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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

AboutRyanLisse/engram

Local-first, Convex-synced, agent-native.

README.md

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.