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pablontiv

PDF Reader MCP Server

by pablontiv

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: metadata extraction, page extraction, text extraction, and validation. The descriptions reinforce these differences, with no overlap that would cause agent confusion or misselection.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with 'extract' or 'validate' as the verb and 'pdf' plus a specific noun (metadata, pages, text, or implied file for validate). The naming is uniform and predictable throughout the set.

    Tool Count5/5

    With 4 tools, the server is well-scoped for a PDF reader domain, covering key operations without bloat. Each tool earns its place by addressing a distinct aspect of PDF processing, making the count appropriate and focused.

    Completeness4/5

    The tool set covers essential PDF operations like metadata, content extraction, and validation, but lacks tools for actions like merging, splitting, or converting PDFs. These gaps are minor and agents can likely work around them for basic reading tasks.

  • Average 3/5 across 4 of 4 tools scored.

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

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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 extraction but doesn't describe what metadata is returned (e.g., author, creation date, page count), whether the operation is read-only or has side effects, error handling, or performance characteristics. This leaves significant gaps for a tool with no annotation coverage.

    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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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

    Completeness2/5

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

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what metadata is extracted, the return format, or potential limitations (e.g., encrypted PDFs). For a tool with no structured behavioral or output information, more detail is needed to guide effective use.

    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 the single parameter 'file_path' clearly documented. The description adds no additional parameter details beyond what the schema provides, such as file format requirements or path validation rules. With high schema coverage, the baseline score of 3 is appropriate.

    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 with a specific verb ('extract') and resource ('metadata and document information from PDF files'). It distinguishes from siblings like 'extract_pdf_text' (which extracts text content) and 'extract_pdf_pages' (which extracts pages), but doesn't explicitly mention these distinctions in the description itself.

    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?

    The description provides no guidance on when to use this tool versus alternatives like 'extract_pdf_text' or 'validate_pdf'. It states what the tool does but offers no context about use cases, prerequisites, or exclusions.

    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 the full burden of behavioral disclosure. It mentions extraction but doesn't cover critical aspects like whether this modifies the original file, requires specific permissions, handles errors, or has rate limits. For a tool with three parameters and no annotations, this is a significant gap in transparency.

    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, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for the tool's complexity and gets straight to the point.

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

    Completeness2/5

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

    Given the tool has no annotations, no output schema, and three parameters, the description is incomplete. It doesn't explain what 'extract content' means in practice (e.g., returns text, images, or something else), lacks error handling or behavioral context, and doesn't guide usage relative to siblings. For a tool with this complexity, more context is needed.

    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 schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't explain 'structured' format details or provide examples beyond the schema's 'page_range' examples). Baseline 3 is appropriate when the schema does the heavy lifting.

    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 with a specific verb ('extract content') and resource ('PDF documents'), and specifies the scope ('specific pages or page ranges'). However, it doesn't explicitly differentiate from sibling tools like 'extract_pdf_text' or 'extract_pdf_metadata', which prevents a perfect score.

    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?

    The description provides no guidance on when to use this tool versus alternatives like 'extract_pdf_text' (which might extract all pages) or 'validate_pdf'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the purpose alone.

    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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions optional metadata and formatting preservation, but lacks details on permissions needed, file size limits, rate limits, error handling, or output format. For a tool that processes files and has no annotation coverage, this leaves significant 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 a single, efficient sentence that front-loads the core purpose ('Extract text content from PDF documents') and adds key optional features. Every word earns its place with no redundancy or unnecessary elaboration.

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

    Completeness2/5

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

    Given no annotations, no output schema, and a tool that performs file processing with multiple parameters, the description is incomplete. It doesn't address behavioral aspects like error conditions, performance expectations, or output structure, leaving the agent with insufficient context for reliable use.

    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 description coverage is 100%, so the schema fully documents all four parameters. The description adds minimal value beyond the schema by hinting at optional metadata and formatting preservation, but doesn't provide additional context like examples of preserved formatting or metadata types. Baseline 3 is appropriate when the schema does the heavy lifting.

    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: 'Extract text content from PDF documents' with additional features like optional metadata and formatting preservation. It specifies the verb ('extract') and resource ('text content from PDF documents'), but doesn't explicitly differentiate from sibling tools like 'extract_pdf_metadata' or 'extract_pdf_pages' beyond the core focus on text extraction.

    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?

    The description provides no guidance on when to use this tool versus its siblings (extract_pdf_metadata, extract_pdf_pages, validate_pdf). It mentions optional features like metadata and formatting preservation, but doesn't clarify scenarios where this tool is preferred over alternatives or any prerequisites for use.

    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 the full burden of behavioral disclosure. It states the tool validates 'integrity and readability,' which implies a read-only, non-destructive operation, but doesn't specify what validation entails (e.g., checks for corruption, encryption, or formatting issues), potential error conditions, or output format. This leaves significant gaps in understanding the tool's behavior.

    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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action ('validate') and resource ('PDF file'), making it easy to parse quickly. Every part of the sentence earns its place by conveying essential 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?

    Given the tool's moderate complexity (validation operation with one parameter) and lack of annotations or output schema, the description is minimally adequate but incomplete. It covers the basic purpose but misses details on behavioral traits, usage context, and expected results, which are important for an agent to invoke it correctly without structured guidance.

    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 the single parameter 'file_path' clearly documented. The description doesn't add any parameter-specific details beyond what the schema provides, such as file format requirements or path examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

    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 with a specific verb ('validate') and resource ('PDF file integrity and readability'), making it immediately understandable. However, it doesn't explicitly distinguish this validation tool from its sibling tools (extract_pdf_metadata, extract_pdf_pages, extract_pdf_text), which all perform extraction rather than validation.

    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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., file existence), context for validation (e.g., before extraction operations), or comparisons with sibling tools, leaving the agent to infer usage scenarios.

    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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