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OCR Beans

by btechbrasil
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Python
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    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

    A3.9/5.0

    Scored across 5 tools

    Disambiguation4/5

    Each tool has a fairly distinct target: ocr_image (images), check_legibility (diagnostic), batch_ocr (directory batch), ocr_pdf (full PDF), and ocr_page (specific pages). The only mild overlap is ocr_pdf vs ocr_page, but the descriptions clearly delineate the full-document vs page-subset use cases.

    Naming Consistency4/5

    Three tools share the 'ocr_' prefix (ocr_image, ocr_pdf, ocr_page) and the rest use clear verb_noun forms (check_legibility, batch_ocr). Mostly readable and predictable, though the prefix/suffix placement of 'ocr' varies slightly.

    Tool Count5/5

    Five tools is a tight, well-scoped set for an OCR/PDF extraction domain. Every tool covers a distinct entry point (single image, single PDF, page subset, batch directory, pre-flight diagnostic) with no redundancy.

    Completeness4/5

    The surface covers the core OCR lifecycle well: images, full PDFs, page subsets, batch directories, and a legibility diagnostic. Minor gaps remain (e.g. batch image processing or configurable output formats), but the main workflows are fully supported.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources