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anki-agent

anki-agent

by maibrandon
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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

    A3.8/5.0

    Scored across 15 tools

    Disambiguation5/5

    Each tool targets a distinct resource+action, and the preview/apply pairs (preview_notes/create_notes, preview_delete_cards/delete_cards, preview_delete_deck/delete_deck) are explicitly framed as dry-run versus commit steps, so an agent can tell them apart without guesswork. Card-level versus deck-level deletion is also clearly separated by scope.

    Naming Consistency4/5

    Nearly every tool follows a snake_case verb_noun pattern (list_decks, create_deck, rename_deck, move_cards, search_notes, delete_deck), including the compound preview_* prefix. The lone outlier is connection_status, a noun-only status check, which is a minor but visible deviation.

    Tool Count5/5

    At 15 tools the surface is dense but every tool maps to a real operation (connection check, deck CRUD, note lifecycle, card moves/deletes, backup), with no redundant wrappers. Nothing feels padded or missing from the count perspective.

    Completeness4/5

    Core lifecycle is well covered: decks (list/create/rename/delete), notes (search/preview/create/update), cards (move/preview-delete/delete), plus backup. Gaps remain around tags (no tag add/remove/list), card scheduling controls (suspend/bury/reset), and direct single-note deletion, which agents must work around via card deletion.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing

    Resources