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payments-toolkit-mcp

payments-toolkit-mcp

by ramigs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Validate Card Number

validate_card_number

Validate a credit card number via the Luhn checksum. Input digits only, 8–19 characters.

Instructions

Checks whether a card number passes the Luhn checksum algorithm. Accepts digits only (spaces/dashes should be stripped by the caller).

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": {
      "cardNumber": "<cardNumber>"
    },
    "name": "validate_card_number"
  }
}

Input Schema

NameRequiredDescriptionDefault
cardNumberYes

Output Schema

NameRequiredDescriptionDefault
validYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It states the algorithm (Luhn) and input requirements (digits only, spaces/dashes stripped by caller), which is useful. However, it does not disclose what happens on invalid input (e.g., return value or error behavior) or any other side effects, leaving some gaps.

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 two sentences, front-loaded with the core purpose, and every sentence adds value. No wasted words.

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?

Given the tool's simplicity (one parameter, clear algorithm) and the presence of an output schema, the description is fairly complete. It covers the algorithm, input constraints, and caller responsibility. It could mention the return format (boolean) but the output schema likely covers that, so this is adequate.

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?

The schema has 0% description coverage, so the description must compensate. It explains that the cardNumber should be digits only and that spaces/dashes should be stripped, which adds meaning beyond the schema's pattern. However, it does not explain the expected format beyond digits (e.g., length range) or the meaning of the return value, so it only partially compensates.

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's purpose: 'Checks whether a card number passes the Luhn checksum algorithm.' It uses a specific verb ('checks') and resource ('card number'), and the mention of the Luhn algorithm distinguishes it from sibling tools like detect_card_type and validate_iban.

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

Usage Guidelines4/5

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

The description provides clear context on when to use the tool (to validate a card number via Luhn) and includes a usage note about stripping spaces/dashes. However, it does not explicitly state when not to use it or mention alternatives like validate_iban for other validation needs.

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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