Memori for OpenClaw: Persistent Memory for Multi-Agent Gateways | Memori

OpenClaw makes it easy to run agents through a shared gateway. The harder problem is memory. By default, agents still lose context between sessions, and the built-in memory model starts to break down as usage gets more complex.

Today, we're launching the Memori OpenClaw plugin so every agent on your gateway can automatically recall relevant context before responding and capture durable memory after each turn.

Why OpenClaw needs a stronger memory layer

OpenClaw's built-in memory is useful to get started, but it has real limitations in production:

Limitation	What happens
Flat markdown files	Memory lives as plain text instead of structured facts and relationships
Context compaction	Important details disappear as sessions grow and context gets compressed
No relationship reasoning	The agent cannot connect related facts across sessions
Cross-project noise	Memories from one workflow show up in another
No user isolation	Multi-tenant setups can mix memory across users

Memori replaces that with a knowledge graph, process-level isolation, entity-level isolation, and intelligent recall with smart decay.

Two hooks, automatic memory

The plugin integrates directly with OpenClaw's event lifecycle through two hooks:

before_prompt_build — intercepts the prompt, queries Memori, and prepends relevant memories
agent_end — extracts the completed user/assistant exchange and sends it to Memori for fact extraction

The plugin also sanitizes OpenClaw metadata, timestamps, and thinking blocks before data reaches the memory layer.

Setup takes a few minutes

OpenClaw v2026.3.2 or later is required.

Install and enable the plugin:

openclaw plugins install @memorilabs/openclaw-memori
openclaw plugins enable openclaw-memori
openclaw gateway restart

Then configure your Memori API key and entity ID:

openclaw config set plugins.entries.openclaw-memori.config.apiKey "your-memori-api-key"
openclaw config set plugins.entries.openclaw-memori.config.entityId "user_123"

From that point, every agent on the gateway auto-recalls before responding and auto-captures after. No per-agent wiring required.

What Memori adds to OpenClaw

Structured memory storage: Instead of raw markdown blobs, Memori stores conversations, facts, preferences, and knowledge-graph triples as structured records tied to an entity, process, and session. Facts are extracted as subject-predicate-object relationships, deduplicated over time, and connected into a graph so related memories stay queryable instead of being buried in text files.
Advanced Augmentation: After each conversation, Memori processes the user and assistant exchange asynchronously in the background, identifies facts, preferences, skills, and attributes, generates embeddings for semantic search, and updates the knowledge graph without blocking the agent's response path.
Intelligent Recall: Before the agent responds, Memori searches the current entity's stored facts and knowledge graph, ranks memories by semantic relevance and importance, and injects the most useful context into the prompt so durable knowledge survives context-window compression.
Production-ready observability: Memori Cloud gives you dashboard visibility into memory creation, recalls, cache hit rate, sessions, quota usage, top subjects, per-memory retrieval metrics, and knowledge-graph relationships, so you can inspect what was stored and how recall is behaving in production.

That means agents running through OpenClaw can share the same long-term memory system as your other Memori-powered applications.

Get started

The Memori OpenClaw plugin is available now.