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Godot MCP - Full Control

Godot MCP - Full Control

by cxb2523
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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manage_docker_export

Create or read a Dockerfile for headless Godot exports, specifying project path, Godot version, base image, and export preset.

Instructions

Create Dockerfile for headless Godot export

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>",
      "action": "<action>"
    },
    "name": "manage_docker_export"
  }
}

Input Schema

NameRequiredDescriptionDefault
actionYesAction: create or read
baseImageNoBase Docker image (default: ubuntu:22.04)
projectPathYesAbsolute path to Godot project
exportPresetNoExport preset name
godotVersionNoGodot version (e.g. 4.3-stable)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does almost nothing with that burden. It does not state where the Dockerfile is written, whether an existing Dockerfile is overwritten, what the 'read' action does, or what side effects (if any) occur on the project directory.

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?

The description is a single efficient sentence with the verb front-loaded and zero filler words. It loses a point because the brevity comes at the cost of omitting the tool's read mode, making it slightly under-specified rather than purely concise.

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

Completeness2/5

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

For a 5-parameter tool with a mode-switching required parameter, no output schema, and no annotations, the description is incomplete. An agent would not know that 'action' supports reading an existing Dockerfile, what the tool returns, or how the parameters compose into a usable Dockerfile definition.

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%, so the baseline is 3; the schema already documents all five parameters. The description adds only the 'headless export' framing, which hints at how godotVersion and exportPreset are used, but adds no detail about parameter formats or the create/read action semantics.

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 uses a specific verb+resource pair ('Create Dockerfile') with a clear context ('headless Godot export'), and this clearly separates it from siblings like export_project or manage_export_presets. However, it only covers the 'create' side of the tool while the required 'action' parameter explicitly supports both create and read, so the stated purpose is incomplete.

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 guidance is given about when to use this tool versus the obvious alternatives (export_project, manage_export_presets, manage_ci_pipeline, run_project). There is no mention of CI/CD contexts, prerequisites, or when a Dockerfile is needed versus a direct export.

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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