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Open source project
Norn
Local-first persistent memory for AI assistants
A clear build, with a person accountable for every detail.
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What it is
A local-first persistent memory server for AI assistants, implementing the Model Context Protocol.
The problem
AI assistants forget everything between sessions, and most memory tools send your data to a hosted service.
What I built
- Three npm workspace packages: server, core with SQLite and sqlite-vec, and a Next.js dashboard
- Two local models via Transformers.js: all-MiniLM-L6-v2 for embeddings and nli-deberta-v3-xsmall for conflict detection
- Recall blending 70% semantic similarity with 30% recency, on a 30-day half-life
- Four MCP tools
- Norn Live, an SSE fleet dashboard, added in v1.3.0
Design and engineering decisions
- Local-first with SQLite and local models, so memory never leaves the machine. That constraint set every other choice.
- Recall weights recency alongside similarity, because an out-of-date fact that matches well is worse than a newer fact that matches slightly less.
- A conflict-detection pass using an NLI model, so contradictory memories get surfaced for review instead of silently coexisting.
- The conflict pipeline measured 95% precision and 100% recall on a 32-pair test fixture.
Verifiable proof
View @samad001z/norn-server on npm
Built with
TypeScript · Node · SQLite · sqlite-vec · Transformers.js · Next.js
Selected views
Screens


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