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engram
RyanLisse
Unified multi-agent memory for OpenClaw.
Open RyanLisse/engram → Does not match the four rules.
Works with any agent
ships AGENTS.md, the cross-tool instruction file.
In its own words
Local-first, Convex-synced, agent-native.
Unified multi-agent memory for OpenClaw.
An elephant never forgets. Neither should your agents.
Engram is a shared memory layer that any OpenClaw agent can plug into. Cloud-synced through Convex with native vector search and full agent-native architecture.
What It Does
- Store atomic facts, entities, and conversations across agents
- Recall semantically — vector search finds what matters, not just what matches
- Share memory between agents with scoped access control
- Decay gracefully — old memories fade but never disappear
- Sync across devices — Mac Mini, MacBook Air, MacBook Pro all see the same brain
- Enrich automatically — embeddings, importance scoring, lifecycle management
- Recall three ways — semantic vector search + symbolic text + graph expansion, fused via Reciprocal Rank Fusion
Quick Start
OpenClaw (one-liner)
This does everything: deploys Convex → builds plugin → patches OpenClaw config → bootstraps existing memory files → verifies recall. Restart OpenClaw after.
Auto-Memory Discovery
Engram auto-ingests existing memory files from your workspace. The installer bootstraps all .md files from ~/.openclaw/workspace/memory/ on first run, then an hourly cron syncs new/modified files.
State tracked in memory/.engram-sync-state.json — only changed files re-ingested.
Add Engram to your agent (easy guide)
Use Engram from Claude Code, OpenClaw, or OpenCode in a few steps.
The repository's own description, then 28% of its README. Read the rest on GitHub ↗
Read from the repository's git tree on 2026-08-17.