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multimodels-mcp

multimodels-mcp

by dpmadsen
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Listar modelos disponíveis

list_models
Read-only

List available AI models for delegation, showing each model's ID and provider status.

Instructions

Lista os modelos de IA habilitados para delegação, com o id exato a usar na ferramenta delegate_task e o status de cada provedor.

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_models"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare 'readOnlyHint': true, and the description adds that the tool provides exact ids and provider statuses, which aligns with read-only behavior. No contradictions, and additional context is provided beyond annotations.

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 a single, well-structured sentence that conveys all necessary information without any 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?

For a simple list tool with no output schema, the description sufficiently explains what is returned (model IDs and provider statuses) and its relevance to the sibling tool, making it contextually complete.

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?

The tool has no parameters, so the description does not need to add parameter details. Schema coverage is trivially 100%, and the baseline for zero parameters is 4.

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 'modelos de IA habilitados para delegação' with specific details (id and status), and distinguishes itself from the sibling 'delegate_task' by providing the id needed for that tool.

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?

The description implies usage before 'delegate_task' by mentioning the id is for that tool, but it does not explicitly state when to use or not use this tool, nor does it provide alternative scenarios.

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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