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loukach

Stock API MCP Server

by loukach

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    With only one tool, there is no possible ambiguity or overlap. The tool's purpose is clear and singular.

    Naming Consistency5/5

    The single tool name 'search_vehicles' follows a clean verb_noun convention. Consistency is not an issue with one tool.

    Tool Count3/5

    A single tool feels thin for a server named 'Stock API MCP Server', but the tool itself is comprehensive in scope, providing search, counts, and refinements. It borders on acceptable but likely needs more tools for full coverage.

    Completeness1/5

    The server only offers search functionality. Missing essential operations like creating, updating, or deleting vehicle records, making the surface severely incomplete for a stock/inventory management domain.

  • Average 3.3/5 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.

  • 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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    }

    Then . Browse examples.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 provided, the description carries the full burden of behavioral disclosure. It does disclose that the output includes total counts and representative examples, which is useful. However, it does not mention whether the operation is read-only, whether results are paginated, how 'refinement suggestions' behave, or any other side effects or limitations. It provides moderate transparency but lacks depth.

    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 long and every word adds value. The first sentence states the core function, and the second clarifies the output structure (counts and sample listings). It is concise, front-loaded, and easy to parse for an AI agent. No unnecessary phrases or repetition.

    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?

    Given the tool has 7 parameters and no output schema, the description provides a high-level overview but not enough detail to fully understand the expected return shape or how to construct effective queries. It mentions counts and examples, but does not clarify whether the response is a JSON object with fields for counts and arrays for vehicles. It is adequate but leaves gaps for an agent to fully invoke the tool correctly.

    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?

    The input schema provides detailed descriptions for all 7 parameters, so the description does not need to repeat them. The description mentions fields like make, fuel, and condition, which aligns with schema properties, but adds no additional semantics about how parameters interact or are formatted. With 100% schema coverage, the baseline of 3 is appropriate.

    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 identifies the tool as a vehicle inventory discovery tool with a specific output: overview counts and sample listings. It goes beyond a mere restatement of the name, though the verb 'Discover' is less specific than 'Search'. With no sibling tools provided, it cannot distinguish from alternatives, so it misses the top score.

    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 explicit guidance is given about when to use this tool over alternatives or when not to use it. The description implies it is for browsing/overviewing inventory, but does not state target use cases, prerequisites, or exclusions. Since there are no sibling tools, some implicit context may exist, but the description itself provides no usable comparison or situational guidance.

    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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  • Confirm that the MCP server is working as expected.
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  • Evaluate tool definition quality.

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