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Carrefour Drive MCP

Carrefour Drive MCP

by maximeallanic
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

autocomplete_search

Fetches autocomplete suggestions for a query on Carrefour France, returning suggested terms with highlights and search links. Powers search bar typeahead features.

Instructions

Retrieves search autocomplete suggestions for a query on Carrefour France. Returns a list of suggested search terms with their highlighted text, plain text, and corresponding search links. Useful for powering a search bar autocomplete/typeahead feature.

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": {
      "q": "<q>"
    },
    "name": "autocomplete_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
qYesThe search query string to get autocomplete suggestions for. Can be empty or partial text typed by the user.
maxResultsNoMaximum number of autocomplete suggestions to return.
productCardNoWhether to include product card data in the suggestions response.

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 provided, the description carries the full burden for behavioral disclosure. It mentions the output includes 'highlighted text, plain text, and corresponding search links', which gives some transparency about the response structure, but it does not disclose potential side effects (e.g., whether it triggers sessions), error conditions, rate limits, or required authentication. The description adds value beyond the schema but lacks depth for a network read operation.

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 with no wasted words. It front-loads the purpose and includes essential response details, making it concise and well-structured. Every sentence earns its place.

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?

The tool has 3 parameters, 100% schema coverage, and no output schema, but the description does not explain the return format in detail (e.g., whether it returns an array of objects with fields for highlighted/plain text and links). It mentions the response includes these elements, which is helpful, but lacks details on pagination, default behavior, or error handling. Given the simplicity, a score of 3 is adequate but not outstanding.

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?

Schema description coverage is 100%, so the schema already documents all three parameters (q, maxResults, productCard). The description adds little beyond stating that 'q' can be empty or partial text, which is already implied by the schema. It does not explain the interaction between 'maxResults' and 'productCard' or their impact on the response, but the baseline of 3 is appropriate because the schema handles the parameter details.

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 states a specific verb ('Retrieves') and resource ('search autocomplete suggestions for a query on Carrefour France'), distinguishing it from sibling tools like 'search_products' and 'get_products_by_query' by focusing on autocomplete/typeahead behavior. It clearly indicates the purpose is to power a search bar autocomplete feature.

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 for when to use the tool ('for powering a search bar autocomplete/typeahead feature'), but does not explicitly mention when not to use it or contrast it with alternatives like 'search_products' or 'get_products_by_query'. The context is sufficient for typical selection, but exclusions are missing.

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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