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Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    Only one tool exists, so no possibility of ambiguity. The tool's purpose is clearly defined.

    Naming Consistency5/5

    With a single tool, naming is trivially consistent. The name 'get_numerology' follows a clear verb_noun pattern.

    Tool Count2/5

    One tool for a domain like numerology feels insufficient; many standard operations (e.g., separate tools for different number types) are missing, making the surface too thin.

    Completeness4/5

    The tool comprehensively calculates all core numerology numbers (life path, expression, etc.) and returns both text and image. Minor gaps might include alternative systems or detailed interpretations, but the core functionality is well-covered.

  • Average 4.5/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 3 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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    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

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How to sync the server with GitHub?

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

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior4/5

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

    Since no annotations are provided, the description carries the full burden. It discloses that the tool returns both structured text and a PNG image, and states it is deterministic. It does not explicitly state it is read-only, but for a get/calculator tool it is implied. Additional context like side effects or rate limits is not needed for this type of tool.

    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 efficient sentences in Korean. Every piece of information is useful: inputs, calculation details, output format, and methodology. No unnecessary words or repetitions.

    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 has no output schema, the description adequately explains the return values (structured text and PNG). It covers all necessary aspects: input requirements, calculation scope, and output form. For a simple numerology calculator, this is complete.

    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 description coverage is 100% with each parameter having a description. The tool description adds value by clarifying that the name must be in Latin alphabet and provides an example (Hong Gildong), which goes beyond the schema's description. This helps the agent properly format the input.

    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 clearly states the tool takes a name (Latin alphabet) and birthdate, calculates specific numerology core numbers including master/karma numbers, and returns structured text and a summary PNG. It specifies the Pythagorean method and deterministic nature, leaving no ambiguity about what the tool does.

    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?

    No explicit when-to-use or alternatives are mentioned, but with no sibling tools, this is less critical. The description provides clear input format guidance (Latin alphabet for name, date format) and specifies the method (Pythagorean), which helps the agent decide if this is the right numerology tool.

    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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