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gabrielmrojas

PDF Processor Server

by gabrielmrojas
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Python
Hybrid

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.2/5.0

    Scored across 15 tools

    Disambiguation3/5

    Most tools have clear, distinct purposes (extract_text vs extract_text_by_page vs extract_metadata), but get_pdf_info and extract_metadata overlap conceptually, and upload_file accepts base64 dicts, making upload_file_base64 redundant. The three upload tools introduce ambiguity about which to use.

    Naming Consistency4/5

    The majority of tools follow a verb_noun snake_case pattern (e.g., extract_text, merge_pdfs, upload_file). However, server_info lacks a verb, and pdf_to_images/images_to_pdf are noun_to_noun, creating minor inconsistencies in an otherwise predictable naming scheme.

    Tool Count4/5

    15 tools is at the upper boundary of the ideal 3-15 range, but the coverage of PDF processing operations (extract, merge, split, rotate, convert, upload) justifies the count. A few upload variants could be consolidated, but the overall scale is reasonable for a specialized server.

    Completeness4/5

    The tool set covers core PDF lifecycle operations well: creation from images, text extraction, metadata, merging, splitting, rotation, and conversion to images. The main gap is the absence of any delete/remove operation for temporary resources, which can leave dead ends in workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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