Co-Engram

Team memory with neuroscience-inspired plasticity. English | 中文

Co-Engram is a self-evolving memory system for AI agents and teams. Unlike traditional vector stores that only retrieve, Co-Engram models memory after the brain: engrams strengthen with use, weaken when they fail, consolidate during sleep, and verify themselves through metacognition.

Works with Claude Code (via MCP) and OpenClaw (via plugin SDK), with a host-agnostic TypeScript core you can embed anywhere.

Why Co-Engram

| Differentiator | What it means | | ------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Three-file separation | Every memory is split into content.md / meta.yaml / synapses.yaml so content diffs stay clean in Git while metadata evolves independently. | | Self-maintaining | A maintenance engine runs light (RPE-based reinforcement), deep (consolidation), and rem (metacognition upgrade/refute) stages automatically — no manual tagging required. | | Host-agnostic core | @co-engram/core has zero host dependencies. Same memory, same tools, whether you use Claude Code, OpenClaw, or your own agent. |

Quickstart

Three commands to get Co-Engram working inside Claude Code:

# 1. Install the MCP server globally
npm install -g @co-engram/claude-code

# 2. Initialize the data repo (a separate Git repo, not inside this project)
mkdir -p ~/team-memory && cd ~/team-memory && git init

# 3. Wire into Claude Code
claude mcp add co-engram \
  -e CO_ENGRAM_DATA_ROOT=$HOME/team-memory \
  -e CO_ENGRAM_MAINTENANCE=1 \
  --scope user \
  -- co-engram-mcp

Restart Claude Code, run /mcp in a new session, and you should see 25 co-engram tools loaded.

Zero-install alternative (skip step 1): replace co-engram-mcp in step 3 with npx -y @co-engram/claude-code.

For OpenClaw integration, see docs/host-openclaw.md.

Architecture

flowchart TB
  subgraph Host["Host layer"]
    CC["Claude Code"]
    OC["OpenClaw"]
  end

  subgraph Adapter["Adapter layer"]
    A1["@co-engram/claude-code<br/>(MCP server, stdio)"]
    A2["@co-engram/openclaw<br/>(plugin SDK)"]
  end

  subgraph Core["@co-engram/core<br/>(host-agnostic)"]
    Tools["25 tools<br/>engrams · synapses · skills"]
    Engine["Maintenance engine<br/>light · deep · rem"]
    Retrieval["FTS + graph retrieval"]
  end

  subgraph Data["Data layer (separate Git repo)"]
    Engrams["engrams/{content,meta,synapses}"]
    Skills["skills/"]
  end

  subgraph Cache["Cache layer (gitignored)"]
    Derived[".co-engram/<br/>FTS index · vectors"]
  end

  CC --> A1
  OC --> A2
  A1 --> Tools
  A2 --> Tools
  Tools --> Engine
  Tools --> Retrieval
  Retrieval --> Derived
  Engine --> Data
  Tools --> Data

Packages

| Package | What it does | Install | | ------------------------------------------------------ | ----------------------------------------------------------- | ------------------------------------ | | @co-engram/core | Host-agnostic memory engine + 25 tools + maintenance engine | npm install @co-engram/core | | @co-engram/claude-code | MCP server adapter for Claude Code | npm install @co-engram/claude-code | | @co-engram/openclaw | Plugin SDK adapter for OpenClaw | npm install @co-engram/openclaw | | @co-engram/e2e | Cross-host end-to-end tests (private, not published) | workspace only |

Tool Catalog

Co-Engram exposes 25 native tools grouped into five concerns, plus 2 OpenClaw-compatible memory_* wrappers (registered only under @co-engram/openclaw).

Engrams (11) — the core memory units engram_create · engram_get · engram_update · engram_delete · engram_search · engram_list · engram_reinforce · engram_report_failure · engram_archive · engram_restore · engram_forget

Synapses (4) — typed connections between engrams synapse_create · synapse_get · synapse_list · synapse_delete

Skills (2) — procedural memory skill_get · skill_invoke

Learning loop (4) — verification, contradiction, evolution close_learning_loop · contradiction_resolve · upgrade_verification · get_evolution_lineage

Memory proposals (3) — implicit capture from conversations engram_list_proposals · engram_accept_proposal · engram_dismiss_proposal

OpenClaw memory protocol (2) — host-compatible wrappers, registered only under @co-engram/openclaw memory_search · memory_get

The memory_* tools declare kind: "memory" in openclaw.plugin.json so OpenClaw treats Co-Engram as the primary memory plugin (mutually exclusive with memory-core). They are thin adapters over engram_search / engram_get that hide Co-Engram internal terminology and inject a self-evolving prompt section via registerMemoryCapability.promptBuilder.

For full signatures, inputs, and examples, see docs/tool-reference.md.

Configuration

Environment variables (Claude Code MCP server)

All optional. Set them in claude mcp add -e KEY=value or your shell.

| Variable | Default | Purpose | | ----------------------------------------- | -------------------- | ----------------------------------------------------------------------------------------------------------------------------------- | | CO_ENGRAM_DATA_ROOT | $HOME/team-memory | Absolute path to the data Git repo | | CO_ENGRAM_DEFAULT_CREATED_BY | unknown | Default author for new engrams | | CO_ENGRAM_LANGUAGE | en | Language for tool descriptions / viewer UI / prompts (en | zh). Falls back to ~/team-memory/.co-engram/config.json if unset. | | CO_ENGRAM_MAINTENANCE | 0 | Set to 1 to start the maintenance engine | | CO_ENGRAM_MAINTENANCE_ENABLED_STAGES | light,deep,rem | Comma-separated stage list | | CO_ENGRAM_MAINTENANCE_LIGHT_INTERVAL_MS | 300000 (5 min) | Light stage interval | | CO_ENGRAM_MAINTENANCE_DEEP_INTERVAL_MS | 3600000 (1 hour) | Deep stage interval | | CO_ENGRAM_MAINTENANCE_REM_INTERVAL_MS | 604800000 (7 days) | REM stage interval | | CO_ENGRAM_MAINTENANCE_LEARNING_RATE | 0.1 | RPE learning rate |

OpenClaw manifest config

For OpenClaw, configuration goes in the plugin manifest. See docs/host-openclaw.md for the full schema.

Comparisons

| Feature | Co-Engram | mem0 | Letta | LangChain Memory | | -------------------- | ------------------------- | ------------------ | ---------------- | ------------------ | | Storage model | 3-file Git-friendly | Vector + graph | Vector + state | Vector / key-value | | Plasticity (LTP/LTD) | Yes (RPE-driven) | Manual API | Manual API | Manual API | | Auto maintenance | Yes (light/deep/rem) | No | No | No | | Metacognition | Yes (5-dim truth score) | No | No | No | | Host coupling | None (host-agnostic core) | Tight (Python SDK) | Tight (REST API) | Tight (Python SDK) | | License | MIT | Apache-2.0 | Apache-2.0 | MIT |

Roadmap

See GitHub Issues for the live roadmap. Highlights:

• TypeDoc-generated tool reference — replace hand-written docs/tool-reference.md with auto-generated API docs
• Provider-backed abstraction layer — LLM-driven REM stage for narrative abstraction
• Web UI — browse engrams, inspect synapse graph, trigger maintenance manually
• More host adapters — Continue.dev, Cursor, Aider
• 1.0 release — once API is stable and we have real production users

Contributing

Contributions are welcome. See CONTRIBUTING.md for development setup, test commands, and PR conventions. For security reports, see SECURITY.md.

License

MIT — © 2026 Yang Yang