brasil-mcp-essentials

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validate_credit_card

Validate credit card numbers using the Luhn algorithm and detect the card brand (Visa, Mastercard, Elo, Hipercard, Amex, Diners, JCB, Discover).

Instructions

Valida cartão de crédito (Luhn) e detecta bandeira: Visa, Mastercard, Elo, Hipercard, Amex, Diners, JCB, Discover.

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": {
      "value": "<value>"
    },
    "name": "validate_credit_card"
  }
}

Input Schema

Name	Required	Description	Default
`value`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Jul 30, 2026

TDQS

B3.2/5.0

Behavior3/5

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

The description mentions the Luhn algorithm and brand detection, providing some behavioral context. However, without annotations, it lacks details on error behavior, constraints, or return structure.

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 a single, concise sentence that delivers the core purpose efficiently with no wasted words.

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

Completeness3/5

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

Given the simple tool and existence of an output schema, the description is minimally adequate but lacks input format details and usage context, limiting completeness.

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

Parameters1/5

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

Schema parameter coverage is 0%, and the description adds no guidance on the 'value' parameter format, valid inputs, or examples. The agent has no information beyond the parameter name.

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 clearly states the tool validates credit cards using the Luhn algorithm and detects specific brands. It effectively differentiates from sibling tools like validate_cpf and validate_cnpj.

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

Usage Guidelines2/5

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

No guidelines are provided for when to use this tool vs alternatives. The description doesn't mention prerequisites, context, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.