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Documentation Index

Fetch the complete documentation index at: https://docs.memwal.ai/llms.txt

Use this file to discover all available pages before exploring further.

The MemWal memory plugin adds a cloud-based, encrypted memory layer to OpenClaw agents. It works alongside OpenClaw’s existing file-based memory — automatically recalling relevant context and capturing new facts in the background, with no user action needed.

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Features

Automatic Recall

Relevant memories are injected into the LLM’s context before each conversation turn

Automatic Capture

Facts are extracted from conversations and stored as encrypted memories after each turn

Encrypted & User-Owned

SEAL-encrypted, stored on Walrus, tied to your delegate key — you own your data

Cross-App Memory

Memories stored from any MemWal-connected app are accessible to your OpenClaw agent

Multi-Agent Isolation

Each agent gets its own memory space via namespaces — no cross-contamination

Prompt Injection Protection

Detection and HTML escaping on both read and write paths

Agent Tools

Optional memory_search and memory_store tools for explicit LLM control

CLI Commands

openclaw memwal search and openclaw memwal stats for debugging and inspection

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When to use this

  • You want your OpenClaw agents to remember across conversations — preferences, decisions, context
  • You need encrypted, user-owned memory instead of plaintext files or platform-managed storage
  • You want cross-app continuity — memories from other MemWal-connected apps (chatbot, noter, researcher) surface in OpenClaw
  • You’re running multiple agents and need each to have its own isolated memory space

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Get started

Quick Start

Install, configure, and verify the plugin in minutes

How It Works

Architecture, message flow, hooks vs tools

Reference

Hooks, tools, CLI, configuration, and troubleshooting

Source Code

Browse the source on GitHub