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gkhays

MCP NVD Server

by gkhays
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
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 single tool 'nvd_tool' has a clear and distinct purpose of fetching CVE data from NVD.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency as there are no other tools to compare against. The name 'nvd_tool' follows a simple noun-based pattern appropriate for its function.

    Tool Count2/5

    One tool is generally too few for most server purposes, especially for a data source like NVD which typically supports multiple operations (e.g., search by CVE ID, filter by date, get recent vulnerabilities). This feels thin and limited in scope.

    Completeness2/5

    The tool surface is severely incomplete for an NVD server. While fetching CVE data is a core function, obvious gaps include searching, filtering, pagination, and accessing specific vulnerability details, which are essential for comprehensive CVE data interaction.

  • Average 2.9/5 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 Apache 2.0.

  • 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

  • Behavior2/5

    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. 'Fetch CVE data from NVD' implies a read-only operation, but it doesn't specify rate limits, authentication requirements, error conditions, response format, or whether it's idempotent. For a tool with zero annotation coverage, this is insufficient.

    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 at just four words, front-loading the essential information with zero wasted words. It efficiently communicates the core purpose without unnecessary elaboration.

    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?

    For a tool with no annotations and no output schema, the description is inadequate. It doesn't explain what 'CVE data' includes, the format of returned information, potential errors, or any behavioral characteristics. The description fails to compensate for the lack of structured metadata.

    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 description coverage is 100%, with the single parameter 'cve_id' fully documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema, so the baseline score 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 'Fetch CVE data from NVD' clearly states the action (fetch) and resource (CVE data from NVD), making the tool's purpose immediately understandable. It doesn't distinguish from siblings, but there are no sibling tools on this server, so a 4 is appropriate rather than a 5.

    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?

    The description provides no guidance on when to use this tool versus alternatives, prerequisites, or limitations. It simply states what the tool does without any context about appropriate usage scenarios or constraints.

    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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