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Unity MCP Claude Code

Unity MCP Claude Code

by MauricePutinas
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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write_text_asset

Writes any text file (JSON, .asmdef, .shader, .txt, .csv) into a Unity project with path sandboxing and automatic backup.

Instructions

Schreibt eine beliebige Textdatei ins Projekt (JSON, .asmdef, .shader, .txt, .csv …). Path-Sandbox + Backup.

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": {
      "project_path": "<project_path>",
      "rel_path": "<rel_path>",
      "content": "<content>"
    },
    "name": "write_text_asset"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_pathYes
rel_pathYes
contentYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

C2.4/5.0
Behavior3/5

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

The description adds 'Path-Sandbox + Backup', indicating safety features beyond annotations. Annotations show readOnlyHint=false and destructiveHint=false, which is consistent with a safe write operation. However, it does not detail what the sandbox restricts or when backup is restored, leaving behavioral gaps.

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

Conciseness2/5

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

The description is very short (two lines), but lacks critical details. It is concise in length but under-informative. A better balance would include brief explanations of parameters or usage context.

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

Completeness1/5

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

Given 3 required parameters, no output schema, and a file-writing operation, the description is incomplete. It mentions sandbox and backup but does not explain overwrite behavior, path resolution, or error conditions. An agent would have too little context to use the tool correctly.

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

Parameters1/5

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

Schema coverage is 0% (no parameter descriptions). The description does not explain any parameter. It is unclear what project_path vs rel_path mean, or what content expects. The description fails to compensate for the lack of schema documentation, leaving parameters opaque.

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 it writes any text file into the project and lists example file types (JSON, .asmdef, .shader, .txt, .csv). This distinguishes it from siblings like write_script (which writes code scripts). However, it does not specify overwrite behavior or if it creates new files.

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?

No explicit guidance on when to use this tool vs alternatives. The description implies it is for general text files, but does not mention that write_script should be used for scripts or that read_project_file reads files. Lack of exclusion or context makes it less helpful for an AI agent deciding between tools.

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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