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LeonardoDiasRR

MCP Compras Públicas Brasil

pncp_obter_orgaos_unidades_por_cnpj

Retrieve public agencies and their units by CNPJ from official Brazilian government procurement data. Find all units linked to a specific public agency's CNPJ through the PNCP.

Instructions

Consulta dados públicos de órgãos e unidades públicas; ação consultar unidades orgao no caminho /v1/orgaos/{cnpj}/unidades.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cnpjYes
formatoNoFormato da resposta: normalizado ou payload original.normalizado

Schema Changelog

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

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that the data is public and that this is a consult operation, but it does not mention pagination, response format, authentication needs, rate limits, or what happens for invalid CNPJs. For a tool with no output schema and no annotation safety hints, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the main action, but it is somewhat clumsy and redundant, repeating 'consulta' and mixing a broad statement about public data with a path-specific action. It earns no waste but is not a polished, high-quality definition.

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

Completeness2/5

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

For a tool with no output schema and no annotations, the description is incomplete: it does not describe the shape of the returned units, whether results are paginated, or any constraints on the CNPJ input. The sibling set is large and similar, so more contextual detail is needed to let an agent select and invoke this tool confidently.

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

Parameters2/5

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

Schema description coverage is only 50%, with 'formato' already documented in the schema and 'cnpj' left undocumented. The description adds only minimal meaning by embedding 'cnpj' in the path, but it does not explain the CNPJ format, accepted values, or how 'formato' affects the response. It does not compensate for the schema's missing parameter documentation.

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?

The description uses a specific verb ('Consulta') and identifies the resource as 'unidades' associated with an 'orgao' via the path /v1/orgaos/{cnpj}/unidades. It is somewhat broad because 'dados públicos de órgãos e unidades públicas' could suggest both organs and units, but the endpoint path clarifies the actual purpose and distinguishes it from sibling tools that target specific units.

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 gives no explicit when-to-use guidance and names no alternatives. It does not differentiate this tool from closely related siblings like pncp_obter_orgaos_unidades_por_cnpj_codigounidade or pncp_obter_orgaos_por_cnpj beyond the path itself. Usage context is left entirely to inference from the name and endpoint.

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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