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MCP server for generating sound effects using Meta's AudioGen

Project description

AudioGen MCP Server

PyPI version License: MIT

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

uvx audiogen-mcp

That's it. The first run will download the AudioGen model (~2GB), which takes about 2 minutes.

Configure Claude Code

Option 1: CLI (Recommended)

claude mcp add audiogen uvx -- audiogen-mcp

Option 2: Manual JSON Configuration

Add to ~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "audiogen": {
      "command": "uvx",
      "args": ["audiogen-mcp"]
    }
  }
}

Available Tools

Tool Description
generate_sound_effect Generate a single sound effect from text
generate_batch_sound_effects Generate multiple sounds at once
list_generated_sounds List previously generated files
get_model_status Check model and device status

Example Prompts

Once configured, ask Claude Code to generate sounds:

  • "Generate an explosion sound effect"
  • "Create UI sounds: click, hover, and error"
  • "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"
"button click, soft, satisfying UI sound"

# Less good
"glass sound"
"explosion"
"click"

Include style, mood, and context for better results.

Performance

  • ~60 seconds to generate 5 seconds of audio
  • First generation takes longer (model loading)
  • Uses Metal Performance Shaders (MPS) for GPU acceleration

Output

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

Troubleshooting

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

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