srs-mcp

srs-mcp

Enables agents to perform spaced-repetition learning with FSRS scheduling, including adding cards, reviewing due cards, and grading recall, using a headless SQLite or Postgres backend.

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README

srs-mcp

Agent-agnostic MCP server for spaced-repetition learningno Anki GUI, no Xvfb, no AnkiConnect. Bring your own agent; this brings the card box + the scheduler.

It wraps FSRS (the Free Spaced Repetition Scheduler, the same algorithm modern Anki uses) around a tiny SQLite store, so an agent can author cards, see what's due, and record recall — entirely headless.

Why not headless Anki?

Driving the Anki desktop app headless means Qt + a virtual framebuffer (Xvfb) + the AnkiConnect add-on — brittle and version-coupled. The anki PyPI package can drive a real .anki2 collection GUI-less if you need interop with your phone's Anki. But if you just want spaced repetition behind an API, you don't need Anki at all: FSRS is a library, and this server is ~200 lines around it.

Tools

  • add_card(front, back, deck="default") -> {card_id, due} — author + schedule a card
  • due_cards(deck=None, limit=20) -> [{card_id, front, back, deck, due}] — what's due now
  • grade_card(card_id, rating) -> {card_id, rating, next_due, reps} — record recall (again/hard/good/easy, or 1-4)
  • list_cards(deck=None, limit=50) — overview regardless of due date
  • delete_card(card_id) — remove one (reset / cleanup)
  • stats(deck=None) -> {total, due_now, reviews, decks}

The review loop: due_cards → quiz the user with front → check against backgrade_card. FSRS computes the next due date from the rating.

Run

uv sync
# HTTP (default; for Railway / remote agents)
PORT=8000 uv run srs-mcp
# or stdio (local agent)
MCP_TRANSPORT=stdio uv run srs-mcp

Storage

Two backends, chosen at startup:

  • Postgres (shared deck) — set SRS_DATABASE_URL (or DATABASE_URL) to a Postgres connection string (e.g. a Neon DB). Every deployment that points at the same URL reads/writes one shared deck, so you can add and review cards from anywhere (local, Railway, etc.). FSRS card ids are large, so the cards.card_id column is BIGINT on Postgres. Requires the psycopg dependency (already declared).
  • SQLite (fallback) — when no *DATABASE_URL is set, cards live in a SQLite file at SRS_DB (default ./srs.db). Single-host / offline. In a SQLite-on-Railway setup, mount a volume at /data and keep SRS_DB=/data/srs.db so the box survives redeploys.

The schema is identical (table cards) and auto-created on first use.

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