MaxMSP-MCP Server

MaxMSP-MCP Server

Bridge LLMs with Max patches via Model Context Protocol

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MaxMSP-MCP Server enables large language models to understand, explain, and generate Max patches by leveraging the Model Context Protocol. It connects LLM agents with MaxMSP environments, providing access to documentation and patch objects for detailed interaction. Installation includes both a Python server and Max environment integration, facilitating seamless Python-Max communication. The tool supports explaining patches, debugging, and synthesizer creation directly through LLM interfaces.

Key Features

LLM-based explanation of Max patches
Generation of Max patches via LLM
Integration with Max 9+ using Javascript V8 engine
Access to official Max object documentation
Debugging support for Max patches
Synchronizes context between LLM and Max environment
Plugin system for multiple LLM clients (Claude, Cursor, etc.)
Seamless installation with Python and Max
Interactive user interface within Max patches
Video and demo resources for quick onboarding

Use Cases

Automatically explaining existing Max patches for education or documentation
Generating new Max patches or synths using natural language instructions
Debugging and verifying Max object functionality via LLM agent
Enhancing music production workflows with AI-driven patch manipulation
Onboarding new users to MaxMSP by making patches more interpretable
Rapid prototyping of interactive audio tools using LLMs
Automating patch modifications for live performance setups
Providing smart assistance or recommendations within MaxMSP
Collaborative patch development with AI agents
Creating tools for teaching sound synthesis and Max/MSP concepts

README

MaxMSP-MCP Server

This project uses the Model Context Protocol (MCP) to let LLMs directly understand and generate Max patches.

Understand: LLM Explaining a Max Patch

img Video link. Acknowledgement: the patch being explained is downloaded from here. Text comments in the original file are deleted.

Generate: LLM Making an FM Synth

img Check out the full video where you can listen to the synthesised sounds.

The LLM agent has access to the official documentation of each object, as well as objects in the current patch and subpatch windows, which helps in retrieving and explaining objects, debugging, and verifying their own actions.

Installation

Prerequisites

  • Python 3.8 or newer
  • uv package manager
  • Max 9 or newer (because some of the scripts require the Javascript V8 engine), we have not tested it on Max 8 or earlier versions of Max yet.

Installing the MCP server

  1. Install uv:
# On macOS and Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  1. Clone this repository and open its directory:
git clone https://github.com/tiianhk/MaxMSP-MCP-Server.git
cd MaxMSP-MCP-Server
  1. Start a new environment and install python dependencies:
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt
  1. Connect the MCP server to a MCP client (which hosts LLMs):
# Claude:
python install.py --client claude
# or Cursor:
python install.py --client cursor

To use other clients (check the list), you need to download, mannually add the configuration file path to here, and connect by running python install.py --client {your_client_name}.

Installing to a Max patch

Use or copy from MaxMSP_Agent/demo.maxpat. In the first tab, click the script npm version message to verify that npm is installed. Then click script npm install to install the required dependencies. Switch to the second tab to access the agent. Click script start to initiate communication with Python. Once connected, you can interact with the LLM interface to have it explain, modify, or create Max objects within the patch.

Disclaimer

This is a third party implementation and not made by Cycling '74.

Star History

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Repository Owner

tiianhk
tiianhk

User

Repository Details

Language Max
Default Branch main
Size 44,521 KB
Contributors 2
License MIT License
MCP Verified Nov 11, 2025

Programming Languages

Max
88.3%
JavaScript
5.98%
Python
5.72%

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