Claude-Mem OpenClaw Plugin — Setup Guide

Name: Claude-Mem OpenClaw Plugin — Setup Guide
Availability: InStock
Author: enigmaicon-eng

Configure the Claude-Mem OpenClaw plugin to record and stream agent observations.

1|Updated May 16, 2026

Search Tags:#persistent memory #plugin configuration #openclaw #claude-mem #SSE streaming #agent tooling #system prompt injection

Ready to run

npx skills add https://github.com/enigmaicon-eng/AI-Enterprise-OS --skill claude-mem-openclaw-plugin-setup-guide

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Claude-Mem OpenClaw Plugin — Setup Guide
Source: https://github.com/enigmaicon-eng/AI-Enterprise-OS/tree/main/examples/claude-mem/openclaw
Command: npx skills add https://github.com/enigmaicon-eng/AI-Enterprise-OS --skill claude-mem-openclaw-plugin-setup-guide

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the hassle of manually wiring an enterprise agent runtime to persistent memory by setting up the claude-mem plugin on an OpenClaw gateway so your agents can retain an observation timeline across sessions.

Core Features & Use Cases

Persistent observation memory via worker: Runs a claude-mem worker on port 37777 to store observations and provide context timelines.
System prompt context injection: Injects the observation timeline into each agent’s system prompt using the before_prompt_build hook (optional and configurable).
Real-time observation feed streaming: Streams new observations over the worker’s SSE endpoint into messaging channels (Telegram/Discord/Slack/etc.).
Useful commands for operations: Adds /claude_mem_status to check worker health and /claude_mem_feed to inspect feed connection state.

Quick Start

Run the one-liner installer and follow the interactive prompts to connect the claude-mem worker to your OpenClaw gateway.

Frequently Asked Questions about Claude-Mem OpenClaw Plugin — Setup Guide

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I give my AI agents persistent memory across sessions?▼

Persistent memory across sessions is achieved by running a claude-mem worker on port 37777 to store agent observations and inject the timeline into system prompts for context retention. This setup ensures agents recall past interactions without manual data management.

How does system prompt context injection work for agent observation timelines?▼

System prompt context injection works by using the before_prompt_build hook to automatically insert stored agent observations into the prompt context. This mechanism provides governance-aware longitudinal memory so agents access prior session data seamlessly.

Can I stream agent observations in real-time to Discord or Slack?▼

Yes, you can stream agent observations to Discord, Slack, or Telegram by connecting the worker's SSE endpoint to your messaging channels. This setup provides real-time visibility into what agents learn during their operations.

What's the best way to set up the Claude-Mem plugin on an OpenClaw gateway?▼

The best way to set up the Claude-Mem plugin is to run the one-liner installer and follow the interactive prompts. This process configures the worker connection, enables the plugin entry, and sets project and feed parameters on your OpenClaw gateway.

Do I need an OpenClaw deployment to use persistent memory and SSE streaming?▼

Yes, an OpenClaw deployment is required because the plugin is designed specifically for the OpenClaw gateway environment. It relies on OpenClaw hooks to inject observation timelines and stream new data via SSE to configured messaging channels.

How do I verify if my persistent memory worker and SSE feed are running correctly?▼

Verify the persistent memory worker and SSE feed by running the /claude_mem_status command to check worker health and the /claude_mem_feed command to inspect the feed connection state. These operations confirm the system is actively recording and streaming observations.