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Coletum MCP Server

Coletum MCP Server

Official
by geo-sapiens
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

listar_modelos

Read-only

Lists available PDF templates, including saved client and built-in read-only options, reports saved preferences, and can return a selected template's text for adjustment.

Instructions

Lista os modelos de PDF disponíveis: os salvos na pasta de modelos do cliente e os embutidos (somente leitura: coletum_exportacao, que replica o PDF da exportação do Coletum, e os alternativos coletum_colunas e coletum_fotografico, com aparencia_aceita). Diz também se há preferências salvas. Com mostrar_template, traz o texto de um modelo para ajustar e salvar com outro nome. Não chama a API.

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": "listar_modelos"
  }
}

Input Schema

NameRequiredDescriptionDefault
mostrar_templateNoNome de um modelo para trazer também o texto do template e o modelo.json (ex.: coletum_exportacao, para partir dele).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real context beyond them: which models are built-in/read-only, that preferences presence is reported, and that it does not call the API (a local, side-effect-free operation). Return shape is described in prose but pagination/format is not.

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?

Single dense paragraph, front-loaded with the core listing behavior before the parameter-specific clause. Nearly every sentence earns its place, though the enumeration of built-in model names is a little heavy for a description.

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

Completeness4/5

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

No output schema exists, so the description must carry the return semantics, and it does: it enumerates what is listed (saved + built-in read-only models) and reports preference presence. An agent has enough to call it correctly; only the exact response structure/pagination is unstated.

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 coverage is 100%, so the baseline is 3. The description goes slightly beyond the schema by clarifying the parameter's purpose (fetch the template text to adapt and save under another name) and naming a concrete example value (coletum_exportacao) to start from.

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?

States a specific verb+resource (lists available PDF templates) and splits the result into client-saved vs built-in read-only models, naming the built-in IDs. It does not explicitly differentiate itself from siblings like listar_formularios or analisar_pdf_modelo, so the agent must infer the boundary.

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?

It explains the mostrar_template use case ('trazer o texto de um modelo para ajustar e salvar com outro nome'), which is genuine when-to-use guidance, but gives no when-not guidance and never names an alternative sibling to route to. Usage is implied rather than contrasted.

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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