Polícia Rodoviária Federal: Infrações, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| placa | Yes | ||
| renavam | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / RenavamRemoved value: -{
- "type": "string"
-}Input schema / properties / completoRemoved value: -{
- "type": "boolean"
-}Input schema / properties / placaAdded value: +{
+ "type": "string"
+}Input schema / properties / renavamAdded value: +{
+ "type": "string"
+}Input schema / requiredPrevious value: -[
- "Renavam"
-]New value: +[
+ "placa",
+ "renavam"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable context: it's hosted by the platform, requires no platform credentials, charges per query with prepaid credits, and clarifies data is not confidential. This goes beyond annotations by explaining the commercial and legal aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph with several sentences, each adding distinct information: purpose, hosting, payment, data source, and legal responsibility. It's front-loaded with the core purpose. Slightly verbose due to legal disclaimers, but each sentence earns its place for a tool with compliance implications.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only 2 required parameters, no output schema, and clear annotations, the description covers the essential context: what it does, how it's accessed, cost model, and legal obligations. It doesn't explain return values, but without an output schema, that's less critical. The description is complete enough for an agent to decide when and how to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'placa' and 'renavam' implicitly by stating the tool queries infractions, but it doesn't explain the format or meaning of these parameters. The description adds minimal value beyond the schema, which only lists types. A 3 is appropriate because the parameters are self-explanatory (license plate and RENAVAM number) but the description doesn't explicitly clarify them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries Brazilian Federal Highway Police traffic infractions from an official source, with a specific verb ('consultar') and resource ('infrações'). It distinguishes itself from siblings by specifying the data source and official nature, though it doesn't explicitly contrast with other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the payment model (prepaid credits) and legal context (LGPD), which implies when to use it (for official Brazilian traffic infraction data). However, it doesn't explicitly state when not to use it or mention alternatives, and the sibling tools are mostly unrelated (auth, marketplace, etc.), so differentiation is less critical.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools serve distinct platform functions; connect and toolkit_info overlap somewhat on connection status but are clearly separated by focus (URLs/auth vs installed MCPs/accounts). The single domain tool stands apart naturally, leaving little ambiguity.
Names mix verb-based (authenticate, connect, report_bug, show_version) with noun-based (marketplace, toolkit_info) and a Portuguese domain-specific name (prf_infracoes_consultar), showing no consistent pattern beyond lowercase underscores.
Seven tools is a reasonable count, but six are generic platform utilities while only one addresses the stated PRF domain, making the set feel bloated and off-topic for a server named 'Infrações da PRF'.
The domain surface is minimal—only a single consultation tool for traffic fines with no additional operations like export, reporting, or support for different query types. The generic platform tools do not contribute to domain coverage.