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MCP Compras.gov.br

compras_detalhar_preco_material

Read-onlyIdempotent

Lista as compras individuais de um item CATMAT — sem valor de preço.

Endpoint: /modulo-pesquisa-preco/2_consultarMaterialDetalhe.

⚠️ Esta tool não devolve preço. Até a v0.3.12 a docstring prometia "valor unitário homologado"; auditoria de 2026-08-05 mostrou que o DTO upstream (FtPesqPrecoCompraMaterialDetalheDTO) tem exatamente 7 campos e nenhum deles é valor:

idCompra, idItemCompra, numeroItemCompra, codigoItemCatalogo,
objetoCompra, descricaoDetalhadaItem, dataAtualizacaoFato

Confirmado nos dois sentidos: chamada crua ao upstream (fora da camada do MCP) devolve as mesmas 7 chaves, e o contrato OpenAPI oficial declara as mesmas 7. Ou seja: não somos nós que filtramos — o campo nunca existiu nesta rota. A rota 4 (serviço detalhe) tem DTO idêntico.

Para preço unitário de material use compras_pesquisar_preco_material, que devolve precoUnitario, quantidade, dataCompra e fornecedor por compra — é a fonte correta para a amostragem da IN SEGES/ME 65/2021.

Use esta tool apenas para: descrição detalhada do item como comprado, objeto da compra e rastreio do idCompra para cruzar com outras bases.

Cache 10 min.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paginaNoPágina (1-based).
data_fimNoData final da compra (YYYY-MM-DD). Quando omitida, a API usa a data atual.
data_inicioNoData inicial da compra (YYYY-MM-DD). Quando omitida, a API usa o início do ano corrente.
tamanho_paginaNoRegistros por página.
codigo_item_catalogoYesCódigo CATMAT do material. Inteiro 4-8 dígitos. Ex.: 460789.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds substantial context beyond that: it states the tool never returns price, documents the exact 7 upstream DTO fields, confirms via raw call and OpenAPI that the price field never existed, and mentions the 10-minute cache. No contradiction with annotations.

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 front-loaded with the most important warning and clearly structured with bold callouts, endpoint, field list, and usage guidance. It is longer than strictly necessary, with some redundant audit detail, but the length is largely justified by the need to correct a misleading tool name and historical docstring.

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?

The description covers purpose, non-goals, the correct sibling alternative, the exact returned fields, the endpoint, cache behavior, and usage boundaries. Combined with a complete input schema and existing output schema, nothing essential is missing for selecting and invoking the tool correctly.

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?

The input schema has 100% description coverage, with all five parameters already documented, including defaults, formats, and an example. The description adds no new parameter-level semantics, so the baseline of 3 is appropriate.

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 first sentence states a specific verb and resource: it lists the individual purchases of a CATMAT item. It immediately clarifies the critical scope limitation ('sem valor de preço') and explicitly distinguishes this tool from the price-returning sibling compras_pesquisar_preco_material.

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 description explicitly states when to use this tool ('Use esta tool apenas para: descrição detalhada do item...') and when not to use it, directing price queries to compras_pesquisar_preco_material. This is an ideal when/when-not/alternative structure.

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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TDQS

A3.6/5.0
Disambiguation3/5

Most tools target distinct resources, and descriptions are extremely detailed, often explicitly warning about look-alikes. However, there is real overlap between composite and single-purpose tools (e.g., compras_checar_sancoes_fornecedor vs compras_perfil_fornecedor_completo vs compras_sancao_*), and similar-looking pairs like compras_contratos_consultar vs compras_contrato_comprasnet_consultar or compras_arp_listar vs compras_pncp_atas_listar require careful reading. With 100 tools, an agent will still face meaningful selection ambiguity.

Naming Consistency3/5

The dominant pattern is snake_case with a compras_ prefix, but the order and style vary: some are domain-first (compras_catmat_buscar), some are verb-first (compras_buscar_contratacoes_similares), and some are bare entity names with no verb (compras_sancao_ceis, compras_pncp_modalidades). The many listar/consultar/buscar variants are readable, but the convention is not predictable enough for a 100-tool surface.

Tool Count1/5

100 tools is an extreme count for any MCP server, regardless of domain breadth. Even if each tool has a legitimate upstream endpoint, this volume will heavily tax context windows and make reliable tool selection harder. Many tools could be consolidated into parameterized families (e.g., contratos, sancoes, pncp resources).

Completeness4/5

The server covers the Brazilian procurement domain remarkably well: catalogs, ARPs, 14.133 contracts, legacy regime, price research, suppliers, sanctions, PGC/PCA, PNCP, and Comprasnet contract subresources. Minor gaps remain, such as listing a supplier's full contract history without specifying an órgão, and some upstream limitations are only papered over with client-side workarounds.