srs-mcp
You can use this server to give an MCP-compatible agent real, correctly scheduled spaced-repetition memory (SM-2) backed by a local SQLite file.
Add review items under topics (flashcards, vocab, interview questions, LeetCode problems, etc.); new items are due immediately.
Get due or overdue items, optionally filtered by topic and limited in count; answers are withheld until you grade them.
Grade an item on a 0–5 recall quality scale; the server computes the next review date via SM-2 and shows the correct answer.
View summary stats: total items, due-today count, and average ease factor, optionally per topic.
With a Pro license, export/backup items as JSON or CSV, and get a forecast of how many items will be due over the next N days to spot upcoming review pile-ups.
Click on "Deploy 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-mcp Show me my items due for review today."
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 — spaced repetition, as an MCP server
Give any MCP-capable agent (Claude Code, Claude Desktop, or any other MCP host) real, correctly-scheduled spaced-repetition memory instead of re-deriving "what's due today" from a markdown table by hand every session. Implements SM-2 (the algorithm behind Anki/SuperMemo) as four callable tools, backed by a local SQLite file. No account, no network calls, no telemetry — everything runs on your machine.
Status: prototype, not yet published anywhere. Built and verified locally (see "How it's been verified" below); not yet installed by anyone outside this project. Treat version 0.2.0 as pre-release.
Why this exists
Markdown checklists and vocab tables are common ways people (and the agents helping them) track what to review, but nothing computes an actual schedule from them — "due today" ends up being a guess, re-read by eye every time. srs-mcp is the missing piece: a small, real scheduling algorithm exposed as tools, so an agent can track review state for anything — flashcards, interview questions, vocab, onboarding quizzes — without re-implementing SM-2 in a prompt.
Related MCP server: FlashLearn
The four core tools (free, unlimited, forever)
Tool | What it does |
| Add a review item under a topic. New items are due immediately. |
| List items due today or overdue. Answer withheld until graded, like a real flashcard review. |
| Grade recall 0–5 (5 = perfect, <3 = fail/reset). Returns the next due date via SM-2 and the correct answer. |
| Totals, due-today count, average ease factor. |
Get Pro
Two additional tools are gated behind a Pro license — this is the free/paid split srs-mcp uses instead of subscriptions or a hosted backend:
Tool | What it does |
| Bulk export/backup all your review data. |
| Review-load forecast — how many items come due each of the next N days, so a pile-up is visible before it happens. |
How licensing works, concretely: srs-mcp signs license keys with an
Ed25519 private key that never leaves the maintainer's machine; this
repo ships only the matching public key (license.py), which can
verify a signature but can't forge one. Buy a key, set it as
SRS_LICENSE_KEY (env var) or save it to ~/.srs-mcp/license.key, and
the Pro tools unlock — no account, no phone-home check, works offline.
See license.py for the full mechanism and its stated limitations
(short version: this deters casual copying, it isn't DRM — nothing
stops someone from patching out the check in their own local copy of
an open-source Python file; see the module docstring for the honest
version of this tradeoff).
No live purchase link exists yet. This section describes the
mechanism, which is built and tested (see test_license_gate.py), not
a working store. When a purchase flow exists, it goes here.
Install
Requires Python 3.11+.
git clone <repo-url> # not yet public — see status note above
cd srs-mcp
python3 -m venv .venv
.venv/bin/pip install -e .
.venv/bin/srs-mcp # runs the server on stdioTo use it as a Claude Code plugin, point Claude Code at this directory
(or, once published, at its marketplace listing) — .claude-plugin/plugin.json
and .mcp.json are already set up; the server reads SRS_DB_PATH so a
plugin install's data survives updates (${CLAUDE_PLUGIN_DATA}/srs.db
under Claude Code, or a co-located srs.db for a direct/manual run).
How it's been verified
Not just "it imports" — actually run, over the real MCP protocol:
test_client.pyspawnsserver.pyas a subprocess (the same way a real MCP host does), drives a full add/list/grade/list session, and independently re-checks the resulting SQLite rows outside the test harness.test_license_gate.pyspawns the server three ways (no license, valid license, tampered license) and confirmsexport_items/get_forecastrefuse in cases 1 and 3 and return real data in case 2 — proving the license check is a real gate, not a no-op.examples/bulk_import.pyis a working, idempotent example script that loads a generic CSV or JSON file of items into srs-mcp via realadd_itemMCP calls (not direct SQLite writes) — a starting point for bulk-loading your own tracker (vocab, interview prep, onboarding checklists, anything else) instead of adding items one at a time.
Honest gap to "ready to launch" — not rounded up
No public repo. Every real distribution path (Claude Code's community plugin marketplace, a GitHub release, an MCP directory listing) needs this reachable at a public git URL. This project is local-only. Creating that (a GitHub repo, possibly an account) is outside this project's current autonomy without an explicit go-ahead — everything above is prepared to make that a copy-and-push action, not a build task, once given.
Can't self-validate against
claude plugin validate. NoclaudeCLI or Node/npx available in this dev environment. The plugin manifest is schema-conformant as far as careful reading of Anthropic's docs and cross-referencing their own productionmarketplace.jsoncan confirm, not machine-validated.No live purchase flow. The license mechanism is real and tested; turning it into an actual sale needs a storefront (Ko-fi, Gumroad, or similar) that doesn't exist yet — that's an account-creation step, outside this project's autonomy without a go-ahead.
License enforcement is honesty-based, not tamper-proof, by design and by the nature of shipping readable Python — see the "Get Pro" section above and
license.py's docstring.No auth/multi-tenant story. Single local SQLite file, single user. Fine for the current "runs on your machine" model; would need real design work to become a hosted/team product.
Zero external validation. Nobody outside this project has installed or used this. Every claim above is "this works as built and tested," not "people want this."
License
MIT — see LICENSE. (The Pro-tier license key mechanism is separate
from the code's own MIT license — see "Get Pro" above.)
Available Tools
6 toolsadd_itemA
Add a new spaced-repetition item (e.g. a LeetCode problem, a Chinese vocab word, an interview question) under a topic. New items are due immediately.
Inputs: topic (required), answer (required), question (required).
export_itemsA
[Pro] Export items (id, topic, question, answer, interval_days, repetitions, ease_factor, due_date, created_at) as json or csv text, optionally filtered to one topic. Requires a valid Pro license (see README's "Get Pro" section) -- this is the free/Pro split's first concrete gate: the 4 core tools stay free and unlimited forever, bulk export/backup is part of the paid tier. Without a valid license, returns an upgrade message instead of data, not an error the caller has to guess the meaning of.
Inputs: topic, format.
get_due_itemsA
List items due for review today (or overdue), optionally filtered to one topic. Returns id, topic, question (answer withheld until grade_item is called, same as a real flashcard review).
Inputs: limit, topic.
get_forecastA
[Pro] Review-load forecast: how many items become due on each of the next N days, optionally filtered to one topic. Lets a user see an upcoming pile-up before it happens instead of discovering it the day of -- a real planning feature, not a gate for its own sake. Requires a valid Pro license, same as export_items.
Inputs: days, topic.
get_statsA
Summary stats: total items, how many due today, average ease factor, optionally scoped to one topic.
Inputs: topic.
grade_itemA
Grade recall quality for an item just reviewed (0-5: 0 = total blackout, 3 = correct with effort, 5 = perfect instant recall) and return the newly computed next-due date, plus the correct answer for confirmation. Uses SM-2 scheduling.
Inputs: item_id (required), quality (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 6 tools
Each tool serves a clearly distinct purpose: adding items, fetching due items, grading recall, viewing stats, exporting data, and forecasting workload. There is no overlap or ambiguity in their intended actions.
Every tool follows a consistent verb_noun pattern (add_item, get_due_items, grade_item, get_stats, export_items, get_forecast), making it easy to infer the action and target. No mixed conventions or vague verbs.
With 6 tools, the server is well-scoped for a spaced-repetition system, covering the core workflows (add, review, stats, export, forecast) without unnecessary bloat or excessive granularity.
The tool surface covers the primary lifecycle (add, review, stats, export, forecast) well, but lacks direct update and delete operations for items. Export tools can serve as a workaround, so the gap is minor.
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