godot-mcp-extended

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get_project_settings

Reads project.godot and returns parsed sections like application, autoload, and input, capped for AI use. Use it to inspect Godot project settings without loading the editor.

Instructions

Read project.godot and return parsed sections (application, autoload, input, etc.) capped for AI use

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": {
      "projectPath": "<projectPath>"
    },
    "name": "get_project_settings"
  }
}

Input Schema

Name	Required	Description	Default
`projectPath`	Yes	Path to the Godot project directory

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Oct 19, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses that output is 'capped for AI use' (implying truncation of large sections) and that it reads rather than writes, but it says nothing about behavior on a missing/malformed project.godot, permission needs, or how capping is applied.

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

Conciseness4/5

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

A single front-loaded sentence that identifies the file read, the return shape, and the AI-oriented cap with no wasted words. It is dense but not bloated.

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?

For a one-parameter read tool with no output schema, the definition is serviceable but leaves gaps: it doesn't specify which sections are always present, what 'capped' means in practice, or how the parsed result is keyed. An agent can call it correctly but cannot predict the response shape.

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 description coverage is 100% and there is only one parameter (projectPath) with a clear schema description, so the schema already does the work. The description adds no format details (absolute vs relative, trailing slash expectations) beyond it, making 3 the appropriate baseline.

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?

States a specific verb ('Read'), a concrete resource ('project.godot'), and the shape of the result ('parsed sections (application, autoload, input, etc.)'). It does not, however, distinguish itself from sibling read-oriented tools such as get_project_info or list_projects, which an agent could plausibly confuse it with.

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?

Usage is only implied: the agent can infer this is the tool for inspecting project configuration, but there is no explicit when-to-use statement and no named alternative (e.g. get_project_info) to route against. The phrase 'capped for AI use' hints at a use case but is not framed as guidance.

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