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anujmv

mcp-doc-search

by anujmv
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Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one for searching documents with snippets, the other for retrieving full text by ID. No ambiguity exists.

    Naming Consistency5/5

    Both names follow a consistent verb_noun pattern in snake_case (search_docs, get_document), making them predictable and easy to distinguish.

    Tool Count4/5

    With only two tools, the server is minimal but adequately scoped for a focused document search and retrieval purpose. It is slightly thin but not inappropriate.

    Completeness5/5

    The tool surface covers the essential workflow for a read-only document search: searching and retrieving full documents. No obvious gaps for its stated purpose.

  • Average 4.1/5 across 2 of 2 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

  • 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

  • Behavior3/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns 'snippets' but does not elaborate on ordering, pagination, authentication, or scope constraints beyond 'local document set'. This is adequate but not fully transparent.

    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 with no extraneous words. The first sentence states the core function, and the second provides usage guidance. It is front-loaded and efficient.

    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 tool's simplicity (2 parameters, no output schema, one sibling), the description covers the main purpose and usage context. However, it lacks explicit details about the output structure (e.g., format of snippets), which would be beneficial since no output schema is provided.

    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 both parameters. The description does not add any semantic detail beyond what the schema provides, such as clarifying the nature of snippets or the meaning of the limit parameter. Thus, 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 specifies the verb 'search' and resource 'local document set', and distinguishes from the sibling tool 'get_document' by implying it is for retrieval of specific documents, while search_docs is for searching and returning snippets.

    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 says 'Use this to ground answers in real sources before responding', providing clear context for when to use the tool. However, it does not explicitly state when not to use it or mention alternatives like get_document.

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

  • Behavior3/5

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

    No annotations exist, so description carries full burden. It indicates read-only behavior by 'Return the full text' but does not disclose error handling, auth requirements, or rate limits. Minimal behavioral context beyond purpose.

    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?

    Single sentence efficiently conveys action, subject, and purpose without redundancy. Every word earns its place.

    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?

    Tool is simple with one parameter and clear purpose. Description covers use case and expected input. No output schema, but return type is implied as 'full text'. Complete for this context.

    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% with description of id as 'Document id, e.g. a filename returned by search_docs'. The tool description adds 'for citation or deeper reading' but no new parameter-specific information beyond the schema. 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?

    Description clearly states verb 'Return' and resource 'full text of a document', specifying the identifier (id as filename) and use case (citation or deeper reading). It distinguishes from sibling search_docs, which is for searching, by focusing on retrieval.

    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 phrase 'for citation or deeper reading' implies use after search_docs, but no explicit when-to-use or when-not-to-use guidance is provided. It gives context but lacks exclusions or alternatives.

    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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