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RachitJava

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by RachitJava
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JavaScript
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one retrieves authenticated user details, the other lists repositories. There is no overlap or confusion between them.

    Naming Consistency5/5

    Both tools follow the consistent verb_noun pattern (get_user, list_repos), making the naming predictable and clear.

    Tool Count3/5

    With only 2 tools, the server feels thin for its name 'Navigator', which implies broader GitHub navigation capabilities. The count is borderline acceptable but does not fully earn its place.

    Completeness2/5

    The surface is severely limited: it covers only user details and repository listing, missing common operations like fetching a specific repo, listing branches, or viewing commits. Significant gaps exist for a navigation-focused server.

  • Average 4.2/5 across 2 of 2 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

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  • 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"
  ]
}

    Then . Browse examples.

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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

  • Behavior3/5

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

    No annotations are provided, so the description must carry the burden of behavioral disclosure. It clarifies that the user is the authenticated one, but it does not explicitly state that the operation is read-only, what the return format looks like, or potential errors. However, the word 'Get' strongly implies a safe read operation.

    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?

    One concise, front-loaded sentence with no wasted words. It states the action and target clearly.

    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?

    For a zero-parameter tool with no output schema, the description is adequate but could have been slightly more explicit about what 'details' includes or that it returns the profile object. It is still complete enough for an AI agent to correctly invoke the tool.

    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?

    There are zero parameters, and the schema covers 100% of the (empty) parameter set. The description adds meaning by noting the user is 'authenticated', implying no parameters are needed because the identity comes from the session.

    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 verb (Get), the resource (authenticated GitHub user), and the scope (details). It distinguishes itself from the sibling tool list_repos, which deals with repositories, by focusing on the user profile.

    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 phrase 'authenticated user' clearly implies this is for the current user's profile, and it contrasts with list_repos which handles repositories. No explicit exclusions are given, but the context is clear for such a simple tool.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

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

    With no annotations provided, the description must carry the burden of behavioral disclosure. It reveals key constraints (10 most recently updated, authenticated user scope) but does not mention whether private repositories are included, pagination behavior, or typical auth failures. This is adequate but leaves room for more detail.

    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, well-structured sentence that front-loads the verb and includes the most important qualifiers without any filler. Every word contributes to understanding.

    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?

    For a simple zero-parameter list operation, the description provides the essential context: what is listed, for whom, and the ordering/limit. It is slightly incomplete in not mentioning alternatives or edge cases, but overall adequate for the tool's low complexity.

    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?

    The tool has zero parameters, so the schema already fully covers the input surface. The description adds value by specifying the implicit scope (authenticated user) and the limit of 10, which are meaningful semantics beyond the empty schema.

    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 a specific action ('List'), the resource ('repositories'), and precise scope ('10 most recently updated', 'for the authenticated user'). It distinguishes the tool from sibling 'get_user' by focusing on repositories rather than user info.

    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 makes the intended use clear: list recent repositories for the authenticated user. It does not explicitly mention alternatives or when not to use it, but the sibling tool is clearly a different concern, so the context is sufficient without exclusions.

    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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