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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools, as there are no other tools to compare it against. The single tool's purpose is inherently distinct by default.

    Naming Consistency5/5

    A single tool cannot demonstrate inconsistency, as there are no other tool names to compare it to. The naming pattern for 'hello_tool' (snake_case) is consistent within the set, albeit trivially so.

    Tool Count2/5

    A single tool is generally too few for most server purposes, as it limits functionality and suggests an incomplete or trivial implementation. While it might be appropriate for a minimal 'hello world' server, it is inadequate for any substantive domain coverage.

    Completeness1/5

    With only one tool named 'hello_tool', it is impossible to infer a meaningful domain or assess coverage. There are obvious gaps, as no CRUD operations, lifecycle management, or typical API interactions are present, making the surface severely incomplete for any practical purpose.

  • Average 1.7/5 across 1 of 1 tools scored.

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

    • No issues in the last 6 months
    • No commit activity data available
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing
  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

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

    Then . Browse examples.

  • Add related servers to improve discoverability.

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

  • Behavior1/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Hello tool' reveals nothing about what the tool actually does operationally - whether it's a read operation, a write operation, what permissions might be needed, what side effects occur, or what the response format might be. This is a complete failure to describe behavioral traits.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness2/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    While technically concise with just two words, this is under-specification rather than effective brevity. The description fails to provide any meaningful information about the tool's function. True conciseness would efficiently convey essential information, but this description is so sparse it's essentially non-functional.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness1/5

    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 'Hello tool' is completely inadequate. It doesn't explain what the tool does, how to use it, what it returns, or any behavioral characteristics. The single parameter is well-documented in the schema, but the overall description fails to provide the contextual understanding needed to effectively use this tool.

    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 has 100% description coverage, with the single parameter 'name' clearly documented as 'The name of the person to greet.' The description 'Hello tool' adds no additional parameter information beyond what's already in the schema. With complete schema coverage, the baseline score of 3 is appropriate since the schema does all the work.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description 'Hello tool' is a tautology that merely restates the tool name without specifying what the tool actually does. It doesn't provide a verb-action combination or clarify the tool's function beyond the obvious implication from the name. While the name suggests greeting functionality, the description fails to explicitly state this purpose.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines1/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides absolutely no guidance on when to use this tool. There are no sibling tools mentioned, so differentiation isn't needed, but the description doesn't indicate any context, prerequisites, or appropriate scenarios for invoking this tool. It's completely devoid of usage instructions.

    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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