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ig-extract-mcp

by nurhikam
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    TDQS

    A3.7/5.0

    Scored across 4 tools

    Disambiguation3/5

    ig_extract and ig_to_screener are fairly distinct, but screener_parse and screener_from_image overlap because both appear to handle image/carousel OCR input. Descriptions help clarify the intended input type, but an agent could still hesitate when given an image.

    Naming Consistency3/5

    All names are lowercase snake_case, which is readable, but the naming patterns are mixed: noun_verb (ig_extract, screener_parse) vs. prepositional phrases (screener_from_image, ig_to_screener). There is no consistent verb-first or verb_noun convention across the set.

    Tool Count5/5

    Four tools is well-scoped for a focused pipeline: raw IG extraction, text parsing, OCR parsing, and a combined one-shot workflow. Each tool earns its place without bloat or an overly thin surface.

    Completeness5/5

    The set covers the full intended workflow from an Instagram URL or raw text/image input to structured screener filters. Post, reel, carousel, OCR, and manual text paths are all addressed, with ig_to_screener covering the end-to-end case.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources