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webmoleai

mcp-license-audit

by webmoleai

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Only one tool exists, so there is no possible confusion between tools.

    Naming Consistency5/5

    The sole tool name 'audit-licenses' follows a clear verb_noun pattern, consistent with itself.

    Tool Count3/5

    With only one tool, the server feels thin for a license audit domain, which might benefit from separate reporting or configuration tools. However, the single tool may suffice for basic use.

    Completeness3/5

    The tool covers scanning and report generation, but lacks tools for managing license policies, viewing history, or handling exceptions, leaving notable gaps.

  • Average 3.5/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 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 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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    {
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    }

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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?

    No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It states it flags conflicts and generates reports, but does not mention side effects (e.g., whether it modifies files, requires network access, or is read-only). The agent is left guessing about permissions, mutability, and output format.

    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 sentence that directly states the tool's purpose and key features. It contains no redundant information or filler. Every word contributes to understanding, making it highly efficient.

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

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The description is adequate for a tool with one parameter and no siblings. It covers the core function but omits details about the output format of compliance reports (e.g., stdout, file) and any prerequisites. Given the lack of output schema, additional context on return values would improve completeness.

    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 for the only parameter ('packageJson'), which already explains it is the contents of a package.json file. The description adds no further meaning or constraints beyond what the schema provides. Baseline score is appropriate given full schema coverage.

    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 audits dependency licenses for compatibility issues, specifically flags GPL/AGPL conflicts and generates compliance reports. It uses a specific verb ('audit') and resource (dependency licenses), effectively communicating its purpose. With no sibling tools, differentiation is unnecessary.

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

    Usage Guidelines3/5

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

    The description implies usage for projects with dependencies and mentions specific outcomes (flagging GPL/AGPL conflicts, generating reports). However, it does not explicitly state when to use or not use this tool, nor does it provide alternative tools or context. Without siblings, the lack of guidance is acceptable but limits clarity for complex scenarios.

    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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