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BukeLy

PageIndex Light MCP

by BukeLy
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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

    The two tools have clearly distinct purposes: one retrieves detailed content for a specific page, the other returns an index with optional semantic search. No overlap or ambiguity exists.

    Naming Consistency5/5

    Both tools follow the same 'get_' prefix followed by a noun, perfectly consistent and predictable.

    Tool Count3/5

    Only two tools exist, which is at the thin end of the range. While appropriate for a 'light' server, the scope is minimal and may feel incomplete for broader PDF workflows.

    Completeness4/5

    The core workflow of indexing and retrieving page details is covered. Minor gaps exist such as no explicit metadata retrieval or index update, but these can be worked around.

  • Average 3.6/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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 status not available

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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. It discloses conditional behavior: if a query is provided, the most relevant pages are returned; otherwise the entire index is returned. It also notes that top_k only applies when a query exists. However, it does not mention side effects, error handling, or whether the operation is read-only, leaving some behavioral gaps.

    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 tightly structured: a one-line purpose followed by a bulleted Args list. There is no redundancy or filler; every sentence 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?

    Since an output schema exists, return values need not be described. The description covers the main behavior and all parameters. However, it does not provide usage context relative to get_detail or mention preconditions/errors, making it adequate but not exhaustive.

    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?

    Schema description coverage is 0%, so the description compensates by listing each parameter with meaning: file_path is the full path, query is an optional search that returns relevant pages, and top_k is the result count defaulting to 5 and only active with a query. This adds value beyond the raw schema, though it lacks constraints like positive integer requirements.

    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 opens with '获取 PDF 文件索引，支持语义搜索' (Get PDF file index, supports semantic search), which clearly identifies the action (get/retrieve) and resource (PDF file index). It is specific and unambiguous, but does not explicitly differentiate from the sibling tool get_detail.

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

    Usage Guidelines2/5

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

    No guidance is given about when to use this tool versus get_detail, nor are there any exclusions or alternative recommendations. The description only explains what the tool does, not when it should be selected.

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

  • Behavior2/5

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

    With no annotations provided, the description carries full responsibility for behavioral disclosure. It fails to explain what 'detailed content' includes (text, images, layout), error behavior, or side effects. The existence of an output schema is not referenced, and no such context is added.

    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 a clear purpose statement and two well-defined arguments. There is no unnecessary information, and the structure is front-loaded and easy to scan.

    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?

    The tool is simple with two parameters, so the description is minimally viable. However, the lack of usage context (when to choose this over get_index) and behavioral detail leaves gaps. Since an output schema exists, return values are presumably covered, but the description alone is not fully self-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?

    The description adds meaningful explanations for both parameters: file_path is the full path to the PDF, and page is 1-based. This fully compensates for the schema's 0% description coverage, giving the agent the necessary context to populate the parameters correctly.

    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 '获取 PDF 某一页的详细内容' (get detailed content of a specific PDF page), identifying the action and resource with specificity. This distinguishes it from the sibling tool get_index, which likely provides an index overview rather than page-level details.

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

    Usage Guidelines2/5

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

    No guidance is given for when to use this tool versus alternatives. The description only lists arguments and does not mention prerequisites, edge cases, or scenarios where another tool (e.g., get_index) would be more appropriate.

    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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