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BitFigther

local-docs-mcp

by BitFigther
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: listing all documents, reading a specific document with pagination, and full-text searching. No ambiguity or overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (list_documents, read_document, search_documents), making them predictable.

    Tool Count5/5

    Three tools are well-scoped for a document server, covering the essential operations without unnecessary bloat or deficiency.

    Completeness5/5

    The tool set provides listing, reading with pagination, and full-text search, which is complete for a read-only document retrieval system. No obvious gaps.

  • Average 4.3/5 across 3 of 3 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?

    Without annotations, the description carries full burden. It discloses the function returns a list with specific fields and implies read-only behavior. However, it does not mention order, pagination, or behavior for empty/error states.

    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 extremely concise with two sentences, front-loading the purpose and then listing return fields. No superfluous information.

    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?

    While the description covers the basic purpose and output, it lacks details like whether the listing is recursive, if there are any sorting defaults, or how errors are handled. For a simple list tool, this is adequate but not fully complete.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    No parameters exist, so schema coverage is complete. The description adds value by explaining what DOCS_ROOT is and what output is provided, giving context beyond the empty schema.

    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 it returns a list of documents under DOCS_ROOT, specifying returned fields (relative path, size, bytes, update timestamp). It distinguishes from siblings read_document and search_documents by focusing on broad listing.

    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 listing all documents but does not explicitly state when to use this vs. search_documents, nor does it mention any prerequisites or limitations. It lacks explicit when-to-use guidance.

    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?

    With no annotations provided, the description adequately discloses that the tool is a read operation returning text, total length, and continuation status. However, it does not mention prerequisites like permissions, error handling, or whether the operation is idempotent. The behavior is implied 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 concise and well-structured. It leads with the purpose, followed by argument details, and ends with the return value description. Every sentence provides essential information without 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, the description explains return values (body text, total length, continuation flag). It covers the main use case adequately. Minor gaps: no mention of handling invalid paths or error scenarios, but the description is sufficient for a simple read tool with good context signals.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description adds significant meaning beyond the input schema, which has 0% coverage. It explains that 'path' comes from search/list documents, 'offset' is for continuation reading, and 'max_chars' controls response size. This fully compensates for the schema's lack of descriptions.

    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 the action (read) and resource (document body as Markdown). It effectively differentiates from sibling tools list_documents and search_documents by specifying what this tool does (read content) as opposed to listing or searching.

    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 explains how to use arguments (path from search/list, offset for continuation, max_chars) but does not explicitly state when to use this tool versus alternatives or provide exclusion conditions. The guidance is implicit through the context of sibling tools.

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

  • Behavior4/5

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

    No annotations, so description carries burden. It discloses search semantics (AND, case-insensitive), return format (relative path, match count, snippets), and ordering. Lacks explicit statement of read-only nature, but search inherently non-destructive.

    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?

    Very concise: one sentence for purpose, bullet-like Args/Returns with no redundant text. Every sentence adds value.

    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?

    For a search tool with output schema, description covers search behavior, return ordering, and directs to read_document for full text. Fully sufficient.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema has 0% description coverage, but description explains 'query' as space-separated AND search and case-insensitive, and 'max_results' as upper limit with default 10. Adds significant meaning beyond schema.

    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 it performs full-text search on documents under DOCS_ROOT. It distinguishes from siblings: 'If need full text, use read_document' and implicitly lists vs search.

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

    Usage Guidelines5/5

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

    Explicitly says to use read_document for full text, describes AND search with space-separated keywords, and gives return order. Provides clear context for when to 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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