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einsteindark-edgm

MCP PDF Extract

by einsteindark-edgm
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

    The two tools have clearly distinct purposes: one lists available PDFs, the other reads their contents. There is no overlap or ambiguity.

    Naming Consistency4/5

    Both tools use snake_case and follow a verb_noun pattern (read_doc_contents, list_available_pdfs). The slight inconsistency between 'doc_contents' and 'pdfs' is minor, and overall naming is predictable.

    Tool Count3/5

    With only 2 tools, the server is minimal. For a PDF extraction server, a few more tools (e.g., extract metadata, search text) would be expected, but the scope may be intentionally narrow.

    Completeness2/5

    The server lacks common operations like extracting specific pages, retrieving metadata, or searching within PDFs. The surface is incomplete for typical PDF extraction tasks.

  • Average 3.4/5 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

  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

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  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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  "$schema": "https://glama.ai/mcp/schemas/server.json",
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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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?

    No annotations are provided, so the description carries full burden. It states the tool lists PDFs, implying a read-only operation. However, it does not disclose what 'available' means, whether the list is static or dynamic, or any side effects. The description is honest but lacks depth.

    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?

    A single sentence of 8 words with no redundancy. Every word is necessary. It is appropriately brief for a parameterless tool.

    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?

    No output schema is provided, and the description does not describe the return format (e.g., file names, paths, IDs). The tool is simple, but the agent needs to know what the output looks like to use it effectively, especially to feed into the sibling 'read_doc_contents'. This gap reduces completeness.

    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?

    The tool has zero parameters, so the schema is fully descriptive. The description adds slight value by stating the list is of 'all available PDF documents', implying no filtering. Baseline for 0 parameters is 4, and this is met.

    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 action ('List') and the resource ('all available PDF documents that can be read'). It distinguishes from the sibling tool 'read_doc_contents' by implying the listing is a precursor to reading, but does not explicitly differentiate.

    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 on when to use this tool versus alternatives. It is implied that listing is a discovery step before reading, but there are no explicit usage contexts, prerequisites, or exclusions.

    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 the description carries full burden. It discloses the tool reads PDFs and returns a string, but does not mention behavior for non-existent files, access permissions, large file handling, or any side effects. Adequate but minimal.

    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?

    One sentence, front-loaded with the action verb 'Read', zero wasted words. Every element serves a purpose.

    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?

    For a simple single-parameter tool with no output schema, the description is mostly adequate. It covers the core purpose and return type, but could benefit from mentioning error cases (file not found, unreadable) or that the string contains raw text from the PDF.

    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 description adds little beyond the schema. It correctly describes the single parameter as a 'PDF filename', matching the schema's description. No additional meaning about format, path conventions, or restrictions is provided.

    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 reads a PDF and returns its content as a string. It specifies both the file type (PDF) and the return format, distinguishing it from siblings like list_available_pdfs which lists files rather than reading them.

    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 when to use this tool (after listing PDFs), but does not explicitly state when not to use it or mention alternatives. No guidance on prerequisite steps (e.g., file must exist).

    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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