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MCP Compras.gov.br

compras_pesquisar_preco_servico

Read-onlyIdempotent

Pesquisa preços praticados em compras de serviço (CATSER).

Endpoint: /modulo-pesquisa-preco/3_consultarServico. Para visão consolidada (mediana, média, desvio no padrão IN 65/2021), use a tool composta compras_pesquisar_precos_para_etp com tipo='servico'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ufNoSigla da UF.
paginaNoPágina (1-based).
data_fimNoData final (YYYY-MM-DD).
codigo_uasgNoCódigo UASG.
data_inicioNoData inicial (YYYY-MM-DD).
tamanho_paginaNoRegistros por página.
codigo_municipioNoCódigo IBGE do município.
codigo_item_catalogoYesCódigo CATSER do serviço. Inteiro 4-6 dígitos. Ex.: 27332.

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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds meaningful context beyond those: it identifies this as a direct/raw price search rather than a consolidated statistical view, and gives the concrete endpoint. No contradiction with annotations exists.

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 two sentences with no filler. The primary purpose is stated first, followed by the endpoint and the alternative for consolidated results. Every sentence earns its place.

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

Completeness4/5

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

With 100% parameter documentation, rich annotations, and an output schema, the description needs to carry less burden. It provides the essential routing context and endpoint. Slightly more detail about what distinguishes this from compras_detalhar_preco_servico would make it fully complete, but nothing critical is missing.

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%, so the schema documents all parameters including codigo_item_catalogo with format and example. The description adds no extra parameter-level semantics, so the baseline score 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 description states a specific verb and resource: it searches practiced prices for service purchases (CATSER), which clearly distinguishes it from material price search and other siblings. It also names the endpoint and the composed alternative, so the tool's role is unambiguous.

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 tells the agent when to use a different tool instead: for a consolidated view (median, mean, deviation per IN 65/2021), use compras_pesquisar_precos_para_etp with tipo='servico'. This gives clear routing guidance beyond what the schema provides.

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.