MCP MIDI Bridge

MCP MIDI Bridge

An Electron desktop application that bridges LLM-driven music generation with DAWs by converting NoteSequence JSON from AI models into MIDI data that can be played, recorded, and manipulated in any digital audio workstation.

Category
Visit Server

README

MCP MIDI Bridge

Overview

MCP MIDI Bridge is an Electron-based desktop application that acts as a bridge between LLM-driven music generation (via the Model Context Protocol, MCP) and any DAW (Digital Audio Workstation) that accepts MIDI input. It enables AI-generated or AI-edited musical content (in Magenta NoteSequence JSON format) to be easily played, recorded, and manipulated in a DAW via a virtual MIDI device.

This project has been recently refactored to use a modern technology stack, including Next.js for the user interface and TypeScript for the entire codebase.

Features

  • MCP API Server: An Express-based server that receives and updates musical content (NoteSequence JSON) from LLMs via HTTP.
  • Virtual MIDI Output: Creates a virtual MIDI device that any DAW can connect to, powered by easymidi.
  • Multi-Channel Support: Full support for all 16 MIDI channels with General MIDI instruments.
  • Configurable Port: Run multiple instances on different ports for parallel workflows.
  • Song Cache: Stores song data for persistence between sessions.
  • User Dashboard: A modern, responsive UI built with Next.js and React, for viewing and playing songs.
  • MIDI Import/Export: Support for importing and exporting MIDI files (coming soon).
  • TypeScript Codebase: The entire project is written in TypeScript for improved type safety and maintainability.

Technology Stack

  • Electron: Cross-platform desktop application framework.
  • Next.js: React framework for building the user interface.
  • TypeScript: Superset of JavaScript that adds static types.
  • Express: Web framework for creating the MCP API server.
  • EasyMIDI: Library for creating virtual MIDI devices.
  • Tailwind CSS: Utility-first CSS framework for styling the UI.
  • Magenta: Python library for music generation (used in the Python backend).

Development

Prerequisites

  • Node.js 18+
  • Python 3.8+ (for Magenta features)
  • npm or yarn

Setup

  1. Clone the repository:

    git clone https://github.com/your-username/mcp-midi.git
    cd mcp-midi
    
  2. Install dependencies:

    npm install
    
  3. Start the development server: This command will concurrently start the Next.js development server and the Electron application.

    npm run dev
    

Build

To build the application for production, run the following command:

npm run build

This will create a distributable package in the dist directory.

License

Apache 2.0

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured