# MuseScore

> Use this tool when you need to programmatically control music notation software for tasks like composing, editing, and analyzing musical scores. It solves problems in AI-assisted music composition, automated score generation, and music theory education by providing a WebSocket-based bridge to MuseScore. With inputs like note and rest insertion, cursor navigation, and instrument management, and outputs like edited musical scores, it's ideal for use cases requiring direct integration with professional music notation software.

Canonical page: https://skillsregistry.net/skills/ghchen99-musescore  
JSON: https://api.skillsregistry.net/v1/skills/ghchen99-musescore

## Description

This MCP server provides programmatic control of MuseScore music notation software through a WebSocket-based bridge, enabling AI assistants to compose, edit, and analyze musical scores directly within the MuseScore application. Built by George Chen using Python with FastMCP and a custom QML plugin for MuseScore 3.0, it offers comprehensive music editing capabilities including note and rest insertion with precise duration control, cursor navigation across measures and staves, tuplet creation, lyrics addition, instrument management, and time signature modifications. The implementation features a modular architecture with organized tool categories, robust cursor state management with automatic selection synchronization, sequence processing for batch operations, and real-time communication between the MCP server and MuseScore through WebSocket connections, making it valuable for AI-assisted music composition workflows, automated score generation, music theory education applications, and building AI tools that need direct integration with professional music notation software.

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/ghchen99-musescore)
- **Repository:** <https://github.com/ghchen99/mcp-musescore>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ghchen99-musescore"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ghchen99-musescore` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ghchen99-musescore/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt