srs-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@srs-mcpshow me my due cards"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
srs-mcp
Agent-agnostic MCP server for spaced-repetition learning — no 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.
Related MCP server: MCPMem
Tools
add_card(front, back, deck="default") -> {card_id, due}— author + schedule a carddue_cards(deck=None, limit=20) -> [{card_id, front, back, deck, due}]— what's due nowgrade_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 datedelete_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
back → grade_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-mcpStorage
Two backends, chosen at startup:
Postgres (shared deck) — set
SRS_DATABASE_URL(orDATABASE_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 thecards.card_idcolumn isBIGINTon Postgres. Requires thepsycopgdependency (already declared).SQLite (fallback) — when no
*DATABASE_URLis set, cards live in a SQLite file atSRS_DB(default./srs.db). Single-host / offline. In a SQLite-on-Railway setup, mount a volume at/dataand keepSRS_DB=/data/srs.dbso the box survives redeploys.
The schema is identical (table cards) and auto-created on first use.
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