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1clawAI

@1claw/mcp

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by 1clawAI

Server Quality Checklist

67%
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  • Latest release: v0.34.5

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion between tools. The tool's purpose is clear and distinct, leaving no ambiguity.

    Naming Consistency5/5

    A single tool name 'inspect_content' follows a clear verb_noun pattern, and with no other tools to compare against, consistency is irrelevant.

    Tool Count3/5

    One tool is borderline for a server claiming to handle multiple threat detection types. While the tool is not trivial, the scope feels thin for the described purpose.

    Completeness2/5

    The server only offers inspection capabilities. Missing tools for remediation, sanitization, or further analysis create significant gaps for a security workflow.

  • 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
    • 86 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • 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 to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 provided, the description carries full burden. It discloses that the tool returns a JSON threat report with fields (safe, verdict, threat_count, threats) and the inspection scope. It does not mention side effects, but as a non-destructive inspection, this is adequate.

    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: the first defines purpose and scope, the second covers output structure and usage. Every sentence is informative, with no wasted words or 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 no output schema, no annotations, and only 2 parameters, the description provides sufficient context: purpose, return format, and usage guidance. It could elaborate on specific threat indicators but is adequate for an agent to use correctly.

    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 documents both parameters. The description adds no additional parameter-specific meaning beyond the schema; it only lists general threat types. Baseline 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 uses a specific verb ('Inspect') and resource ('text content'), lists concrete threat types (command injection, encoding obfuscation, social engineering, PII), and clearly defines the tool's security inspection purpose. There are no sibling tools to differentiate against.

    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 states 'Use before processing untrusted input', providing clear when-to-use guidance. Although it does not explicitly mention when not to use, the context is sufficient given no sibling tools for comparison.

    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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