pip install engram-mem

flowchart TD
    subgraph Agents["Agents & IDEs"]
        CC["Claude Code"]
        OC["OpenClaw"]
        CU["Cursor"]
        ANY["Any MCP Client"]
    end

    subgraph Interfaces
        CLI["CLI (Typer)"]
        MCP["MCP (stdio)"]
        HTTP["HTTP API /api/v1/"]
        WS["WebSocket /ws"]
    end

    CC & OC & CU & ANY --> MCP
    CLI & MCP & HTTP & WS --> Auth["Auth Middleware\n(JWT + RBAC, optional)"]
    Auth --> Tenant["TenantContext (ContextVar)"]
    Tenant --> Recall["Recall Pipeline\n(decision > resolve > search > feedback)"]
    Recall --> Episodic["EpisodicStore\n(Qdrant)"]
    Recall --> Semantic["SemanticGraph\n(NetworkX + SQLite/PG)"]
    Recall --> Fed["Federated Providers"]
    Episodic & Semantic --> Reasoning["Reasoning Engine\n(Gemini via litellm)"]
    Episodic --> Cache["Redis Cache (optional)"]
    WS --> EventBus["Event Bus\n(push events)"]

    subgraph Fed["Federated Knowledge"]
        M0["mem0"]
        LR["LightRAG"]
        GR["Graphiti"]
        REST["REST / File / PG / MCP"]
    end

# Install from PyPI
pip install engram-mem

# Or from source
git clone https://github.com/docaohieu2808/Engram-Mem.git
cd engram && pip install -e .

# Initialize config
engram init

# Set API key
export GEMINI_API_KEY="your-key"

# Start daemon (background HTTP server + watcher)
engram start

# Store a memory
engram remember "Deployed v2.1 to production at 14:00 - caused 503 spike"

# Search memories
engram recall "production incidents"

# Browse all data (episodic + semantic)
engram dump

# Reason across all memory
engram think "What deployment issues have we had?"

{
  "mcpServers": {
    "engram": {
      "command": "engram-mcp",
      "env": { "GEMINI_API_KEY": "your-key" }
    }
  }
}

{
  "mcpServers": {
    "engram": {
      "command": "engram-mcp",
      "env": { "GEMINI_API_KEY": "your-key" }
    }
  }
}

capture:
  openclaw:
    enabled: true
    sessions_dir: ~/.openclaw/workspace/sessions

# Auto-discovery (enabled by default)
discovery:
  local: true
  hosts: ["10.10.0.2"]  # additional hosts to scan

# Or manual provider config
providers:
  - name: my-mem0
    type: rest
    url: http://localhost:8080
    search_endpoint: /v1/memories/search
    search_method: POST
    search_body: '{"query": "{query}", "limit": {limit}}'
    result_path: "results[].memory"

# Start server
engram serve --port 8765

# Store memory
curl -X POST http://localhost:8765/api/v1/remember \
  -H "Content-Type: application/json" \
  -d '{"content": "Deployed v1.0", "memory_type": "fact", "priority": 8}'

# Search
curl "http://localhost:8765/api/v1/recall?query=deployment&limit=5"

# Reason
curl -X POST http://localhost:8765/api/v1/think \
  -H "Content-Type: application/json" \
  -d '{"question": "What deployment issues have we had?"}'

# Meeting ledger
curl -X POST http://localhost:8765/api/v1/meeting-ledger \
  -H "Content-Type: application/json" \
  -d '{"title": "Sprint Review", "decisions": ["Ship v2"], "action_items": ["Update docs"]}'

engram remember <content> [--type fact|decision|...] [--priority 1-10]
                          [--tags tag1,tag2] [--expires 7d] [--topic-key key]
engram recall <query> [--limit 5] [--type <type>] [--tags tag1,tag2]
engram ask <question>               # Smart query (auto-routes)
engram think <question>             # LLM reasoning
engram summarize [--count 20] [--save]
engram decay [--limit 20]           # Ebbinghaus retention curve

engram add node <name> --type <type>
engram add edge <from> <to> --relation <relation>
engram remove node <key>
engram remove edge <key>
engram query [keyword] [--type X] [--related-to Y] [--format table|json]
engram autolink-orphans [--apply] [--min-co-mentions 3]

engram status                       # Memory counts
engram dump [--format table|json]   # All memories + graph
engram health                       # Full system health check
engram tui                          # Terminal UI (interactive browser)
engram graph [--port 8100]          # Open visualization browser

engram cleanup                      # Delete expired memories
engram consolidate [--limit 50]     # LLM clustering + summarization
engram ingest <file.json> [--dry-run]  # Extract entities + remember
engram backup                       # Export snapshot
engram restore <file>               # Import snapshot
engram migrate <file>               # Import legacy JSON

engram session-start
engram session-end
engram feedback <id> --positive|--negative
engram resolve <query>              # Pronoun + temporal resolution
engram audit [--limit 50]           # Retrieval audit log

engram init                         # Zero-config setup
engram start                        # Start daemon (HTTP server + watcher)
engram stop                         # Stop daemon
engram logs [--tail 50]             # Show logs
engram serve [--host 0.0.0.0] [--port 8765]  # Foreground HTTP server
engram watch [--daemon]             # Watch inbox + OpenClaw/Claude Code sessions

engram setup                        # Interactive IDE connector wizard
engram config show|get <key>|set <key> <value>
engram auth                         # API key management
engram providers discover           # Auto-discover external providers
engram providers list|add|remove    # Manage providers
engram schema                       # Manage semantic schemas

engram queue-status                 # Embedding queue health
engram resource-status              # LLM tier (FULL/STANDARD/BASIC/READONLY)
engram constitution-status          # 3-law governance + SHA-256
engram scheduler-status             # Background task schedule
engram benchmark [--quick]          # Run recall accuracy benchmark

engram autostart                    # Install systemd user services
engram sync [--direction]           # Git-friendly memory sharing

episodic:
  mode: embedded              # embedded (Qdrant in-process) or server
  path: ~/.engram/qdrant
  namespace: default

embedding:
  provider: gemini
  model: gemini-embedding-001
  key_strategy: failover      # failover or round-robin

semantic:
  provider: sqlite            # or postgresql
  path: ~/.engram/semantic.db

llm:
  provider: gemini
  model: gemini/gemini-2.0-flash
  api_key: ${GEMINI_API_KEY}

serve:
  host: 127.0.0.1
  port: 8765

capture:
  openclaw:
    enabled: false
    sessions_dir: ~/.openclaw/workspace/sessions
  claude_code:
    enabled: false
    sessions_dir: ~/.claude/projects

auth:
  enabled: false
cache:
  enabled: false
  redis_url: redis://localhost:6379/0
rate_limit:
  enabled: false
audit:
  enabled: false
  path: ~/.engram/audit.jsonl

# Quick start
docker build -t engram:latest .
docker run -e GEMINI_API_KEY="your-key" -p 8765:8765 engram:latest

# Production with PostgreSQL + Redis
ENGRAM_AUTH_ENABLED=true \
ENGRAM_SEMANTIC_PROVIDER=postgresql \
ENGRAM_SEMANTIC_DSN=postgresql://user:pass@postgres:5432/engram \
ENGRAM_CACHE_ENABLED=true \
ENGRAM_CACHE_REDIS_URL=redis://redis:6379/0 \
docker compose up

pytest tests/ -v                      # All tests
pytest tests/ --cov=src/engram        # With coverage
pytest tests/ -k "recall or feedback" # Specific suites