How do I use IRCAM Amplify MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@IRCAM Amplify MCP Server analyze this track's genre and mood: https://soundcloud.com/artist/track.mp3" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

IRCAM Amplify MCP Server

MCP (Model Context Protocol) server for IRCAM Amplify audio processing APIs. Enables any MCP-compatible LLM to analyze music, separate stems, detect AI-generated audio, and more.

Features

Music Analysis: Extract genre, mood, tempo, key, and instruments from audio
Stem Separation: Split audio into vocals, drums, bass, and other instruments
AI Detection: Detect whether music is AI-generated or human-made
Loudness Analysis: Measure LUFS, true peak, and dynamic range
Async Job Handling: Poll long-running operations with progress tracking

Supported Audio Formats

MP3, WAV, FLAC, OGG, M4A (max 100MB)

Quick Start

Prerequisites

Node.js 18+ (download)
IRCAM Amplify API Key from app.ircamamplify.io
An MCP-compatible client (Claude Desktop, Cline, etc.)

Installation

npm install -g ircam-amplify-mcp

Or run directly with npx:

npx ircam-amplify-mcp

Configuration

1. Set your API key

export IRCAM_AMPLIFY_API_KEY="your-api-key-here"

2. Configure your MCP client

Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "ircam-amplify": {
      "command": "npx",
      "args": ["ircam-amplify-mcp"],
      "env": {
        "IRCAM_AMPLIFY_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

Tool	Description	Input	Output
`analyze_music`	Extract genre, mood, tempo, key, instruments	`audio_url`	`{ genre[], mood[], tempo, key, instruments[] }`
`separate_stems`	Split into vocals, drums, bass, other	`audio_url`	`{ vocals_url, drums_url, bass_url, other_url }` or `{ job_id }`
`detect_ai_music`	Detect AI vs human-made music	`audio_url`	`{ confidence, classification }`
`analyze_loudness`	Measure LUFS, peak, dynamic range	`audio_url`	`{ integrated_lufs, true_peak_db, loudness_range }`
`check_job_status`	Poll async operations	`job_id`	`{ status, progress, result }`

Usage Examples

Analyze a song

"Analyze this song: https://example.com/song.mp3"

Response:

{
  "genre": ["electronic", "house"],
  "mood": ["energetic", "uplifting"],
  "tempo": 128,
  "key": "A minor",
  "instruments": ["synthesizer", "drums", "bass"]
}

Separate stems

"Separate the vocals from this track: https://example.com/track.mp3"

Response (sync for short files):

{
  "vocals_url": "https://cdn.ircamamplify.io/stems/vocals.wav",
  "drums_url": "https://cdn.ircamamplify.io/stems/drums.wav",
  "bass_url": "https://cdn.ircamamplify.io/stems/bass.wav",
  "other_url": "https://cdn.ircamamplify.io/stems/other.wav"
}

Response (async for longer files):

{
  "job_id": "abc123-def456"
}

Check if AI-generated

"Is this track AI-generated? https://example.com/mystery.mp3"

Response:

{
  "confidence": 85,
  "classification": "ai_generated"
}

Classification values: ai_generated, human_made, or uncertain

Analyze loudness

"Check if this master is ready for Spotify: https://example.com/master.wav"

Response:

{
  "integrated_lufs": -14.0,
  "true_peak_db": -1.0,
  "loudness_range": 6.0
}

Check job status

"Check the status of job abc123-def456"

Response:

{
  "status": "completed",
  "progress": 100,
  "result": {
    "vocals_url": "...",
    "drums_url": "...",
    "bass_url": "...",
    "other_url": "..."
  }
}

Status values: pending, processing, completed, failed

Error Handling

The server provides detailed error messages with actionable suggestions:

Error Code	Meaning	Suggestion
`MISSING_API_KEY`	API key not configured	Set `IRCAM_AMPLIFY_API_KEY` environment variable
`INVALID_API_KEY`	API key rejected	Verify key at app.ircamamplify.io
`INVALID_URL`	Cannot access audio URL	Ensure URL is publicly accessible
`UNSUPPORTED_FORMAT`	Audio format not supported	Use MP3, WAV, FLAC, OGG, or M4A
`FILE_TOO_LARGE`	File exceeds 100MB limit	Use a shorter audio clip
`RATE_LIMITED`	Too many requests	Wait and retry
`JOB_NOT_FOUND`	Job ID invalid or expired	Job results expire after 24 hours

Development

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

# Run tests
npm test

# Type check
npm run typecheck

# Lint and format
npm run lint
npm run format

Architecture

src/
├── index.ts              # MCP server entry point
├── types/
│   ├── mcp-tools.ts      # MCP tool type definitions
│   └── ircam-api.ts      # IRCAM API response types
├── tools/
│   ├── analyze-music.ts  # Music tagging tool
│   ├── separate-stems.ts # Stem separation tool
│   ├── detect-ai-music.ts # AI detection tool
│   ├── analyze-loudness.ts # Loudness analysis tool
│   └── check-job-status.ts # Job polling tool
└── utils/
    ├── auth.ts           # API key management
    ├── http.ts           # HTTP client with retry
    ├── validation.ts     # Input validation
    └── errors.ts         # Error formatting

License

MIT - See LICENSE for details.

Support

IRCAM Documentation: docs.ircamamplify.io
Get API Key: app.ircamamplify.io
Issues: GitHub Issues

IRCAM Amplify MCP Server

IRCAM Amplify MCP Server

Features

Supported Audio Formats

Quick Start

Prerequisites

Installation

Configuration

1. Set your API key

2. Configure your MCP client

Available Tools

Usage Examples

Analyze a song

Separate stems

Check if AI-generated

Analyze loudness

Check job status

Error Handling

Development

Architecture

License

Support

Resources

Tools

Latest Blog Posts

MCP directory API