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Johnhyeon

StockLens

by Johnhyeon
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Python
Remote

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    Deploy Server
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    TDQS

    B3.4/5.0

    Scored across 56 tools

    Disambiguation2/5

    Many tools are clearly separated by market and data type, but the set includes an exact duplicate pair (search/search_stock) and near-identical financial names (get_us_financials vs get_us_financial_statement). Batch variants also blur boundaries across multi/batch/bulk naming, so despite detailed descriptions, an agent has several realistic misselection risks.

    Naming Consistency3/5

    The surface is mostly snake_case and get_us_ consistently marks US tools, but batch operations use three different markers: multi, batch, and bulk. Standalone names like watchlist and stocklens_status, plus the search/search_stock alias, add further inconsistency while remaining readable.

    Tool Count2/5

    At 56 tools, the surface is well into the too-many range for an MCP server. The dual KR/US scope justifies some breadth, but many tools are batch/export/watchlist variants that inflate the count and increase discovery and selection overhead.

    Completeness4/5

    Coverage is impressively broad: quotes, charts, indicators, rankings, financials, flows, themes, reports, disclosures, ETFs, and Excel export workflows exist for the Korean market, with substantial US counterparts. The main gaps are asymmetries like Korean news having no get_us_news equivalent, but core analysis workflows have no dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources