudioGen model. Designed for Apple Silicon Macs.

Prerequisites

• macOS with Apple Silicon (M1/M2/M3/M4)
• Python 3.9-3.11 (3.12+ not yet supported by audiocraft)
• ffmpeg: brew install ffmpeg
• ~4GB disk space for model weights
• ~8GB RAM recommended

Installation

Due to audiocraft's complex dependencies (xformers doesn't build on Apple Silicon), installation requires a specific order:

# Create virtual environment with Python 3.11
uv venv ~/.audiogen-env --python 3.11
source ~/.audiogen-env/bin/activate

# Install audiocraft without its problematic dependencies
uv pip install audiocraft --no-deps

# Install the actual dependencies (skipping xformers)
uv pip install torch torchaudio transformers huggingface_hub encodec einops \
    flashy num2words sentencepiece librosa av julius spacy torchmetrics \
    hydra-core hydra-colorlog demucs lameenc

# Install audiogen-mcp
uv pip install audiogen-mcp

The first run will download the AudioGen model (~2GB).

Configure Claude Code

claude mcp add audiogen ~/.audiogen-env/bin/python -- -m audiogen_mcp.server

Or add to ~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "audiogen": {
      "command": "/Users/YOUR_USERNAME/.audiogen-env/bin/python",
      "args": ["-m", "audiogen_mcp.server"]
    }
  }
}

Available Tools

Tool	Description
generate_sound_effect	Start a background generation job, returns job_id
check_generation_status	Poll job status by job_id until completed
list_generation_jobs	List all jobs and their current status
list_generated_sounds	List previously generated audio files
get_model_status	Check if model is loaded and device info

How It Works

Generation runs in the background to avoid timeouts:

1. Call generate_sound_effect with your prompt → returns job_id
2. Poll check_generation_status with the job_id every 10-15 seconds
3. When status is completed, the result includes file_path

Example Prompts

Once configured, ask Claude Code to generate sounds:

• "Generate an explosion sound effect"
• "Create a dark ambient tension drone, 10 seconds"
• "Make a retro 8-bit power-up sound, 2 seconds long"
• "Generate footsteps on gravel, 5 seconds"

Prompt Tips

For best results, be specific:

# Good
"glass breaking, single wine glass falling on tile floor"
"8-bit arcade explosion, retro game style"
"dark ambient tension drone, synth pad, ominous low frequency rumble"

# Less good
"glass sound"
"explosion"
"ambient"

Include style, mood, and context for better results.

Performance

• ~18 seconds to generate 1 second of audio on Apple Silicon
• 5 seconds of audio ≈ 90 seconds generation time
• 10 seconds of audio ≈ 180 seconds generation time
• First generation takes longer (model loading ~5s)
• Uses Metal Performance Shaders (MPS) for GPU acceleration

Output

Generated files save to ~/audiogen_outputs/ by default as WAV or OGG files.

Troubleshooting

Installation fails with xformers error

This is expected on Apple Silicon. The server mocks xformers at runtime since it's only needed for CUDA. If audiocraft installation fails, try:

uv pip install torch torchaudio
uv pip install audiocraft --no-build-isolation

Model download fails

Ensure stable internet and sufficient disk space. The model downloads from HuggingFace Hub.

Slow generation

Check device with get_model_status tool. CPU fallback is 10-20x slower than MPS.

MPS not available

Requires macOS 12.3+ and PyTorch 2.0+.

License

MIT License - see LICENSE file.

Acknowledgments

• Meta AudioCraft - The underlying AI model
• MCP - Model Context Protocol specification