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Dados Abertos Senado BR MCP

by io.github.SidneyBissoli

Horas extras de servidores

senado_horas_extras
Read-onlyIdempotent

Horas extras pagas a servidores do Senado em ano/mes de referência (a partir de 2013). Para perguntas de maior/menor/média/mediana/distribuição/ranking ('quem recebeu mais horas extras', 'valor mediano de hora extra', 'distribuição dos pagamentos') use estatisticas=true: computa min/máx/média/mediana/desvio/percentis sobre TODAS as linhas filtradas (valorTotal) e devolve top/bottom (padrão 10) com identificadores. Sem agruparPor → distribuicao das linhas individuais + top/bottom; com agruparPor (nome/competencia) → grupos[] ranqueados por soma decrescente (grupos[0] = quem mais recebeu; por nome soma as linhas do mesmo servidor no mês), cada um com sua mini-distribuição. Sem estatisticas: retorna { ano, mes, count, total, valorTotal, horasExtras[] }, onde valorTotal soma o gasto do mês e cada item traz nome, valorTotal, horasExtras, competencia e pagamento. Filtro opcional por nome (busca parcial) e limite (padrão 100, máx 500; ignorado quando estatisticas=true). Para a remuneração completa do servidor use senado_remuneracoes_servidores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
anoYesAno de referência
mesYesMês de referência
nomeNoNome do servidor (busca parcial)
topNNoTamanho das listas top/bottom quando estatisticas=true sem agruparPor (padrão: 10, máx: 100)
limiteNoMáximo de resultados (padrão: 100; ignorado quando estatisticas=true)
agruparPorNoQuando estatisticas=true, ranqueia os grupos por soma decrescente (grupos[0] = quem mais recebeu): `nome` soma as linhas do mesmo servidor no mês, `competencia` agrupa por mês de prestação. Cada grupo traz sua mini-distribuição
estatisticasNoComputa estatísticas (min/máx/média/mediana/percentis) + ranking top/bottom sobre todas as linhas filtradas. Use para 'quem recebeu mais/menos', 'média', 'mediana', 'ranking'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A5/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/destructive annotations, the description discloses detailed runtime behavior: statistics computation, top/bottom defaults, grouping semantics, output structure, and the fact that `limite` is ignored when `estatisticas=true`. This significantly enriches the agent's mental model and does not contradict any annotation.

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 dense but well-structured, with bolded mode labels, conditional branches, and clear separators. Every sentence adds operational value, and the alternative tool reference is placed at the end without bloating the core guidance.

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?

Despite having 7 parameters and two distinct behavioral modes, the description covers all major decision points: when to use statistics, what grouping achieves, output shape in both modes, optional filters, and the relationship to a sibling tool. With annotated safety hints and an output schema present, nothing essential is missing.

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

Parameters5/5

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

With 100% schema description coverage, the baseline is already 3, and the description adds substantial cross-parameter semantics: how `estatisticas` changes the whole response shape, how `agruparPor` works only within statistics mode, and how `limite` behaves differently in each mode. This goes well beyond repeating the 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 starts with a specific verb+resource: 'Horas extras pagas a servidores do Senado em ano/mes de referência' and clearly scopes the tool to overtime payments. It also distinguishes itself from the directly related sibling `senado_remuneracoes_servidores` by stating 'Para a remuneração completa do servidor use senado_remuneracoes_servidores', making its purpose unmistakable.

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 when to call with `estatisticas=true` versus without it, including concrete example queries like 'quem recebeu mais horas extras'. It also names the alternative tool for full remuneration, and explains the interaction of `agruparPor` with statistics mode, so an agent can route correctly without extra inference.

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

A4.1/5.0
Disambiguation2/5

Several tools perform overlapping functions (e.g., senado_buscar_materias vs senado_search_processos, senado_contratos vs senado_contratacoes_lista, and three e-cidadania consultation tools). Although descriptions are detailed, an agent can easily select the wrong one without deep inspection.

Naming Consistency3/5

All tools share the 'senado_' prefix, but the pattern is inconsistent: some use Portuguese verbs (buscar, listar, obter), others English 'search', and some are bare nouns (senado_ceaps, senado_mesa, senado_vetos). This mixed convention reduces predictability.

Tool Count2/5

67 tools is far above the 25 threshold, indicating an overgrown surface. While each tool may serve a niche endpoint, the sheer number makes it difficult for an agent to choose efficiently, and many tools could be consolidated.

Completeness4/5

The toolset covers nearly every aspect of Senate open data (legislative, senatorial, committee, administrative, financial, e-cidadania) with list/detail/searches. Minor gaps exist, such as no direct consolidated contract search, but most workflows can be achieved.

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