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mertcanvural

overlayrisk-witness-mcp

by mertcanvural
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JavaScript
Remote

Server Quality Checklist

58%
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 possibility of confusion between tools. The tool's purpose is clearly defined and distinct.

    Naming Consistency4/5

    With only one tool, naming consistency is not fully testable, but the tool name 'witness_page' follows a logical verb_noun pattern and is descriptive of its function.

    Tool Count1/5

    A single tool for a service that could reasonably include multiple related operations (e.g., different types of audits, history, or batch processing) feels extremely thin and insufficient for a cohesive server.

    Completeness1/5

    The tool performs one specific check and then directs to an external paid service for further results, leaving the agent with no ability to complete a full workflow or access additional features, making the surface severely incomplete.

  • Average 4.1/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 4 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.

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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

  • Behavior4/5

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

    The description adds behavioral details beyond annotations by explaining the witness process (loading, toggling overlays, capturing states, returning timestamped findings). It does not contradict annotations such as destructiveHint=false, and the openWorldHint=true aligns with the free tool nature.

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

    Conciseness4/5

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

    The description is efficiently structured with four sentences, each adding value: core action, process, output nature, and pricing note. Slightly verbose but front-loaded with key details, earning a 4.

    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?

    Given the simple tool with one parameter, no output schema, and annotations present, the description adequately covers the input, process, output (finding with timestamp), and a caveat. Minor gaps like exact output format are acceptable for this complexity level.

    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?

    With 100% schema description coverage for the single parameter, the baseline is 3. The description reiterates the need for a public URL, matching the schema, but adds no new semantic information beyond what the schema already provides.

    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 runs a free one-page witness for a public URL, detailing the specific process of loading with overlay on/off, capturing states, and returning a finding. It distinguishes the tool's action using specific verbs and resources.

    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 provides context by specifying the input as a public URL and noting that findings are evidence not legal rulings. While it gives good usage context, it does not explicitly state when not to use the tool or mention alternatives, but no siblings exist.

    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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