cep
Pontos CNEFE de um CEP, com lat/lon IBGE.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| cep | Yes | 8 dígitos, com ou sem hífen |
Pontos CNEFE de um CEP, com lat/lon IBGE.
| Name | Required | Description | Default |
|---|---|---|---|
| cep | Yes | 8 dígitos, com ou sem hífen |
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?
With no annotations, the description carries the full burden of explaining behavior. It communicates that the tool provides CNEFE points with IBGE lat/lon, implying a read-only lookup, but it does not disclose response shape, error behavior, or any limitations.
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 very short and free of filler; every word contributes to identifying the tool's purpose. It is concise rather than merely underspecified, though it lacks a complete sentence structure.
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?
For a one-parameter lookup tool, the description plus schema covers the essential invocation details. However, there is no output schema and no expansion of the CNEFE acronym, so an agent unfamiliar with the domain may not fully anticipate the returned data shape.
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?
The schema fully documents the only parameter, including the expected format ('8 dígitos, com ou sem hífen'). The description adds no additional parameter semantics, so the schema-driven baseline 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 specifies the resource ('Pontos CNEFE'), the input ('CEP'), and the key data attribute ('lat/lon IBGE'). It stops short of using an explicit verb like 'returns' or 'lists', but the meaning is clear enough to distinguish this from a generic CEP lookup tool.
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?
No guidance is given about when to use this tool versus any sibling such as 'raio', 'proximo', or 'buscar'. The only implied context is that the caller must provide a CEP, which is already visible in the input schema.
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 target distinct resources and query patterns: text search, CEP lookup, nearest point, radius search, and company queries are generally separable. Some overlap exists between cep/unidades and empresas/vizinhanca, but the descriptions clarify the intended use.
Naming is inconsistent: api_index uses snake_case while all others are single lowercase words, and the names mix Portuguese and English, as well as verbs (buscar) and nouns (cep, unidades, raio). There is no clear verb_noun or other consistent convention.
Ten tools is a well-scoped count for a geodata/API-focused server. Each tool covers a meaningful aspect of the domain, and the set does not feel padded or overly large.
The domain is read-only geospatial and registry data, and the tools cover textual search, CEP lookup, CNEFE points and units, nearest-point queries, radius searches, company data by CEP or radius, and API health. No major lifecycle or operational gaps are apparent for the stated purpose.