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Client Manage

client_manage

Configure AI clients to connect to the Godot AI MCP server by adding, removing, or checking client config entries.

Instructions

Configure AI clients to use this Godot AI MCP server. Writes / removes client config files (Claude Code, Codex, Antigravity, Cursor, Devin Desktop (Windsurf), Zed, etc.).

Ops: • status() List every supported client with id, display_name, status (configured | not_configured | configured_mismatch | error), and installed flag. • configure(client) Write the MCP server entry into the named client's config file. client is one of the ids returned by status(). • remove(client) Remove this server's entry from the named client's config.

Canonical call shape: {"op": "<verb>", "params": {...}}. Flat op parameters are accepted as a compatibility alias when the client transmits them; op and session_id remain top-level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opYes
paramsNo
session_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.1.4
  2. Removedv3.0.7
  3. First observedv2.9.1

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries full burden and explicitly acknowledges that it 'Writes / removes client config files.' It also discloses the status values returned and the compatibility alias behavior for flat parameters. It does not mention permissions or reversibility, but the core side effects are clearly stated.

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 efficiently structured: a one-sentence purpose, a bulleted operation list, and a compact call-shape note. Every section adds necessary information, and the most important mutation warning appears in the first sentence.

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

Completeness5/5

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

Given an output schema and no annotations, the description is sufficiently complete for calling the tool correctly: it describes each operation, parameter semantics, call shape, and compatibility behavior. No critical aspect needed to invoke the tool is missing.

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 0%, so the description compensates well: it explains op values via the ops list, defines 'client' as an id from status(), and clarifies the canonical call shape. The session_id parameter is only noted as top-level, not semantically explained, but its purpose is fairly self-evident.

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 opens with a specific verb+resource: 'Configure AI clients to use this Godot AI MCP server.' It then enumerates three concrete operations (status, configure, remove), making it distinct from sibling manage tools and unambiguous about scope.

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

Usage Guidelines4/5

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

The description gives clear operational context by defining each op and explicitly directing users to call status() first to obtain valid client ids for configure/remove. It does not explicitly compare against alternative tools, but the workflow within the tool is well specified.

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