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MuseScore MCP Server

MuseScore MCP Server

by ghchen99
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Highlight Markings

highlight_markings

Highlights score markings such as dynamics with translucent boxes for quick visual review; supports color, opacity, type, and measure/staff ranges.

Instructions

Highlight markings such as dynamics (f, mf, ff) with a translucent box behind each one. get_score lists the markings in each measure. Remove with clear_highlights.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "highlight_markings"
  }
}

Input Schema

NameRequiredDescriptionDefault
colorNoHighlight color as "#rrggbb" (default yellow)#ffd600
typesNoKinds of markings to highlight
opacityNoOpacity from 0 to 1
last_staffNoLast staff (0-based, inclusive). Defaults to the last staff.
end_measureNoLast measure (1-based, inclusive). Defaults to the end of the score.
first_staffNoFirst staff (0-based)
start_measureNoFirst measure (1-based)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are supplied, so the description carries the full burden. It discloses the visual effect (translucent box) and the paired removal tool, but says nothing about whether highlights persist in the score, are undoable, or what the call returns — meaningful gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short front-loaded sentences, each carrying distinct information: the action, the discovery path via get_score, and the removal path via clear_highlights. No filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a seven-parameter, all-optional tool with complete schema documentation and no output schema, the description covers purpose, discovery, and cleanup. It could say more about default behavior when ranges are omitted, but the schema already explains the null defaults.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so every parameter including color, opacity, and measure/staff ranges is already documented in the schema. The description's only added meaning is the parenthetical example of dynamic values (f, mf, ff) illustrating the default "Dynamic" type, so it sits at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Highlight markings such as dynamics") and describes the visual result ("translucent box behind each one"), which distinguishes it from sibling highlighting tools like highlight_bars, highlight_notes, and highlight_symbols by scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear operational context: use get_score to list markings per measure, and use clear_highlights to remove them. It does not explicitly say when to choose this over highlight_symbols or highlight_notes, so guidance is strong but not exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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