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
Tool | Description |
| Generate AI music from a text prompt. |
| Generate music with custom lyrics, title, and style. |
| Extend an existing song from a specific timestamp. |
| Create a cover/remix version in a different style. |
| Create a variation of an existing song. |
| Swap vocals between two songs. |
| Swap instrumentals between two songs. |
| Replace a specific time range with new content. |
| Separate a song into vocal and instrumental stems. |
| Generate structured song lyrics from a prompt. |
| Upload external audio for processing. |
| Generate a music video for a song. |
| Get lossless WAV format of a song. |
| Query the status of a generation task. |
| Query multiple generation tasks at once. |
| List all available FUZZ models. |
| List all available actions and tools. |
| Get lyrics formatting guide. |
Quick Start
1. Get Your API Token
Sign up at AceDataCloud Platform
Navigate to the API documentation
Click "Acquire" to get your API token
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:
Go to Claude.ai Settings > Integrations > Add More
Enter the server URL:
https://producer.mcp.acedata.cloud/mcpComplete the OAuth login flow
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
Go to Settings > Tools > AI Assistant > Model Context Protocol (MCP)
Click Add > HTTP
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 8000Claude 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:latestClients connect with their own Bearer token -- the server extracts the token from each request's Authorization header.
Available Tools
Music Generation
Tool | Description |
| Generate music from a text prompt |
| Generate with custom lyrics and style |
| Extend a song from a timestamp |
| Create a cover in a different style |
| Create a variation of a song |
Vocal/Instrumental
Tool | Description |
| Swap vocals between two songs |
| Swap instrumentals between two songs |
| Replace a time range with new content |
| Separate into stems |
Lyrics
Tool | Description |
| Generate lyrics from a prompt |
Media
Tool | Description |
| Upload external audio |
| Generate video for a song |
| Get lossless WAV format |
Tasks
Tool | Description |
| Query a single task status |
| Query multiple tasks at once |
Information
Tool | Description |
| List available FUZZ models |
| List available API actions |
| Lyric formatting guide |
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
Model | Tier | Description |
FUZZ-2.0 Pro | Pro | Highest quality, best for professional production |
FUZZ-2.0 | Default | Recommended for most use cases (default) |
FUZZ-2.0 Raw | Raw | Unprocessed output, for custom post-processing |
FUZZ-1.1 Pro | Pro | High quality legacy model |
FUZZ-1.0 Pro | Pro | Professional legacy model |
FUZZ-1.0 | Default | Stable legacy model |
FUZZ-1.1 | Default | Improved legacy model |
FUZZ-0.8 | Legacy | Original model, basic quality |
Configuration
Environment Variables
Variable | Description | Default |
| API token from AceDataCloud | Required |
| API base URL |
|
| OAuth client ID (hosted mode) | -- |
| Platform base URL |
|
| Default FUZZ model |
|
| Request timeout in seconds |
|
| Logging level |
|
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 integrationCode Quality
# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core toolsBuild & 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.mdContributing
Contributions are welcome! Please:
Fork the repository
Create a feature branch (
git checkout -b feature/amazing)Commit your changes (
git commit -m 'Add amazing feature')Push to the branch (
git push origin feature/amazing)Open a Pull Request
License
MIT License - see LICENSE for details.
Links
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