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damonwill78-a11y

clean-markdown-mcp

by damonwill78-a11y
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.1.3

  • Disambiguation5/5

    With only a single tool, there is no possibility of confusion or overlap. The tool's purpose is clear and distinct by definition.

    Naming Consistency5/5

    The tool name 'scrape_url' follows a clear verb_noun pattern, which is consistent with common MCP naming conventions. With only one tool, the pattern is trivially consistent.

    Tool Count4/5

    The server has only 1 tool, which is below the typical 3-15 range. However, it is appropriately scoped for a highly focused purpose: fetching and converting web pages to clean markdown. The single tool fully covers the server's stated function.

    Completeness5/5

    The domain is 'clean-markdown', and the single tool provides a complete lifecycle: it fetches any web page and returns clean markdown, covering all necessary functionality. There are no obvious gaps for the stated purpose.

  • Average 4.3/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 9 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?

    Since no annotations are present, the description carries the full burden. It discloses that the tool strips navigation, ads, cookie banners, scripts, and other boilerplate, and outputs clean Markdown. This gives the agent meaningful behavioral expectations, though it does not cover error handling or rate limits, which would be desirable but not essential for this tool type.

    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 two sentences, front-loaded with the core functionality, and contains no fluff. It efficiently conveys the behavior and use case.

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

    Completeness5/5

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

    Given the tool's simplicity and the fully documented schema, the description covers the essential context. It clarifies the return format (Markdown) and the cleaning behavior, which is important because there is no output schema. The description is complete for 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?

    Schema description coverage is 100%, so the schema already fully documents each parameter. The description adds no extra meaning beyond what the schema provides for url, renderJs, and includeLinks. The baseline score of 3 is appropriate.

    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 states a clear verb-resource pair: 'Fetch any web page and return its main content as clean, readable Markdown.' It also specifies the cleanup behavior, making the tool's purpose unmistakable. No sibling tools exist, so no differentiation is needed.

    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 a clear usage context: 'Ideal for feeding article or documentation content to an LLM.' It implies the tool is for extracting clean main content, but does not explicitly mention when not to use it or list alternatives (none exist). The use case guidance is sufficient.

    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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