Mengram — OpenClaw Memory Plugin

Human-like long-term memory for your OpenClaw agent. Three memory types that work together, with automatic recall and capture on every turn.

What It Does

Without Mengram	With Mengram
"Which restaurant?"	"Booking Kaganat at 7pm for 2. Vegan menu for Anya?"
New session = blank slate	Knows your preferences, history, workflows
Same as day 1 after 100 chats	Deep understanding of who you are

Memory types:

• Semantic — facts: preferences, relationships, habits
• Episodic — events with timestamps and outcomes
• Procedural — learned workflows that self-improve from failures
• Graph RAG — 2-hop knowledge graph traversal connects related memories

Auto-recall: Before every agent turn, relevant memories are injected into context. No manual tool calls needed.

Auto-capture: After every turn, new information is automatically extracted and stored. Nothing is lost.

Install

openclaw plugins install openclaw-mengram

Setup

1. Get a free API key at mengram.io

2. Add to ~/.openclaw/openclaw.json:

{
  "plugins": {
    "entries": {
      "openclaw-mengram": {
        "enabled": true,
        "config": {
          "apiKey": "${MENGRAM_API_KEY}"
        }
      }
    },
    "slots": {
      "memory": "openclaw-mengram"
    }
  }
}

3. Set your API key:

export MENGRAM_API_KEY="om-your-key-here"

4. Restart OpenClaw. Memory works automatically.

Configuration

Option	Default	Description
apiKey	$MENGRAM_API_KEY	API key from mengram.io
baseUrl	https://mengram.io	Custom URL for self-hosted
autoRecall	true	Inject memories before each turn
autoCapture	true	Store memories after each turn
topK	5	Max results per search
graphDepth	2	Knowledge graph hops (0=off, 1, 2)
injectProfile	false	Include cognitive profile periodically
profileFrequency	25	Profile injection every N turns
maxFactsPerEntity	5	Max facts shown per entity in context
maxRelationsPerEntity	5	Max relationships shown per entity
maxEpisodes	5	Max episodic memories in context
maxProcedures	3	Max procedures in context
maxStepsPerProcedure	8	Max steps shown per procedure
captureMessageCount	10	Messages to capture after each turn
maxTriggers	10	Max triggers shown
maxTimelineItems	20	Max timeline items shown
requestTimeout	15000	HTTP timeout in milliseconds
debug	false	Verbose logging

Tools

The agent can use these 12 tools explicitly:

Tool	Purpose
memory_search	Search all 3 memory types with Graph RAG
memory_store	Save text to long-term memory
memory_forget	Delete a memory entity by name
memory_profile	Get cognitive profile (who the user is)
memory_procedures	List or search learned workflows
memory_feedback	Record workflow success/failure (triggers evolution)
memory_episodes	Search or list past events with date filtering
memory_timeline	Get chronological timeline of memory events
memory_triggers	Get smart triggers (reminders, contradictions, patterns)
memory_insights	Get AI-generated reflections and patterns
memory_agents	Run maintenance agents (curator, connector, digest)
memory_graph	Get the knowledge graph (entities + connections)

Slash Commands

Command	Action
/remember <text>	Save to memory
/recall <query>	Search memory
/forget <entity>	Delete from memory

CLI

openclaw mengram search "coffee preferences"   # Search all 3 memory types
openclaw mengram stats                          # Memory usage statistics
openclaw mengram profile                        # Cognitive profile
openclaw mengram procedures                     # List learned workflows
openclaw mengram episodes                       # List past events
openclaw mengram timeline                       # Chronological event timeline
openclaw mengram triggers                       # Smart triggers
openclaw mengram insights                       # AI-generated reflections
openclaw mengram agents                         # Run maintenance agents
openclaw mengram graph                          # Knowledge graph
openclaw mengram feed                           # Activity feed
openclaw mengram reindex                        # Reindex embeddings
openclaw mengram dedup                          # Deduplicate memories
openclaw mengram merge <source> <target>        # Merge two entities

Experience-Driven Procedures

Workflows learn from experience:

Day 1: Agent figures out deploy steps manually
Day 2: Agent finds the saved workflow, follows it (v1)
Day 3: Deploy fails — agent reports failure with context
Day 4: Procedure auto-evolved to v2 with fixed steps

Record outcomes with memory_feedback. On failure with context, the procedure automatically evolves.

vs mem0

Feature	mem0	Mengram
Memory types	1 (flat facts)	3 (semantic + episodic + procedural)
Knowledge graph	Optional	Built-in Graph RAG (2-hop)
Self-improving workflows	No	Yes (auto-evolution)
Cognitive profile	No	Yes
Price	$99/mo+	Free (open-source)

Links

• mengram.io — Get API key
• GitHub — Source code
• API Docs — Full API reference

License

Apache-2.0