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shrish346

docs-rag-mcp

by shrish346
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Python
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Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between overlapping tools. The purpose of search_docs is singular and clear.

    Naming Consistency5/5

    The single tool name 'search_docs' follows a clear verb_noun pattern, which is consistent for the server's scope. There are no other names to compare, so it is perfectly consistent.

    Tool Count4/5

    A single tool for a docs RAG server is borderline but acceptable, as search is the primary function. However, it feels slightly thin, and additional tools like list_docs or get_doc could enhance usability.

    Completeness4/5

    For a documentation search server, search_docs covers the core retrieval need. Minor gaps exist such as no ability to list available document sources or fetch a specific document directly, but these are not critical for basic RAG workflows.

  • Average 3.8/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 3 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

  • Behavior3/5

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

    The description mentions 'TF-IDF retrieval,' which discloses the algorithmic approach, but provides no insight into return behavior, sorting, or side effects. With no annotations, the description carries the burden, yet it lacks detail on what happens when invoking the tool.

    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 a single, front-loaded sentence that conveys the core functionality without unnecessary words. Every word earns its place.

    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 the simple 2-parameter tool and the existence of an output schema, the description adequately covers the purpose. The schema handles parameter details, and the description completes the context. A full 5 would require more detail on expected output or limits, which is already present in schema.

    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?

    Since the schema covers 100% of parameters with descriptions, the description does not need to add parameter information. It adds no extra semantic value beyond the schema, so 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 clearly states 'Search the documentation corpus' with a specific verb and resource, and also specifies the retrieval method (TF-IDF). This clearly distinguishes the tool's purpose even without sibling tools.

    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 implies usage for searching documentation, but does not provide explicit guidance on when to use this tool versus alternatives or any prerequisites. No sibling tools are listed, so it relies on the verb 'Search' to convey its intended use.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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