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.
- 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
- Sign up at AceDataCloud Platform
- Go to the API documentation page
- Click "Acquire" to get your API token
- Copy the token for use below
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.
Connect directly on Claude.ai with OAuth — no API token needed:
- Go to Claude.ai Settings → Integrations → Add More
- Enter the server URL:
https://suno.mcp.acedata.cloud/mcp - Complete the OAuth login flow
- Start using the tools in your conversation
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"
}
}
}
}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"
}
}
}
}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.
- Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
- Click Add → HTTP
- Paste:
{
"mcpServers": {
"suno": {
"url": "https://suno.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}Claude Code supports MCP servers natively:
claude mcp add suno --transport http https://suno.mcp.acedata.cloud/mcp \
-h "Authorization: Bearer YOUR_API_TOKEN"Or add to your project's .mcp.json:
{
"mcpServers": {
"suno": {
"type": "streamable-http",
"url": "https://suno.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}Add to Cline's MCP settings (.cline/mcp_settings.json):
{
"mcpServers": {
"suno": {
"type": "streamable-http",
"url": "https://suno.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}Add to your MCP configuration:
{
"mcpServers": {
"suno": {
"type": "streamable-http",
"url": "https://suno.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}Add to Roo Code MCP settings:
{
"mcpServers": {
"suno": {
"type": "streamable-http",
"url": "https://suno.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}Add to .continue/config.yaml:
mcpServers:
- name: suno
type: streamable-http
url: https://suno.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"Add to Zed's settings (~/.config/zed/settings.json):
{
"language_models": {
"mcp_servers": {
"suno": {
"url": "https://suno.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
}# 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"}}}'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{
"mcpServers": {
"suno": {
"command": "uvx",
"args": ["mcp-suno"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}docker pull ghcr.io/acedatacloud/mcp-suno:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-suno:latestClients connect with their own Bearer token — the server extracts the token from each request's Authorization header.
| 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 |
| 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 |
| 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 |
| Tool | Description |
|---|---|
create_persona |
Save a voice style for reuse |
| Tool | Description |
|---|---|
upload_audio |
Upload an external audio file for use in subsequent operations |
| Tool | Description |
|---|---|
get_task |
Query a single task status |
get_tasks_batch |
Query multiple tasks at once |
| Tool | Description |
|---|---|
list_models |
List available Suno models |
list_actions |
List available API actions |
get_lyric_format_guide |
Get lyrics formatting guide |
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"]
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"]
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]..."]
| Model | Version | Max Duration | Features |
|---|---|---|---|
chirp-v5-5 |
V5.5 | 8 minutes | Latest, best quality |
chirp-v5 |
V5 | 8 minutes | High 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-v3-0 |
V3 | 120 seconds | Legacy |
Vocal Gender Control (v4.5+ only):
f- Female vocalsm- Male vocals
| Variable | Description | Default |
|---|---|---|
ACEDATACLOUD_API_TOKEN |
API token from AceDataCloud | Required |
ACEDATACLOUD_API_BASE_URL |
API base URL | https://api.acedata.cloud |
ACEDATACLOUD_OAUTH_CLIENT_ID |
OAuth client ID (hosted mode) | — |
ACEDATACLOUD_PLATFORM_BASE_URL |
Platform base URL | https://platform.acedata.cloud |
SUNO_DEFAULT_MODEL |
Default model for generation | chirp-v5-5 |
SUNO_REQUEST_TIMEOUT |
Request timeout in seconds | 1800 |
LOG_LEVEL |
Logging level | INFO |
mcp-suno --help
Options:
--version Show version
--transport Transport mode: stdio (default) or http
--port Port for HTTP transport (default: 8000)# 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 unit tests
pytest
# Run with coverage
pytest --cov=core --cov=tools
# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core tools# Install build dependencies
pip install -e ".[release]"
# Build package
python -m build
# Upload to PyPI
twine upload dist/*SunoMCP/
├── 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
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
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
MIT License - see LICENSE for details.
Made with love by AceDataCloud