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Municípios do Brasil

ibge_municipios
Read-onlyIdempotent

Lists Brazilian municipalities from IBGE.

Features:

  • List municipalities by state (using state abbreviation)

  • List all municipalities in Brazil (5,570 municipalities)

  • Search by municipality name

  • Returns 7-digit IBGE code

Examples:

  • São Paulo municipalities: uf="SP"

  • Search by name: busca="Campinas"

  • MG municipalities containing "Belo": uf="MG", busca="Belo"

Use a different tool when:

  • Resolve/decode a code at any level (region, state, district), not just municipalities → ibge_geocodigo

  • Full details/hierarchy of one locality by code → ibge_localidade

  • Neighboring municipalities → ibge_vizinhos

Behavior: read-only and idempotent — a live GET against the public IBGE Localidades API. Returns a Markdown table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ufNoEstado por sigla (SP), nome (São Paulo) ou código IBGE (35). Se não informado, retorna todos os municípios do Brasil.
buscaNoTermo para buscar no nome do município
limiteNoNúmero máximo de resultados (padrão: 100, máximo: 5570)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ufNoUF informada no filtro (como recebida na entrada)
buscaNoTermo de busca aplicado ao nome do município
totalYesTotal de municípios encontrados antes do limite
municipiosYesLista de municípios retornados (após filtro e limite)
provenanceYesBloco de proveniência (contrato v1.0): fonte, URL, período, extração e licença
attributionYesURLs canônicas das fontes desta resposta (lista de atribuição)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful operational context: it is a live GET against the public IBGE Localidades API and returns a Markdown table, which clarifies network dependency and output format beyond the 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 well-structured with a clear lead sentence, bulleted features, examples, sibling routing, and behavioral notes. Every section serves a distinct purpose and no sentence is wasted.

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 three optional parameters, a rich sibling set, and an output schema, the description covers what the tool does, how to filter, what it returns, when not to use it, and its live/read-only nature. An agent has enough context to select and invoke it correctly without further research.

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, but the description adds value with practical examples like uf='SP', busca='Campinas', and combined uf='MG', busca='Belo'. It also states that the return includes a 7-digit IBGE code, clarifying output semantics not covered by the input schema.

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 and resource: 'Lists Brazilian municipalities from IBGE.' It clearly defines the core features (by state, all municipalities, name search) and explicitly names sibling tools it is not, making differentiation immediate.

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 'Use a different tool when' section explicitly routes agents to ibge_geocodigo, ibge_localidade, and ibge_vizinhos for related but distinct use cases. It also provides concrete parameter examples that show when to use uf, busca, or both.

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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