K2 Study Decks & Algorithm
Study decks for 8 languages plus the K2 spaced-repetition engine, runnable on your items.
| Endpoint | https://k2kanji.com/api/mcp (streamable-http) |
|---|---|
| Registry version | 1.1.0 |
| Now | 7 tools · grade A (98) · pin ts_9b5f26c94a9a78a414c6f04cc5bf10a4 · protocol 2025-06-18 |
| First / last listed | 2026-10-26 01:51 UTC / 2026-10-26 01:51 UTC |
| Grade over time | 2026-10-26: A (98), 7 tools |
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Tools: list_decks search_deck get_entry get_cube_algorithms explain_k2_algorithm simulate_k2_session get_site_info
list_decks | The catalog of K2 study decks: eight curated datasets spanning Japanese kanji and vocabulary, HSK Chinese, Korean Hangul, Spanish, French, classical Latin and medical Latin. Returns each deck id (the value other tools take), what it teaches, how many entries it has, and what its fields mean. Call this before search_deck. params: none |
search_deck | Search one deck. `query` substring-matches the term, its reading/pronunciation, its English meanings, and its category, so "bone" finds entries glossed as bone and "ㄱ" finds that jamo. Narrow with `category` (exact, from list_decks) or `difficulty` (1-5; for the kanji deck this is the school grade). Paginated via `offset`. params: deck*, query, category, difficulty, limit, offset |
get_entry | One deck entry in full, matched on the exact term (the kanji, hanzi, jamo, or word itself). Case-insensitive. Returns every field the deck carries, including the deck-specific extras: stroke counts and JLPT level for kanji, component kanji for compounds, declension and English derivatives for Latin, IPA and pronunciation audio for French. params: deck*, term* |
get_cube_algorithms | Rubik's cube last-layer algorithm sets used by the K2 cube trainer: full OLL (57 cases), full PLL (21), the two-look beginner subsets, and full ZBLL. Each case returns its primary algorithm plus alternates, with sources and finger-trick notes where recorded. Every algorithm in these sets is verified against a cube simulator by the repo's audit script (app/cube/scripts/audit-algorithms.mjs), run be params: set*, case_id, group, limit |
explain_k2_algorithm | The K2 spaced-repetition engine, described. K2 stores no review dates: each item holds a probability p that halves on a correct answer and doubles on a wrong one, and items are drawn by Monte Carlo rejection sampling, so the pool self-organizes around current weaknesses and expands when it cools. Returns the update rule (including the deliberate hinted-answer exception), the selection and pool-exp params: none |
simulate_k2_session | Run the real K2 engine over your own items. Give it a list of terms (any strings — your flashcards, cube cases, anything), a study mode, and a sequence of answers, and it returns the p-value trajectory per answer, which items are now mastered, when the pool expanded, and the probability distribution over what K2 would serve next. Use this to drive your own drilling with K2 as the scheduler instead params: terms*, mode, steps*, starting_level |
get_site_info | What K2 is, which apps it runs, what this server does and does not expose, and every machine-readable surface. Also returns the full capability map — every tool, prompt, and resource — so a client with a stale or tools-only roster can still see the whole surface. params: none |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.