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Unity MCP Claude Code

Unity MCP Claude Code

by MauricePutinas
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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install_editor_modules

Add modules to an existing Unity editor installation. Executes as a background job and requires explicit confirmation to proceed.

Instructions

Fügt Module zu einem bereits installierten Editor hinzu (Hub-CLI 'install-modules'). Läuft als Hintergrund-Job. confirm=true nötig.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "version": "<version>",
      "modules": "<modules>"
    },
    "name": "install_editor_modules"
  }
}

Input Schema

NameRequiredDescriptionDefault
versionYes
modulesYes
child_modulesNo
confirmNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

A3.5/5.0
Behavior4/5

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

Annotations indicate a non-read-only, non-destructive operation. The description adds valuable behavioral context: the tool runs asynchronously as a background job and requires the confirm parameter to be true. This exceeds what the structured annotations provide, earning a 4. No contradictions with annotations.

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?

The description is concise, consisting of two sentences that front-load the purpose and add critical behavioral notes. Every sentence is necessary and efficient, achieving maximum conciseness.

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

Completeness3/5

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

The description covers the core action and key behaviors (background job, confirm requirement), but lacks details on return values (since no output schema exists), error handling, and prerequisites beyond having an installed editor. These gaps reduce completeness for an AI agent.

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

Parameters2/5

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

With 0% schema description coverage, the description must compensate. It only clarifies that confirm must be true, but does not explain version, modules, or child_modules. This is insufficient for correct parameter usage, resulting in a score of 2.

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?

The description clearly states the tool adds modules to an already installed editor and references the Hub-CLI command, making the purpose unambiguous. However, it does not explicitly differentiate from related tools like install_editor or install_editor_via_deeplink, which limits the score to 4.

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

Usage Guidelines3/5

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

The description mentions the tool runs as a background job and requires confirm=true, which provides some usage context. However, it does not explain when to use this tool vs. alternatives or when not to use it, leaving the agent without sufficient guidance.

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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