npx rekindle init

Rekindle is an MCP continuity engine that solves session orientation, not just storage. Orient at session start, capture at session end. All local, all SQLite, zero API keys.

v0.2.0 — orientation domain layer, end_session tool, typed continuity records. Release notes

Quick Start

npx rekindle init

This creates .rekindle/ in your project with a SQLite database, identity template, and transcript directory. Then add the MCP server config for your client:

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

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

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

Then fill in .rekindle/identity.md and paste the boot instructions into your project's CLAUDE.md.

Session 1 stores. Session 2 remembers. Session 10 anticipates.

The Problem (43 Sessions of Data)

Over 43 sessions, we measured what an AI assistant failed to load at session start:

Existing memory tools (Mem0, Letta, Zep) optimize for retrieval accuracy: can the AI find what it stored? That's necessary but not sufficient. None of them address whether the AI loaded the right context for this session, or whether it can detect what it missed.

Rekindle solves session orientation: loading identity, recent context, memory health, and missing-context warnings before the assistant starts work.

See docs/gap-analysis.md for the full research dataset.

What It Does

Boot: orient at session start

boot_report runs an orientation pipeline before any work begins:

boot_report
  +-- Read identity document (who am I working with?)
  +-- Scan memory stats (what do I know?)
  +-- Find latest checkpoint (where did we leave off?)
  +-- Read last transcript (what actually happened?)
  +-- Detect gaps (what am I missing?)
  +-- Calculate orientation score (how oriented am I?)
  --> "Carrying forward: [context loaded, gaps identified, score: 80/100]"

Healthy output:

## Orientation Score
100/100

+20  Identity document loaded
+20  Recent checkpoint exists
+20  Session transcript found
+20  Recent memories exist (last 7 days)
+10  Relationship/preference memories populated
+10  Project-scoped memories found

Sparse output (flags what's missing):

## Gaps Detected
- [critical] identity_missing: No identity document found
- [warning] checkpoint_missing: No recent checkpoint

## Orientation Score
20/100

 ✗  Identity document loaded (20pts)
 ✗  Recent checkpoint exists (20pts)
 ✗  Session transcript found (20pts)
+20  Recent memories exist (last 7 days)
 ✗  Relationship/preference memories populated (10pts)
 ✗  Project-scoped memories found (10pts)

Capture: close the loop at session end

end_session stores structured continuity records — not just a summary:

All records stored with type, source, and session_id metadata. Next boot_report loads the checkpoint automatically.

Between sessions: search and manage

Categories: preference lesson context relationship general

Why not just CLAUDE.md?

A static file is passive. Your AI reads it, but it can't search it, rank it, track what's been retrieved, or tell you what's missing. Rekindle adds:

• Search — full-text with importance-weighted ranking
• Structure — category and project scoping across memories
• Orientation — proactive context loading at boot, not just on-demand retrieval
• Gap detection — flags missing identity, empty categories, stale data
• Scoring — transparent checklist so you know how oriented the AI is
• Session capture — structured close with checkpoints, decisions, and open loops

v0.2.0 Highlights

• 7 MCP tools — added end_session for structured session close
• Orientation domain layer — boot_report is now a thin wrapper; all logic in OrientationService, GapDetector, Scorer
• Typed continuity records — memories carry type, source, session_id instead of content prefixes
• Orientation scoring — 100-point additive checklist across 6 criteria
• Structured gaps — { code, severity, message } with 8 gap codes
• 64 automated tests — unit, integration, and performance

Install from Source

git clone https://github.com/Skitchy/rekindle.git
cd rekindle
npm install
npm run build
node dist/init/cli.js init

{
  "hooks": {
    "Stop": [{
      "type": "command",
      "command": "python3 /path/to/rekindle/hooks/extract-session.py"
    }]
  }
}

Compatibility

rekindle/
  src/
    index.ts          MCP server entry point
    server.ts         Server setup, tool registration
    storage/
      sqlite.ts       SQLite + FTS5, schema migration, sessions
    orientation/
      types.ts        OrientationResult, Gap, ScoreItem
      GapDetector.ts  Structural gap detection (8 codes)
      Scorer.ts       Orientation scoring (6 criteria, 100pts)
      OrientationService.ts   Orchestrator
      OrientationRenderer.ts  Markdown + JSON output
    tools/
      boot-report.ts  Thin wrapper over OrientationService
      end-session.ts  Structured session close
      store.ts search.ts list.ts delete.ts update.ts
    init/
      cli.ts scaffold.ts templates/
  hooks/
    extract-session.py
    pre-compact-capture.py

Tests

npm test

64 tests: storage CRUD + FTS5 ranking, orientation domain (gap detection, scoring, service, rendering), MCP integration (all 7 tools), and performance (1000-memory search under 100ms).

Roadmap

v0.3: "It thinks in networks" — Spreading activation, semantic search via embeddings, open loops in boot reports, gap analysis tooling, eval harness.

License

MIT