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KerryanOPMace

INSEE MCP Server

by KerryanOPMace
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Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.12

  • Disambiguation5/5

    With only one tool, there is no ambiguity. The agent cannot confuse it with any other tool.

    Naming Consistency5/5

    Single tool name 'search_company' follows a clear verb_noun pattern, consistent within itself.

    Tool Count2/5

    A single search tool is too sparse for a domain like INSEE company data, which typically requires multiple operations (e.g., get details, list results, paginate).

    Completeness1/5

    The server covers only a basic search, missing essential operations like retrieving full company details, filtering, or pagination, making it severely incomplete for practical use.

  • Average 3.1/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits 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 must disclose behavioral traits. It only states 'search' but does not clarify whether exact or fuzzy matching is default, how results are returned, or any side effects. The fuzzy parameter is in the schema but not highlighted in the description.

    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 concise sentence in French, efficient and to the point. However, it could be slightly more structured by separating the search criteria or mentioning the database context more explicitly.

    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 4 parameters, no output schema, and no annotations, the description is incomplete. It does not explain the search behavior when multiple parameters are provided, the structure of results, or any limitations. More details are needed for complete understanding.

    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 baseline is 3. The tool description adds no extra meaning beyond the schema's parameter descriptions, which are adequate but minimal. No additional context is provided for parameter usage.

    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 clearly states the verb 'search' and the resource 'company in the SIRENE database' along with the search criteria (SIREN, SIRET, or name). It is specific enough to distinguish from generic search tools, though no siblings are provided.

    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 implies the tool is used to search for companies using the given identifiers but does not provide explicit guidance on when to use each parameter or when to avoid this tool. No alternatives are mentioned, which is acceptable without siblings.

    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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  • Evaluate tool definition quality.

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