SARIPATI

A local-first, provider-agnostic knowledge vault for any AI host.

sari pati (Malay) — the essence, the concentrated extract.

Most AI tools start every conversation cold. SARIPATI is the memory layer that sits underneath whatever AI you already use — Claude Code, Cursor, Windsurf, Cline, Continue — and lets knowledge compound across sessions. The AI researches with its own tools; you call SARIPATI to distill and store the essence. Weeks later, it recalls it semantically.

It is not a chat app. It runs no LLM and needs no API keys. Your entire knowledge base is a single SQLite file on your own machine.

Why

• Compounding, not disposable. Research done in a session persists and accumulates by topic — the corpus grows every time the agent runs, not only when you take notes.

• Semantic recall, local. Bundled embeddings (all-MiniLM-L6-v2) power hybrid semantic + keyword search entirely on-device.

• A steerer, not just a store. The agent gets signal, not just recall: proactive nudges at session start (open questions, live intentions, unread memos, stale projects), per-kind priority, and conflict detection — every save is checked against the corpus so contradictions surface instead of piling up as equal "truth."

• Knows who it serves. An optional identity + AI-companion persona loads at session start, so any host can adopt the right voice and address you correctly.

• Visible. A launch-on-demand dashboard makes the growing knowledge base browsable, searchable, and (opt-in) editable.

• Zero lock-in. Local SQLite, MIT-licensed, no cloud account, no vendor.

Related MCP server: Memory MCP

Non-goals

• Not a chat app or LLM wrapper — it does not run or require an LLM.

• No cloud dependency required.

• Not tied to any single AI host or provider.

Install

npx saripati setup                 # create the vault, print the config, detect your host
npx saripati setup ./setup.md      # also load your identity from a template file
npx saripati setup ./setup.md --write   # also register SARIPATI with detected hosts

Grab setup.md from this repo, fill in the four identity fields at the top, and point setup at it. Then your host connects by package name — no folder path:

{
  "mcpServers": {
    "saripati": { "command": "npx", "args": ["-y", "saripati", "mcp"] }
  }
}

Restart your AI host. The first vault call downloads the ~90 MB embedding model once (with a progress heartbeat), then works offline forever.

The tools (9)

A typical flow: on at session start → the AI researches with its own tools → vault save → (conflict? entry_update) → next week vault recall → off at the end.

The Steerer model

Entries carry a kind and a lifecycle, so recall returns signal, not noise.

• Kinds: research · note · decision · pattern · question · memo · intention. Questions track resolved; intentions track active; memos are the agent's notes to its future self and surface first at on.

• Status: active · superseded · archived. Superseded/archived entries drop out of default recall (pass include_superseded to see them) — old decisions stop being cited as current truth.

• Priority: a per-kind boost (memo > question > decision/intention > pattern > research/ note), tunable per vault via identity_set({ companion_config: { recall_boost: … } }).

• Conflict detection: after every save, vault runs a narrow similarity check and returns near-duplicate or contradicting entries so the agent can entry_update them.

Identity — who the vault serves

setup reads a small YAML frontmatter from setup.md:

---
name:      Your Name
field:     Software Engineering
skills:    [supabase, next.js, laravel]
language:  English
companion: librarian     # plain | librarian | research-assistant
---

It is stored in a singleton identity row. From then on on and whoami hand your host that context at session start, so it adopts the right voice and addresses you correctly. Set a focus with identity_set({ user_prefs: { focus: "project-name" } }) and on biases recent entries toward it.

The dashboard

npx saripati ui                  # http://localhost:4319 — read-only by default
npx saripati ui --write          # enable in-browser tag/kind edits
npx saripati ui --no-semantic    # FTS only — faster cold start, no model load
npx saripati ui --port 8080      # custom port

A local browser UI built on Preact 10 + HTM (no CDN, no bundler — vendored ESM served at /vendor/*.js). Five tabs — Steer opens by default:

Editing is off by default — pass --write to enable mutations (kind, tags, status, resolved, active).

How it works

AI host (its own web tools)  ──stdio/MCP──▶  saripati mcp
                                                 │
                    embed (MiniLM 384d) ─────────┤
                    hybrid search (vec ∪ FTS5) ──┤
                    per-kind boost + status ─────┤
                                                 ▼
                                    ~/.saripati/vault.db  (SQLite)
                                    ▲
                    saripati ui ────┘  (read-only dashboard)

• Storage: SQLite via better-sqlite3, versioned with a PRAGMA user_version migration runner — existing vaults upgrade in place on open.

• Vectors: sqlite-vec (vec0) — embeddings are L2-normalized so KNN ranks like cosine.

• Keyword: SQLite FTS5. Fusion: Reciprocal Rank Fusion combines the two rankings.

• Embeddings: @xenova/transformers running all-MiniLM-L6-v2 in-process.

• Terminal voice: a small zero-dep presentation layer (src/term/theme.ts) that degrades to plain ASCII off-TTY and never touches the JSON-RPC channel (banners go to stderr).

Data lives in ~/.saripati/ by default (override with SARIPATI_HOME or SARIPATI_DB).

Develop

npm install
npm run build      # tsc → dist/ (+ vendored UI bundles)
npm test           # end-to-end smoke test
npm run dev -- mcp # run from source via tsx

License

MIT © Kyou