ProducerMCP

ProducerMCP

A Model Context Protocol (MCP) server for AI music generation using Producer/Riffusion (FUZZ models) through the AceDataCloud API.

Generate AI music directly from Claude, VS Code, or any MCP-compatible client.

Features

• Text to Music - Create AI-generated music from text prompts
• Custom Music - Full control with custom lyrics, title, and style
• Song Extension - Continue songs from any timestamp
• Cover/Remix - Create covers in different genres and styles
• Variations - Generate alternative versions of songs
• Vocal/Instrumental Swap - Mix vocals and instrumentals between songs
• Section Replacement - Re-generate specific sections of a song
• Stem Separation - Split songs into vocal and instrumental tracks
• Lyrics Generation - Generate structured lyrics from prompts
• Video Generation - Create music videos for songs
• WAV Export - Get lossless audio format
• 8 FUZZ Models - From FUZZ-0.8 to FUZZ-2.0 Pro

Tool Reference

Quick Start

1. Get Your API Token

1. Sign up at AceDataCloud Platform
2. Navigate to the API documentation
3. Click "Acquire" to get your API token
4. Copy the token for use below

2. Use the Hosted Server (Recommended)

AceDataCloud hosts a managed MCP server -- no local installation required.

Endpoint: https://producer.mcp.acedata.cloud/mcp

All requests require a Bearer token. Use the API token from Step 1.

Claude.ai

Connect directly on Claude.ai with OAuth -- no API token needed:

1. Go to Claude.ai Settings > Integrations > Add More
2. Enter the server URL: https://producer.mcp.acedata.cloud/mcp
3. Complete the OAuth login flow
4. Start using the tools in your conversation

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "producer": {
      "type": "streamable-http",
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cursor / Windsurf

Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):

{
  "mcpServers": {
    "producer": {
      "type": "streamable-http",
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

{
  "servers": {
    "producer": {
      "type": "streamable-http",
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Or install the Ace Data Cloud MCP extension for VS Code, which bundles all MCP servers with one-click setup.

JetBrains IDEs

1. Go to Settings > Tools > AI Assistant > Model Context Protocol (MCP)
2. Click Add > HTTP
3. Paste:

{
  "mcpServers": {
    "producer": {
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

claude mcp add producer --transport http https://producer.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

Or add to your project's .mcp.json:

{
  "mcpServers": {
    "producer": {
      "type": "streamable-http",
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cline

Add to Cline's MCP settings (.cline/mcp_settings.json):

{
  "mcpServers": {
    "producer": {
      "type": "streamable-http",
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Amazon Q Developer

Add to your MCP configuration:

{
  "mcpServers": {
    "producer": {
      "type": "streamable-http",
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Roo Code

Add to Roo Code MCP settings:

{
  "mcpServers": {
    "producer": {
      "type": "streamable-http",
      "url": "https://producer.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Continue.dev

Add to .continue/config.yaml:

mcpServers:
  - name: producer
    type: streamable-http
    url: https://producer.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

Zed

Add to Zed's settings (~/.config/zed/settings.json):

{
  "language_models": {
    "mcp_servers": {
      "producer": {
        "url": "https://producer.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

# Health check (no auth required)
curl https://producer.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://producer.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

# Install from PyPI
pip install mcp-producer
# or
uvx mcp-producer

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-producer

# Run (HTTP mode for remote access)
mcp-producer --transport http --port 8000

Claude Desktop (Local)

{
  "mcpServers": {
    "producer": {
      "command": "uvx",
      "args": ["mcp-producer"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

docker pull ghcr.io/acedatacloud/mcp-producer:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-producer:latest

Clients connect with their own Bearer token -- the server extracts the token from each request's Authorization header.

Available Tools

Music Generation

Vocal/Instrumental

Lyrics

Media

Tasks

Information

Usage Examples

Generate Music from Prompt

User: Create a jazz song about rainy nights

Claude: I'll generate a jazz song for you.
[Calls producer_generate_music with prompt="Smooth jazz song about rainy nights, saxophone, piano, moody"]

Custom Song with Lyrics

User: Here are my lyrics:
[Verse] Walking in the rain...
[Chorus] But I keep moving on...

Claude: I'll create a song with your lyrics.
[Calls producer_generate_custom_music with lyrics, title, and style]

Extend a Song

User: Make this song longer with another verse

Claude: I'll extend the song from where it left off.
[Calls producer_extend_music with audio_id, continue_at, and new lyrics]

Create a Cover

User: Make an acoustic version of this song

Claude: I'll create an acoustic cover.
[Calls producer_cover_music with audio_id and style="acoustic folk, gentle guitar"]

Available Models

Configuration

Environment Variables

Command Line Options

mcp-producer --help

Options:
  --version          Show version
  --transport        Transport mode: stdio (default) or http
  --port             Port for HTTP transport (default: 8000)

Development

Setup Development Environment

# Clone repository
git clone https://github.com/AceDataCloud/ProducerMCP.git
cd ProducerMCP

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # or `.venv\Scripts\activate` on Windows

# Install with dev dependencies
pip install -e ".[dev,test]"

Run Tests

# Run unit tests
pytest

# Run with coverage
pytest --cov=core --cov=tools

# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration

Code Quality

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools

Build & Publish

# Install build dependencies
pip install -e ".[release]"

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Project Structure

ProducerMCP/
├── core/                   # Core modules
│   ├── __init__.py
│   ├── client.py          # HTTP client for Producer API
│   ├── config.py          # Configuration management
│   ├── exceptions.py      # Custom exceptions
│   ├── oauth.py           # OAuth 2.1 provider
│   ├── server.py          # MCP server initialization
│   ├── types.py           # Type definitions (models, actions)
│   └── utils.py           # Utility functions
├── tools/                  # MCP tool definitions
│   ├── __init__.py
│   ├── audio_tools.py     # Audio generation tools (9 tools)
│   ├── lyrics_tools.py    # Lyrics generation
│   ├── media_tools.py     # Upload, video, WAV tools
│   ├── task_tools.py      # Task query tools
│   └── info_tools.py      # Information tools
├── prompts/                # MCP prompts
│   └── __init__.py        # Prompt templates
├── tests/                  # Test suite
│   ├── conftest.py
│   ├── test_client.py
│   ├── test_config.py
│   ├── test_integration.py
│   └── test_utils.py
├── deploy/                 # Deployment configs
│   └── production/
│       ├── deployment.yaml
│       ├── ingress.yaml
│       └── service.yaml
├── .env.example           # Environment template
├── .ruff.toml             # Ruff linter config
├── CHANGELOG.md
├── Dockerfile             # Docker image for HTTP mode
├── docker-compose.yaml    # Docker Compose config
├── LICENSE
├── main.py                # Entry point
├── pyproject.toml         # Project configuration
└── README.md

Contributing

Contributions are welcome! Please:

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

License

MIT License - see LICENSE for details.

Links

• AceDataCloud Platform
• Riffusion
• Model Context Protocol
• MCP Python SDK

Made with love by AceDataCloud