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OpenUtau MCP

OpenUtau MCP

by Tehcnological
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_expressions

Lists project expression parameters such as abbreviation, name, type, min, max, and default values so you can inspect available expression controls before editing curves.

Instructions

Project expressions (abbr, name, type, min, max, default). / プロジェクトの表情パラメータ一覧。

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": "list_expressions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. The field list implies a read-only listing, but it does not explicitly state read-only behavior, scope, ordering, or that it has no side effects.

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?

Very concise and front-loaded: one English line with return fields plus a Japanese equivalent. There is no filler, and the field list is packed into the opening sentence.

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?

No output schema exists, but the description lists the expected fields, which covers the key return information for a zero-parameter list tool. It could clarify scope or filtering, but the low complexity makes it reasonably complete.

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

Parameters4/5

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

The tool has zero parameters, so there are no parameter semantics to document. The baseline for a parameterless tool is 4, and the description does not need to add parameter meaning.

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

Purpose4/5

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

Names the specific resource, project expressions, and enumerates the fields returned (abbr, name, type, min, max, default). It lacks an explicit verb and does not differentiate from sibling list_* tools, but the resource is clear.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance. The only cue is the resource name, with no mention of how it relates to alternatives or when an agent should call it.

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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