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Galgame MCP

Galgame MCP

by YeXuanHs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

native_run

Executes catalogued native executables in a Galgame localization toolkit, passing raw arguments for tasks like script extraction, patching, and configuration.

Instructions

Run a catalogued native EXE with raw args. Common: vntextpatch extractlocal/insertlocal — but prefer vntextpatch_extractlocal / vntextpatch_insertlocal wrappers. Also krkrtpc, kagconfig, …

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": {
      "tool": "<tool>"
    },
    "name": "native_run"
  }
}

Input Schema

NameRequiredDescriptionDefault
cwdNoWorking directory (default: tool kit folder)
argsNoe.g. [extractlocal, inputDir, jsonDir] for VNTextPatch
toolYesTool id: vntextpatch / kagconfig / krkrtpc / …
captureNo
timeoutNoSeconds; omit/null for no limit (default 120)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.1/5.0
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 burden of disclosing behavior. It states 'Run a catalogued native EXE with raw args' but does not mention any safety concerns, side effects, output capture, or what happens to the process. The reference to 'raw args' is a hint but insufficient for a potentially arbitrary command execution tool.

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 two sentences with no filler. It front-loads the core purpose and immediately provides actionable alternatives and examples.

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 tool has 5 parameters, no output schema, and no annotations. The description provides useful examples and usage guidance but omits behavioral details like output capture, return format, and safety implications of running arbitrary EXEs. It's minimally adequate but has clear gaps.

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?

Schema description coverage is high (80%), so the baseline is 3. The description adds value by giving concrete examples for the 'tool' parameter (vntextpatch, krkrtpc, kagconfig) and for 'args' (extractlocal/insertlocal), enriching what the schema provides.

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

Purpose5/5

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

The description clearly defines the tool's function: running a catalogued native EXE with raw arguments. It distinguishes itself from wrappers like vntextpatch_extractlocal/insertlocal by noting the preferred alternatives, making its specific role clear.

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

Usage Guidelines5/5

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

The description explicitly advises preferring vntextpatch_extractlocal and vntextpatch_insertlocal wrappers for the common cases, and lists other supported tools (krkrtpc, kagconfig). This gives concrete when-to-use and when-not-to-use guidance relative to sibling 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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