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Carrefour Drive MCP

Carrefour Drive MCP

by maximeallanic
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_advantage_codes

Retrieve active advantage codes for your Carrefour France account, including discount amounts, validity dates, and conditions, to apply available promotions to your shopping.

Instructions

Retrieves the advantage/promo codes available to the authenticated user on Carrefour France. Returns a list of advantage codes with details such as code value, validity start/end dates, reward amount, reward type, label description (e.g. immediate discount on a minimum purchase), whether it is for new customers only, validity slot, and terms and conditions. (requires an authenticated Carrefour session)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_advantage_codes"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It implies a read-only operation by stating 'retrieves' and 'returns', and explicitly mentions the authentication requirement. However, it does not state that no data is modified, nor does it disclose error conditions or rate limits.

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?

The description is a single dense sentence listing many return fields with examples. It is informative but somewhat run-on; splitting into structured bullets or shorter sentences would improve readability without losing content.

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?

Since there is no output schema, the description compensates well by listing the return fields (code value, dates, reward amount, type, label, new customer flag, validity slot, T&C). It also states the authentication requirement. Lacking are any notes on pagination, result limits, or error handling, but for a simple list retrieval, this is nearly sufficient.

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

Parameters4/5

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

The tool has zero parameters and the schema is empty, so description covers all necessary semantics implicitly. Baseline for no-parameter tools is 4, and no additional parameter explanation is needed.

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?

Description clearly states the tool retrieves advantage/promo codes for the authenticated user on Carrefour France, with a list of specific return details. This distinguishes it from sibling tools like get_loyalty_coupons by focusing on 'advantage codes'.

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?

The description notes it requires an authenticated Carrefour session, which implies when to use, but it does not explicitly exclude or compare to similar loyalty/coupon tools. No alternatives are mentioned, and there is no guidance on when not to use.

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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