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dev55acc-ai

Website Content Crawler MCP Server

by dev55acc-ai
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Only one tool is exposed, so there is no chance of confusing it with another. Its purpose is clear and unambiguous.

    Naming Consistency5/5

    The single tool name 'crawl_website' uses a consistent verb_noun structure. With no other tools, there are no conflicting naming conventions.

    Tool Count3/5

    A one-tool server is borderline. The tool covers the core need, but the server feels thin and could reasonably expose additional operations like crawl status or history.

    Completeness3/5

    The server offers a direct crawl-and-extract action, but lacks supporting operations such as configurable crawling options, job inspection, or the ability to cancel or list previous runs. The surface is functional but minimal.

  • 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
    • 1 commit 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?

    With no annotations, the description carries the behavioral burden. It reveals that this is an external actor invocation, requires APIFY_TOKEN, and returns a fixed envelope, which gives the agent an honest model of what happens. It does not detail cost/time/side effects, but the core execution model is disclosed.

    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?

    Three compact sentences deliver purpose, mechanism, return shape, and a prerequisite without wasted words. The key purpose is front-loaded.

    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?

    The hard-coded return envelope compensate for the absent output schema, and the auth requirement is noted. It doesn't cover failure modes or performance expectations, but the essentials for calling and understanding the result are present.

    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 coverage is 100%, so the schema already documents all three parameters. The description adds no parameter-level meaning, but the baseline 3 is appropriate because it does not need to compensate.

    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 precise action ('Crawl a website and extract page content') plus the underlying mechanism (running the apify/website-content-crawler actor), so its purpose is clear even without siblings. It also states the return shape to help the tool be disambiguated.

    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 conveys when the tool is appropriate: when a website needs to be crawled and page text extracted. It names the required environment token and return envelope, but does not explicitly state when not to use or what alternatives might apply.

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

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

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