ANVISA: Processo, 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 |
|---|---|---|---|
| protocolo | No | ||
| expediente | No | ||
| numero_processo | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare the tool as read-only, idempotent, non-destructive, and not open-world. The description adds context about the data being the same as available to citizens and not confidential, which is useful for compliance. However, it doesn't add much about behavioral traits that aren't already covered by annotations. It mentions the commercial model (prepaid credits) which is a behavioral trait. Overall, it's a bit beyond what annotations say, but not extensively. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a bit long but provides relevant legal and commercial context. It front-loads the purpose ('ANVISA: Processo, consulta em fonte oficial') and then adds context about hosting, credits, and LGPD. For an AI agent, this context is useful for legal compliance decisions. It could be more concise, but the structure is logical.
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?
The tool is relatively simple: a query with 3 optional parameters. The annotations cover safety (readOnly) and idempotency. The description adds legal context (LGPD, data control). However, it lacks information about the output format or any specifics about the query parameters (e.g., are they mutually exclusive? do they accept wildcards?). Given the simplicity of the tool, the description is mostly complete, but the absence of output schema and lack of parameter documentation leave some gaps.
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 coverage is 0%, meaning the description does not explain any of the three parameters (protocolo, expediente, numero_processo). However, the parameter names are in Portuguese and are relatively self-explanatory to a Portuguese speaker: protocol number, expediente (docket), and process number. The baseline for 0 params is 4, but with 3 params and 0% coverage, the description should compensate. It does not elaborate on when to use which parameter or if any are preferred. The names are clear but the description adds no additional meaning beyond what the schema field names imply, so a score of 3 is appropriate.
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 ANVISA processes from an official source. It is somewhat generic ('consulta') but the specificity of 'Processo' with 'fonte oficial' ties it to the ANVISA domain. It lacks an explicit comparison to sibling tools, but the name ('anvisa_processo_consultar') is quite specific and the description accurately reflects the action of querying process information. A minor deduction because it could be more explicit about what type of 'processo' (administrative, sanitary, etc.) but the domain context makes it clear.
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 mentions the platform is hosted, uses prepaid credits, and that the client is the data controller (LGPD context). However, it doesn't explicitly state when to choose this tool over alternatives or exclude any use cases. The sibling list includes 'connect', 'marketplace' which might be alternatives for accessing data, but the description doesn't provide a comparison. It implies usage context but lacks explicit guidance on when to use this tool vs others.
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.
The ANVISA consultation tool is clearly distinct, but several platform tools overlap: authenticate and connect both concern connection/auth, and marketplace and toolkit_info both expose catalog/install state. Detailed descriptions help separate them, so misselection is possible but not constant.
Most tools use lowercase English single-word names, while the actual domain tool uses Portuguese snake_case (anvisa_processo_consultar). The set mixes languages and naming styles, with no consistent verb_noun pattern across the server.
Seven tools is not inherently too many, but six are generic platform infrastructure tools (auth, marketplace, version, toolkit state) and only one serves the declared ANVISA Processo purpose. The count is misleading because the server's apparent scope is a single domain lookup.
The named domain is represented by one generic consultar operation, with no explicit listing, filtering, or related process/document operations. For a simple citizen-available lookup this may be functional, but the surface is shallow and offers little workflow depth.