mcp-suno 2026.3.19.9

MCP Server for Suno AI Music Generation via AceDataCloud API

MCP Suno

A Model Context Protocol (MCP) server for AI music generation using Suno through the AceDataCloud API.

Generate AI music, lyrics, and manage audio projects directly from Claude, VS Code, or any MCP-compatible client.

Features

• Music Generation - Create AI-generated songs from text prompts
• Custom Lyrics & Style - Full control over lyrics, title, and music style
• Song Extension - Continue existing songs from any timestamp
• Cover/Remix - Create cover versions with different styles
• Lyrics Generation - Generate structured lyrics from descriptions
• Persona Management - Save and reuse voice styles
• Task Tracking - Monitor generation progress and retrieve results

Quick Start

1. Get Your API Token

1. Sign up at AceDataCloud Platform
2. Go to the API documentation page
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://suno.mcp.acedata.cloud/mcp

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

Claude Desktop

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

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

VS Code (Copilot)

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

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

Or install the Ace Data Cloud MCP extension for VS Code, which bundles all 11 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": {
    "suno": {
      "url": "https://suno.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

cURL Test

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

# MCP initialize
curl -X POST https://suno.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-suno
# or
uvx mcp-suno

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

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

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

Claude Desktop (Local)

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

Docker (Self-Hosting)

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

Clients 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	Generate music from a text prompt (Inspiration Mode)
generate_custom_music	Generate with custom lyrics, title, and style
extend_music	Extend an existing song from a timestamp
cover_music	Create a cover/remix version
concat_music	Merge extended segments into complete audio
generate_with_persona	Generate using a saved voice style
remaster_music	Remaster an existing song to improve audio quality
stems_music	Separate a song into individual stems (vocals/instruments)
replace_section	Replace a specific time range with new generated content
upload_extend	Extend uploaded audio with new AI-generated content
upload_cover	Create an AI cover of uploaded audio
mashup_music	Create a mashup by blending multiple songs together

Lyrics

Tool	Description
generate_lyrics	Generate song lyrics from a prompt
mashup_lyrics	Generate mashup lyrics by combining two sets of lyrics
optimize_style	Optimize a style description for better generation results

Media Conversion

Tool	Description
get_mp4	Get an MP4 video version of a generated song
get_wav	Get lossless WAV format of a generated song
get_midi	Get MIDI data extracted from a generated song
get_timing	Get timing and subtitle data for a generated song
extract_vocals	Extract the vocal track from a generated song

Persona

Tool	Description
create_persona	Save a voice style for reuse

Upload

Tool	Description
upload_audio	Upload an external audio file for use in subsequent operations

Tasks

Tool	Description
get_task	Query a single task status
get_tasks_batch	Query multiple tasks at once

Information

Tool	Description
list_models	List available Suno models
list_actions	List available API actions
get_lyric_format_guide	Get lyrics formatting guide

Usage Examples

Generate Music from Prompt

User: Create a happy birthday song

Claude: I'll generate a birthday song for you.
[Calls generate_music with prompt="A happy birthday celebration song"]

Generate with Custom Lyrics

User: Create a rock song with these lyrics:
[Verse]
Thunder in the night
Electric soul ignite
[Chorus]
We are the storm

Claude: I'll create a rock song with your lyrics.
[Calls generate_custom_music with lyrics, title="Storm", style="rock, powerful"]

Extend a Song

User: Continue this song from the 2-minute mark with a bridge section

Claude: I'll extend the song with a bridge.
[Calls extend_music with audio_id, continue_at=120, lyric="[Bridge]..."]

Available Models

Model	Version	Max Duration	Features
chirp-v5	V5	8 minutes	Latest, best quality
chirp-v4-5-plus	V4.5+	8 minutes	Enhanced quality
chirp-v4-5	V4.5	4 minutes	Vocal gender control
chirp-v4	V4	150 seconds	Stable
chirp-v3-5	V3.5	120 seconds	Fast
chirp-v3	V3	120 seconds	Legacy

Vocal Gender Control (v4.5+ only):

• f - Female vocals
• m - Male vocals

Configuration

Environment Variables

Variable	Description	Default
ACEDATACLOUD_API_TOKEN	API token from AceDataCloud	Required
ACEDATACLOUD_API_BASE_URL	API base URL	https://api.acedata.cloud
SUNO_DEFAULT_MODEL	Default model for generation	chirp-v4-5
SUNO_REQUEST_TIMEOUT	Request timeout in seconds	1800
LOG_LEVEL	Logging level	INFO

Command Line Options

mcp-suno --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/mcp-suno.git
cd mcp-suno

# 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

MCPSuno/
├── core/                   # Core modules
│   ├── __init__.py
│   ├── client.py          # HTTP client for Suno API
│   ├── config.py          # Configuration management
│   ├── exceptions.py      # Custom exceptions
│   ├── server.py          # MCP server initialization
│   └── utils.py           # Utility functions
├── tools/                  # MCP tool definitions
│   ├── __init__.py
│   ├── audio_tools.py     # Audio generation tools
│   ├── info_tools.py      # Information tools
│   ├── lyrics_tools.py    # Lyrics generation tools
│   ├── media_tools.py     # Media conversion tools
│   ├── persona_tools.py   # Persona management tools
│   └── task_tools.py      # Task query tools
├── 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
├── .gitignore
├── 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

API Reference

This server wraps the AceDataCloud Suno API:

• Suno Audios API - Music generation
• Suno Lyrics API - Lyrics generation
• Suno Tasks API - Task queries
• Suno Persona API - Persona management

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
• Suno Official
• Model Context Protocol
• MCP Python SDK

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Made with love by AceDataCloud