I Built a 74-Tool Apple Music MCP Server for Claude & Cursor (Autonomous DJ, Spotify Importer & AirPlay)
What if your AI coding assistant or desktop agent could actually control your music like a pro DJ while you work? I built mcp-applemusic , an open-source Model Context Protocol (MCP) server written in Python with FastMCP that gives Claude Desktop, Cursor, and other AI agents complete, native control over Apple Music on macOS. It features 74 tools spanning playback, playlist engineering, listening…
I created a comprehensive, 74-tool MCP server for Apple Music called mcp-applemusic. This Python-based Model Context Protocol (MCP) server, written in FastMCP, grants AI assistants like Claude Desktop and Cursor full control over Apple Music on macOS. With 74 distinct tools, the server offers a wide range of capabilities for music management and customization.
The server's key features include an autonomous background DJ daemon that runs locally on your CPU, eliminating the need for costly API calls to language models. This background thread operates 24/7 without incurring any token usage. It also employs look-ahead latency compensation to ensure smooth playback by accounting for Apple Music's ~120ms CoreAudio buffer delay.
Another standout feature is the Zero-Login Spotify Importer, which allows you to effortlessly import your favorite Spotify playlists into Apple Music without the need for any Spotify Developer tokens or logins. The server reconstructs the playlist track-by-track, leveraging high-speed catalog lookups to seamlessly integrate your music library.
Multi-room AirPlay control is another powerful addition to the server. You can manage multiple AirPlay speakers simultaneously, assigning individual volume levels (e.g., Living Room HomePod at 40%, Studio AirPods at 80%, with a master volume control). This feature enables you to create an immersive audio experience across your entire home.
The server also maintains a local SQLite database, which serves as a local listening journal and provides replay analytics. It logs every track you play, generates monthly Apple Replay reports, and even calculates your personal listening personality and skip patterns. This data can be invaluable for understanding your music preferences and refining your listening experience.
To set up and use the server, you can integrate it into Claude Desktop or Cursor using a simple uv configuration. An example prompt to start an Auto DJ in adaptive mode on a Hip-Hop playlist is also provided. The project is open source under the MIT License and can be found on GitHub, where you can explore the code and contribute if you find it useful.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
