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cqtrinv

mcp-trinv-server

by cqtrinv
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JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.0.7

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one searches for French communes by name fragment, the other searches for cadastral parcels by area within a commune. There is no overlap or ambiguity in their roles.

    Naming Consistency5/5

    Both tool names follow the same pattern: 'trinv-' prefix, 'chercher-' verb, and a specific object ('commune' or 'parcelle'). The naming is perfectly consistent and predictable.

    Tool Count4/5

    With only two tools, the server is slightly under the typical 3-15 range, but the narrow focus on commune and parcel search justifies the minimal count. The tools are well-scoped and each serves a distinct need.

    Completeness4/5

    The server covers the core search workflows for its domain: finding communes and then parcels within them. Minor gaps exist (e.g., no direct lookup by INSEE code), but the provided tools enable the primary use cases without dead ends.

  • Average 3.9/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • 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 the typical two-step process and the prerequisite of knowing the INSEE code, which is useful behavioral context. It does not mention return behavior, error handling, or side effects, but for a search tool the disclosed information partially addresses transparency.

    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 well-structured: a clear opening statement, a two-step numbered list, and two relevant examples. It is concise and front-loaded with the core purpose; the link and examples are useful without excessive bloat.

    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 no annotations or output schema, placing full responsibility on the description. It adequately covers the input process (commune and area) and necessary prerequisite (INSEE code), but it does not state what the tool returns, how results appear, or what happens when no matching parcel exists. For a search tool this is a significant but not fatal gap.

    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?

    Since schema coverage is 0%, the description must provide meaning. It clarifies that 'area' is in square meters and that the other parameter relates to identifying the commune, but it leaves ambiguity about whether 'fragment' expects a commune name or INSEE code. The examples use names (BEDOUS, BEURD), while the text emphasizes the INSEE code, creating uncertainty.

    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 defines the tool as searching for cadastral parcels of a certain area within a French commune, with parameters for commune and area (in m²). It provides concrete example queries (e.g., 'Y a-t-il une parcelle de surface 247 m² dans BEDOUS'). It distinguishes from the sibling tool by focusing on parcels rather than communes, but does not explicitly name the alternative, so it falls short of full sibling differentiation.

    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 outlines a two-phase workflow (specify the commune, then the area) and stresses knowing the INSEE code, giving implied usage guidance. However, it does not explicitly state when to use this tool over the sibling 'trinv-chercher-commune' or provide exclusions, leaving the comparison implicit.

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

  • Behavior4/5

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

    With no annotations, the description carries the full burden. It discloses that results include INSEE code and coordinates, warns that large result sets may not be listed, and notes that some communes have changed names or merged. This is useful behavioral context beyond a simple 'search' statement.

    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 concise and well-structured, starting with the purpose, followed by usage advice, output details, and example questions. Every sentence adds valuable information, and the link to docs is a bonus.

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

    Completeness5/5

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

    Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is complete. It covers parameter semantics, result contents, edge cases (name changes/mergers), and the practicality of result limits, leaving little ambiguity for an agent.

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

    Parameters5/5

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

    The schema provides zero description for the 'fragment' parameter, but the description thoroughly explains it as a series of consecutive letters from the commune name and gives concrete examples (BEURD → TREBEURDEN). This fully compensates for the missing schema description.

    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 tool searches for French communes by a name fragment ('chercher des communes en France à partir d'un fragment de leur nom'). It is specific about the resource and method, but it does not explicitly mention the sibling tool trinv-chercher-parcelle, so it misses the top score for sibling differentiation.

    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 gives clear context and examples of when to use the tool (e.g., 'Quelle est la commune nommée BEURD ?'). It also provides an important usage warning about being specific to avoid huge result sets (SAINT → 4834 communes). However, it does not explicitly discuss exclusions or alternatives, staying a bit short of a 5.

    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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