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Use-Keen

UseKeen Documentation MCP Server

by Use-Keen
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JavaScript
Remote

Server Quality Checklist

67%
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 ambiguity or overlap between tools. The single tool has a clear and distinct purpose focused on searching documentation.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'usekeen_package_doc_search' follows a descriptive pattern.

    Tool Count2/5

    One tool is too few for a server that appears to cover documentation search for packages and services. This minimal set limits functionality and suggests an incomplete or narrow implementation for the domain.

    Completeness2/5

    The tool set is severely incomplete for a documentation server. It only provides search functionality, lacking essential operations like browsing documentation categories, retrieving specific documents, or managing documentation updates, which are typical for such domains.

  • Average 3.2/5 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 is passing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that queries should be specific for best results, hinting at search behavior, but lacks critical details: it doesn't specify the source of documentation (e.g., official docs, community resources), whether it performs real-time web searches or uses a cached index, potential rate limits, authentication needs, or error handling. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

    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 concise and front-loaded: the first sentence states the core purpose, and the second adds usage guidance. Both sentences earn their place by providing essential information without redundancy. However, it could be slightly more structured by explicitly separating purpose from guidelines, but it's efficient overall.

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

    Completeness3/5

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

    Given the context: no annotations, no output schema, 2 parameters with full schema coverage, and no sibling tools, the description is moderately complete. It covers the basic purpose and offers query specificity advice, but it lacks details on behavioral aspects (e.g., search scope, result format, limitations) that would be crucial for an AI agent to use it effectively. Without an output schema, the description doesn't explain return values, which is a gap, but the schema handles parameters well.

    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?

    The input schema has 100% description coverage, with clear explanations for both parameters: 'package_name' and 'query'. The description doesn't add any additional semantic information beyond what the schema provides (e.g., it doesn't clarify parameter interactions or provide examples not in the schema). According to the rules, with high schema coverage (>80%), the baseline score is 3 even without param info in the description.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Search documentation of packages and services to find implementation details, examples, and specifications.' This specifies the verb (search), resource (documentation), and target (packages/services). However, without sibling tools, it cannot demonstrate differentiation from alternatives, so it doesn't reach the highest score.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides some usage guidance: 'The user's query should be as specific as possible to get the best results.' This implies that vague queries may yield poor results, offering practical advice. However, it doesn't explicitly state when to use this tool versus alternatives (e.g., general web search or other documentation tools), and there are no sibling tools to compare against, so the guidance is limited to query specificity.

    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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  • Evaluate tool definition quality.

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