Ableton For Ai

by peterkolbe

346 downloads

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GitHub

Other
AI

About

Bridge between Ableton Live and AI models. Inspect tracks, analyze audio (LUFS, spectrograms), and control mixing parameters in real-time via MCP.

Details

Author: peterkolbe
Downloads: 346
Categories: Other, AI

- Real-time project inspection — tempo, tracks, mixer state, device chains
- Deep audio analysis — LUFS, Peak, RMS, transient detection, spectrograms
- Remote mixing control — volume, pan, mute, solo, any device parameter
- Sidechain detection — identifies active external sidechain inputs
- Bulk device parameter changes for preset loading

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Ableton For Ai

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

From the repository

Install the server with Python 3.11+ and AbletonOSC as a Control Surface in Ableton Live 11 or 12. Invoke MCP tools such as get_overview, analyze_stems, set_track_volume, and set_device_parameter to interact with the session.

`list_resources`

List resources available on the server.

`read_resource`

Read a resource available on the server.

`analyze_stems`

DEEP AUDIO ANALYSIS: Triggers the generation of summaries and spectrograms for all tracks. This is a heavy operation that: 1. Generates '.summary.json' (Frames, Transients, LUFS) for AI consumption. 2. Generates '.spectrogram.webp' (Log-frequency visualizations). 3. Generates '.analysis.json' (Full resolution data for internal use). ACTION: Use this when you need fresh audio data (e.g., after the user recorded new parts or changed audio effects that significantly alter the sound).

`get_overview`

SESSION DISCOVERY: Returns a high-level overview of the current Live set. Includes: - Tempo and Locators (Song structure). - Simplified Track list with mixer states (Index, Name, Volume, Panning, Mute, Solo). Use this for initial navigation and to identify track indices for further 'get_track' calls.

`get_track`

TRACK INSPECTION: Returns comprehensive data for a single track. Includes: - Mixer state (Volume, Panning, etc.). - Complete Device Chain. - All Device Parameters (including UI-readable strings like "-12.0 dB" or "1500 Hz"). Use this when you need to understand exactly how a specific track is processed or which parameters are available for manipulation.

`get_tracks`

BULK TRACK INSPECTION: Query full data for multiple tracks in a single call. Parameters: - index_min: Starting track index. - index_max: Ending track index. Returns an array of track objects, identical in structure to 'get_track'. Highly efficient for analyzing groups of tracks (e.g., all drum tracks).

`set_device_parameter`

REMOTE CONTROL: Sets a specific device parameter. Parameters: - track_index: The index of the track. - device_index: The index of the device in the chain. - parameter_index: The index of the parameter to change. - value: The new normalized value (0.0 to 1.0). Note: For UI-readable values (like dB or Hz), check 'get_track' output first, but always send the normalized 0.0-1.0 value for the actual change.

`set_device_parameters`

BULK REMOTE CONTROL: Sets multiple parameters for a device at once. Parameters: - values: A list of floats representing the new values for ALL parameters of the device. Recommended for loading 'presets' or making simultaneous multi-parameter adjustments.

`set_track_volume`

MIXER CONTROL: Sets the volume of a track. - value: 0.0 to 1.0 (corresponds to Ableton's internal fader scaling).

`set_track_panning`

MIXER CONTROL: Sets the panning of a track. - value: -1.0 (Left) to 1.0 (Right), 0.0 is Center.

`set_track_mute`

Toggles the mute status of a track (True=Muted, False=Active).

`set_track_solo`

Toggles the solo status of a track (True=Solo, False=Normal).

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "ableton for ai": {
            "ableton-for-ai": {
                "command": "uvx",
                "args": [
                    "ableton-for-ai"
                ],
                "env": {
                    "STEMS_SOURCE_DIR": "/path/to/your/stems"
                }
            }
        }
    }
}

McpServers

{
    "ableton-for-ai": {
        "command": "uvx",
        "args": [
            "ableton-for-ai"
        ],
        "env": {
            "STEMS_SOURCE_DIR": "/path/to/your/stems"
        }
    }
}

Ableton for AI

Bridge between Ableton Live and AI models via the Model Context Protocol (MCP). Makes your DAW hearable and visible to AI — inspect, analyze, and modify music projects in real-time.

What it does

- Real-time project inspection — Read tempo, tracks, mixer state, device chains, and all plugin parameters directly from a running Ableton Live session. - Deep audio analysis — Generate LUFS, Peak, RMS, transient detection, and log-frequency spectrograms for every stem. - Remote mixing control — Adjust volume, panning, EQ, compressor settings, and any device parameter directly from the AI. - Sidechain detection — Automatically identifies active external sidechain inputs on devices.

Tools

| Tool | Description | |------|-------------| | get_overview | Session discovery — tempo, locators, all tracks with mixer state | | get_track | Deep-dive into a single track (devices + all parameters) | | get_tracks | Bulk fetch full data for a range of tracks | | analyze_stems | Generate audio summaries + spectrograms for all tracks | | set_track_volume | Adjust track volume (0.0–1.0) | | set_track_panning | Adjust track panning (-1.0 to 1.0) | | set_track_mute / set_track_solo | Mute/solo control | | set_device_parameter | Change any device parameter by normalized value | | set_device_parameters | Bulk-set all parameters of a device (preset loading) |

Resources

- ableton://stems/{track_name}/summary — Compressed audio analysis (JSON) - ableton://stems/{track_name}/spectrogram — Log-frequency spectrogram (WebP) - ableton://stems/available/summaries — List tracks with available analysis - ableton://stems/available/spectrograms — List tracks with available spectrograms

Use Cases

- 🎛️ "Analyze my mix and suggest EQ adjustments to reduce frequency clashing" - 🔊 "Set the kick volume to -6dB and reduce the reverb send on vocals" - 📊 "Show me the spectrogram of the bass track and identify problematic resonances" - 🎚️ "Give me an overview of all track levels and suggest a better gain staging"

Requirements

- Ableton Live 11/12 with AbletonOSC installed as Control Surface - Python 3.11+ - macOS or Windows

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About

Details

Jump to

Setting up with Highlight

From the repository

list_resources

read_resource

analyze_stems

get_overview

get_track

get_tracks

set_device_parameter

set_device_parameters

set_track_volume

set_track_panning

set_track_mute

set_track_solo

Claude Desktop / Cursor

McpServers

Ableton for AI

What it does

Tools

Resources

Use Cases

Requirements

Install

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`list_resources`

`read_resource`

`analyze_stems`

`get_overview`

`get_track`

`get_tracks`

`set_device_parameter`

`set_device_parameters`

`set_track_volume`

`set_track_panning`

`set_track_mute`

`set_track_solo`