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MCP_CAD

MCP_CAD

by danielproxd2
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_capabilities

Lists all available tools in the MCP_CAD server, returning their names and total count.

Instructions

Inventario autoritativo de herramientas MCP_CAD — solo nombres.

Las descripciones completas ya viajan en cada tools/list; este catálogo confirma la superficie viva (conteo + nombres) sin duplicar ese contexto.

[en: authoritative live tool inventory, names only. Full descriptions already ship with tools/list — call this to confirm the live surface or an exact tool name without re-paying for the docstrings.]

Returns: {"tool_count": int, "tools": [str, ...]} # alphabetical names

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_capabilities"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavior: returns a JSON object with tool_count and alphabetical tool names. It also clarifies that full descriptions are not included, preventing false expectations. This is complete transparency for a listing 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 very concise with bilingual text, front-loaded with the main purpose. Every sentence adds value: purpose, distinction from alternatives, and return format. No wasted words.

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?

Despite no output schema, the description specifies the exact return format and contents. For a zero-parameter tool with a simple inventory list, this is fully complete and sufficient for an AI agent to understand and use correctly.

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?

No parameters exist, so the description does not need to add parameter semantics. Baseline 4 is appropriate as there are no gaps to fill.

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 states the tool lists authoritative tool names. It specifies 'solo nombres' and 'names only', distinguishing it from tools/list which provides full descriptions. This directly addresses the purpose of inventory listing.

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 using this tool to confirm the live surface or exact tool name without the overhead of full docstrings from tools/list. It provides clear context for when to use this tool versus the alternative.

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

Deploy Server

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