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learning-tool-mcp

by Hemosoo
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Python
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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

    A4.2/5.0

    Scored across 12 tools

    Disambiguation5/5

    Each tool targets a distinct resource or lifecycle stage: ingestion vs retrieval, saving flashcards vs quizzes, review scheduling vs progress reporting. The few pairs that could overlap (get_study_items/get_material, get_due_items/get_session_state) are explicitly differentiated in their descriptions.

    Naming Consistency5/5

    All tools use a consistent imperative verb + noun snake_case pattern (save_, get_, ingest_, list_, submit_, export_, delete_, reset_). The style is uniform, making the action and target predictable across the entire set.

    Tool Count5/5

    12 tools is well within the ideal range and each serves a distinct function in the study workflow: ingest, generate/save, retrieve, review, track, export, and manage documents. No tool feels redundant or ornamental.

    Completeness4/5

    The core learning loop is covered end-to-end: ingest material, save generated items, retrieve due items, log responses, and monitor progress. Minor gaps exist—there is no way to edit or delete individual flashcards/quiz questions without deleting the whole document—but these are workable and don't block the main workflow.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources