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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

leboncoin_search

Search public Leboncoin listings by location and return listing cards as clean JSON; excludes contacts, seller profiles, accounts, and transaction data.

Instructions

Search Leboncoin public listings. Returns public listing cards from one Leboncoin location page. This endpoint excludes contacts, seller profiles, accounts, and transaction data.

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": {
      "location": "<location>"
    },
    "name": "leboncoin_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
locationYesPublic Leboncoin location slug

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.2

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses useful behavioral context: it returns public listing cards from a single location page, and explicitly excludes contacts, seller profiles, accounts, and transaction data. However, it omits other important traits such as pagination behavior, rate limits, authentication requirements, or total result counts.

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?

Three tightly written sentences with no wasted words. The core purpose is front-loaded, followed by return format and exclusions, making it easy to scan and understand quickly.

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 simple one-parameter search tool with no output schema, the description is mostly complete: it covers the purpose, return format, and exclusions. It lacks details on pagination or result limits, which would be helpful for a search tool, but the essential information needed to invoke it correctly is present.

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 baseline is 3. The description adds minor context by implying that the location parameter determines which Leboncoin location page is used, but it does not provide additional syntax, format, or meaning beyond what the schema already states ('Public Leboncoin location slug').

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 states a specific verb (Search) and resource (Leboncoin public listings), and clarifies the return format (public listing cards from one location page). It implicitly distinguishes from the sibling leboncoin_listing by focusing on search rather than detail, but does not explicitly name or contrast with that sibling.

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?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of when-not to use it, nor any explicit reference to the sibling leboncoin_listing or other search tools. Usage is only implied by the tool name and purpose.

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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