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Glama
ehrodan

mcp-juridico-brasil

by ehrodan

pesquisar_lexml

Find Brazilian legal documents in LexML by searching titles, subjects, or URNs. Filter by document type, locality, authority, and year range to retrieve persistent URNs, summaries, and official links.

Instructions

Pesquisa metadados juridicos no acervo oficial LexML via SRU/CQL.

Campos aceitos: todos, titulo, ementa, assunto e urn. Filtros opcionais restringem tipo de documento, localidade, autoridade e intervalo de anos. Retorna URN persistente, ementa, assuntos e link do resolvedor oficial.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campoNotodos
limiteNo
paginaNo
termosYes
ano_fimNo
ano_inicioNo
autoridadeNo
localidadeNo
tipo_documentoNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.5.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains the protocol (SRU/CQL) and the return payload (URN, ementa, assuntos, resolver link), which is useful. However, it does not disclose limitations such as pagination behavior, external service dependency, or whether the search is read-only and safe to invoke without side effects.

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 concise and well-structured: it opens with the core action and resource, then lists accepted fields, optional filters, and return values. Every sentence adds distinct value with no redundancy or filler.

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 9 parameters, no schema descriptions, and no annotations, the description is incomplete. It covers high-level functionality but misses required-parameter semantics, pagination controls, and any guidance on how fields/filters interact, so an agent lacks enough detail to invoke it correctly in all cases.

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?

The schema has 0% description coverage, so the text must compensate for the 9 parameters. It adds meaning for `campo` by listing accepted values and for the optional filters (tipo_documento, localidade, autoridade, ano_inicio, ano_fim). However, it completely omits the required `termos` parameter and the pagination parameters `limite` and `pagina`, leaving the most essential input unexplained.

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 clear, specific action: searching legal metadata in the official LexML collection via SRU/CQL. It further differentiates the tool by specifying accepted search fields, optional filters, and return values, making its purpose distinct from siblings like resolver_urn_lexml or consultar_corpus_juridico.

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 for use: searching LexML metadata with configurable fields and filters. It does not explicitly name alternative tools or state when not to use this tool, but the stated scope is enough for an agent to infer the appropriate scenario.

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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