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willianpinho

mcp-gateway-scan

by willianpinho
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TypeScript
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Server Quality Checklist

83%
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  • Latest release: v0.2.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion between tools. The tool's purpose is clearly described and distinct from any other potential tools.

    Naming Consistency5/5

    The single tool name 'scan_gateway' follows a clear verb_noun pattern. Naming consistency is perfect as there is only one name.

    Tool Count3/5

    One tool for a domain that covers 7 dimensions feels slightly thin; a more granular breakdown into separate tools for each dimension might improve flexibility, but the single tool is comprehensive.

    Completeness5/5

    The tool covers all 7 gateway-readiness dimensions comprehensively, providing a full static scan without obvious gaps. It is read-only, which is appropriate for scanning.

  • Average 4.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • No commit activity data available
    • Last stable release on
    • 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.

  • This repository includes a glama.json configuration file.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

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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

  • Behavior5/5

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

    Annotations already declare readOnlyHint=true, and the description adds critical behavioral details: secret values are redacted (location only, never the value), no code execution, returns per-dimension summary plus structured result. This goes beyond annotations.

    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?

    Two sentences, front-loaded with action and scope. Every sentence adds value: first defines the tool, second adds safety and output detail. No fluff.

    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?

    Despite no output schema, the description adequately explains the return format (per-dimension summary + structured result). The 7 dimensions are listed, and the redaction behavior is clarified. The tool is simple, and the description covers its operation fully.

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

    Parameters4/5

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

    Schema has 100% description coverage for both parameters. The description adds value by explaining the effect of 'ci' (reports CI gate verdict) and confirming 'path' is required. Baseline 3 is elevated to 4 due to added clarity.

    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 title and description clearly state the tool's purpose: scanning a repo/directory for production-readiness anti-patterns across 7 dimensions. The verb 'scan' and resource are specific, and the 7 dimensions are listed, making the scope 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 implies safe usage by stating 'Read-only static scan' and 'Never executes target code', but does not explicitly contrast with alternatives (though no siblings exist). The CI gate verdict behavior is explained, providing context for when to use the 'ci' parameter.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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