mcp-brasilapi

Overview Schema Source Related Servers Discussions Admin

ibge__listar_municipios

Retrieve a list of municipalities for a given Brazilian state. Provide the state abbreviation (e.g., 'RJ') and optionally choose a data provider from available sources.

Instructions

Lista os municípios de uma unidade federativa.

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": {
      "sigla_uf": "<sigla_uf>"
    },
    "name": "ibge__listar_municipios"
  }
}

Input Schema

Name	Required	Description	Default
`sigla_uf`	Yes	Sigla da UF (ex.: "RJ", "SC").
`providers`	No	Opcional — provedor(es) de dados separados por vírgula: ``dados-abertos-br``, ``gov`` ou ``wikipedia``.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 16, 2026

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. However, it only states a basic function without addressing constraints, side effects, or system behavior (e.g., no mention of data freshness, pagination, or required permissions). For a simple listing tool, even minimal transparency is missing.

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?

The description is a single concise sentence that is front-loaded and free of verbosity. While efficient, its brevity limits informativeness. It scores highly for structure but loses a point for being overly minimal.

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?

Given the presence of an output schema, the description does not need to explain return values. However, among many sibling tools (especially other IBGE tools), the description lacks contextual guidance for when to select this tool. It covers the essential action but omits helpful usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both parameters adequately described in the input schema. The tool description adds no new parameter semantics beyond what the schema already provides (e.g., the relationship between sigla_uf and municipalities). Thus, the description does not enhance parameter understanding.

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 "Lista os municípios de uma unidade federativa" clearly specifies the action (list) and resource (municipalities of a specific federation unit). It distinguishes from sibling tools like ibge__listar_ufs (which lists states) and ibge__buscar_uf (which searches states), making the tool's specific purpose unambiguous.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor does it state any prerequisites or exclusions. Sibling tools exist for related lookups, but no contextual recommendation is given, leaving the agent to infer usage from the name alone.

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