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ab-orbit

ab-ibge-mcp-server

by ab-orbit

Buscar Notícias do IBGE

ibge_noticias
Read-only

Retrieve recent IBGE news, releases, and publications. Filter by subject or product to get targeted updates.

Instructions

Busca notícias, releases e publicações recentes do IBGE.

Args:

  • quantidade (number): número de notícias a retornar (1-20, padrão: 10)

  • assunto (string, opcional): filtra por assunto/tema (ex: "censo", "pib", "desemprego")

  • produto (string, opcional): filtra por produto/pesquisa IBGE (ex: "PNAD", "IPCA", "Censo")

Retorna: Lista de notícias com título, introdução, data de publicação e link.

Exemplos:

  • "Últimas notícias do IBGE" → quantidade=10

  • "Notícias sobre o Censo 2022" → assunto="censo"

  • "Releases do IPCA" → produto="IPCA"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assuntoNoFiltrar por assunto (ex: 'censo', 'emprego', 'agricultura')
produtoNoFiltrar por produto IBGE (ex: 'PNAD', 'IPCA', 'Censo', 'PIB')
quantidadeNoNúmero de notícias a retornar (1-20)
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds useful context by defining the return format ('Lista de notícias com título, introdução, data de publicação e link') and the scope 'recentes' (recent). It also clarifies parameter constraints (quantidade 1-20, default 10), which supplements the schema.

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 and front-loaded: a single clear purpose sentence, followed by concise parameter details, return format, and examples. Every line adds value, with no redundancy or fluff.

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?

There is no output schema, but the description compensates by explicitly listing the return fields (title, introduction, date, link). It covers all optional parameters with examples, making it complete for an agent to decide when and how to invoke the tool.

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 description coverage is 100% for all three parameters, providing baseline. The description adds substantial value by giving concrete example values for each parameter (assunto: 'censo', 'pib', 'desemprego'; produto: 'PNAD', 'IPCA', 'Censo'), which helps an agent understand how to invoke filters correctly.

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's specific function: 'Busca notícias, releases e publicações recentes do IBGE' (searches recent news, releases, and publications from IBGE). This distinguishes it from sibling tools that focus on structured data like regions, municipalities, tables, and indicators.

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

Usage Guidelines4/5

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

The description provides clear context and practical usage examples mapping natural language queries to parameters (e.g., 'Notícias sobre o Censo 2022' → assunto='censo'). It does not explicitly mention alternatives or exclusions, but the focus on news vs. structured data is evident from the examples and the tool name.

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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