Memory & Contextdsh-plugin
interest-memory
interest-memory is a lightweight, local-first long-term memory backend for AI agents. It runs as a single ~18MB binary with SQLite, extracts and verifies interest points at session end, and recalls relevant context at session start. Supports multiple agents, MCP, and graph-based memory traversal.
Stars
2
Forks
0
Open issues
0
Last push
Aug 16, 2026
Latest release
v0.1.0
24h Growth
+0
7d Growth
+0
Installation
dsh plugin --profile web add @djasdh/interest-memory-dsh-bridgeOverview
interest-memory is a lightweight, local-first long-term memory backend for AI agents. It runs as a single ~18MB binary with SQLite, extracts and verifies interest points at session end, and recalls relevant context at session start. Supports multiple agents, MCP, and graph-based memory traversal.
- Single ~18MB binary + SQLite file; idle ~17MB RAM, <75MB peak; runs on Raspberry Pi.
- Session-end extraction of interest points with 3-stage verification (check/claims/contradictions).
- Session-start recall injection with concise entries; full content on demand to minimize context pollution.
- Multi-agent shared service with isolated, fully-shared, or custom namespaces.
- Interest-point convergence: semantically similar points auto-merged or related; memory converges with use.
- Graph walk: every result carries outlinks/backlinks; traverse from point to neighborhood to network.
- Evidence-backed entries: each has evidence (web URL/turn/query); subjective preferences never stored as facts.
- Full audit: all structural changes logged to change_log, replayable; stale entries archived with successor chain.