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RichardDillman

Googlebot Simulator MCP

by RichardDillman
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TypeScript

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion between tools. The tool's purpose is clearly distinct by default.

    Naming Consistency5/5

    The single tool name 'simulate_googlebot' follows a clear verb_noun pattern and is descriptive. With only one tool, there are no naming inconsistencies.

    Tool Count3/5

    One tool is on the low end, but it is well-scoped to a specific use case (simulating Googlebot). It feels slightly thin but not inappropriate for its narrow domain.

    Completeness4/5

    The tool covers the main aspects of simulating Googlebot crawling (user-agent, idle detection, event capture, timing, screenshots). No obvious gaps for its stated purpose, though it is a single tool.

  • Average 4.2/5 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

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  • 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?

    No annotations exist, so the description fully carries the transparency burden. It discloses key behaviors: authentic user-agent, requestIdleCallback simulation, network interception, and capture of timing/events/screenshots. It doesn't mention limits or error handling, but the transparency is high.

    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 concise and well-structured: a one-line summary, a bulleted list of features, and a bulleted list of use cases. Every sentence is informative with no redundancy.

    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 three parameters (one nested), no output schema, and no annotations, the description covers the tool's purpose, behavior, and use cases adequately. It mentions return values (timing, events, screenshots) but lacks details on output format. Still, it is complete for the 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?

    Schema description coverage is 100%, so the schema already documents parameters well. The description adds context about the tool's purpose (e.g., capturing analytics events) that complements the eventPattern parameter, but it does not provide new parameter-level details beyond the 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 'Simulate Googlebot crawling a page and capture analytics events.' It provides a specific verb and resource, and lists detailed behaviors and use cases. Without sibling tools, it effectively distinguishes itself.

    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 explicitly lists four verification scenarios ('Use this to verify:...'), providing clear usage context. It lacks explicit alternatives or when-not-to-use statements, but the absence of sibling tools reduces the need for exclusion guidance.

    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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  • 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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