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TheoGirardin

mcp-lbc

by TheoGirardin
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Both tools have clearly distinct purposes: one searches for ads, the other retrieves details of a specific ad. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern using snake_case: 'search_ads' and 'get_ad_detail'. This is predictable and clear.

    Tool Count2/5

    With only two tools, the server feels thin for a full-fledged classified ads platform. Typical scopes require more tools for CRUD operations and additional features.

    Completeness2/5

    The server only provides read operations (search and detail). Missing create, update, delete, or management tools, leaving significant gaps for user workflows.

  • Average 3.3/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    With no annotations, the description carries full burden for behavioral transparency. It only states the function but doesn't disclose any traits like read-only nature, required permissions, rate limits, or error behavior (e.g., if ad_id not found). The description is insufficient for understanding operational implications.

    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 sentence, immediately stating the tool's core function. It is concise with no extraneous information, and the key data points are listed briefly. Every word contributes to the purpose.

    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 retrieval tool with one parameter and an output schema, the description adequately covers what the tool does and what data is returned. It explicitly mentions common fields (description, price, location, images). The presence of an output schema means return values are defined elsewhere. Minor improvement would be to mention that ad_id is required and obtained from search_ads.

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

    Parameters2/5

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

    The input schema has one parameter (ad_id) with 0% description coverage. The description does not explain the parameter beyond the schema type and requirement. Although the parameter name is self-explanatory, the description should clarify that it is the unique identifier of the ad (e.g., from Leboncoin). Additional context is missing.

    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 verb ('Retourne'), the resource ('détail complet d'une annonce Leboncoin'), and the key fields returned (description, price, location, pictures). It distinguishes from the sibling tool 'search_ads', which likely returns a list of ads rather than full details.

    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 usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, such as needing an ad_id retrieved from 'search_ads' first. No prerequisites or limitations are mentioned.

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

  • Behavior3/5

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

    The rate limit is disclosed, but no other behavioral traits like authentication needs, data freshness, or handling of missing results are mentioned. With no annotations, the description carries full burden and only covers one aspect.

    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 extremely concise with two sentences, front-loading the purpose and rate limit constraint.

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

    Completeness2/5

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

    Given 8 parameters, an output schema, and a sibling tool, the description is insufficient. It lacks parameter guidance, pagination logic, and return value explanation, despite the output schema existing to mitigate 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 coverage is 0%, and the description only says 'with filters' without explaining any of the 8 parameters (text, category, region, etc.), leaving the agent without meaning for the inputs.

    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 it searches Leboncoin ads with filters, distinguishing it from sibling tool get_ad_detail which retrieves individual ad details.

    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 mentions a rate limit (10 requests/hour) but provides no guidance on when to use this tool versus the sibling, nor any prerequisites or limitations on filters.

    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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