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SiddarthaKoppaka

Car Deals Search MCP Server

by SiddarthaKoppaka
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as searching for car deals, making it impossible for an agent to misselect among non-existent alternatives.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'search_car_deals' follows a clear verb_noun pattern, and there are no other tools to create inconsistency or mixed conventions.

    Tool Count2/5

    A single tool is too few for a server named 'Car Deals Search MCP Server', which implies a broader domain of car deal operations. While search is a core function, the lack of tools for filtering, sorting, or managing deals (e.g., save, compare) makes the set feel thin and incomplete for the apparent scope.

    Completeness2/5

    The tool set is severely incomplete for the domain of car deals search. It only provides a basic search function, with obvious gaps such as no tools for refining searches (e.g., by price, mileage), viewing deal details beyond listings, or interacting with deals (e.g., saving favorites). This will likely cause agent failures when more complex tasks are required.

  • Average 3.5/5 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

  • This repository is licensed under MIT License.

  • 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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It discloses that the tool searches across multiple sources and returns listings with specific fields. However, it does not mention any limitations, rate limits, authentication requirements, or what happens if no results are found. It does not contradict anything, but it lacks depth in behavioral disclosure beyond the basic function.

    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, concise sentence that front-loads the primary action and result. Every part is informative with no waste. It efficiently communicates the tool's purpose without unnecessary elaboration.

    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?

    Despite 12 parameters and no output schema, the description provides enough context by mentioning the return fields (prices, mileage, deal ratings, links). It does not explain ordering, pagination, or error handling, but the schema covers parameter semantics. Given the tool's complexity, it is reasonably complete, though slightly more detail on result behavior would justify a 5.

    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 schema provides 100% coverage with descriptions for every parameter. The tool description does not add additional parameter-specific semantics beyond what the schema already states, such as the use of 'maxResults' or 'oneOwner'. Per the baseline rule, since schema coverage is high, a score of 3 is appropriate.

    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 states a specific verb ('Search'), a specific resource ('car deals'), and names the sources (Cars.com, Autotrader, KBB) and return types (prices, mileage, deal ratings, links). It is clear and distinct, though there are no sibling tools to differentiate from. The purpose is unambiguous.

    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 clearly implies usage: search for car deals using the provided filters. Since no sibling tools are listed, there is no need to specify alternatives or exclusions. The context is clear, but it does not explicitly state when not to use or what alternatives exist. Given the absence of siblings, this is adequate.

    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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