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get_company_kyb

Enterprise KYB v2: structured Brazilian registration data, CGU CEIS/CNEP sanctions, source freshness, explainable NON-credit risk heuristic. Human review required; never automatic AML/credit approval. Price: $0.10.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "cnpj": "<cnpj>"
    },
    "name": "get_company_kyb"
  }
}

Input Schema

NameRequiredDescriptionDefault
cnpjYesBrazilian CNPJ, with or without formatting. Numeric or alphanumeric (IN RFB 2.229/2024).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and delivers unusually valuable context: the $0.10 price, the sanctions sources, source-freshness reporting, an explainable heuristic, and the explicit caveat that results are never valid for automatic AML/credit approval. It omits error behavior on invalid CNPJ and any latency/rate-limit notes, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence plus disclaimer and price, front-loaded with the tool's identity and payload. Every clause earns its place (sources, heuristic nature, review requirement, cost); only the slight run-on density keeps it off a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter lookup with no output schema and no annotations, the description tells the agent what the response conceptually contains and the boundary conditions of its use. It is nearly complete; the only gaps are error/invalid-input behavior and any auth or rate-limit expectations.

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

Parameters3/5

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

There is a single required parameter with 100% schema description coverage, so the schema already documents the CNPJ format (formatted or unformatted, numeric or alphanumeric per IN RFB 2.229/2024). The description adds nothing about the parameter, which is the baseline-3 case when the schema does the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a KYB lookup that returns structured Brazilian registration data, CGU CEIS/CNEP sanctions, source freshness, and a NON-credit risk heuristic. It is specific about the resource and outputs, but never names which sibling (get_company, get_company_dossier, get_company_score, check_sanctions) it should be preferred over, leaving overlap unresolved.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Human review required; never automatic AML/credit approval' and 'NON-credit risk heuristic' imply the intended compliance context and a hard usage limit on downstream automation. However, there is no explicit guidance on when to pick this versus get_company_score, check_sanctions, or get_company_dossier, so routing is left to 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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