Memory Cache

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name: memory-cache description: High-performance temporary storage system using Redis. Supports namespaced keys (mema:*), TTL management, and session context caching. Use for: (1) Saving agent state, (2) Caching API results, (3) Sharing data between sub-agents. metadata: {"openclaw":{"requires":{"bins":["python3"],"env":["REDIS_URL"]},"install":[{"id":"pip-dependencies","kind":"exec","command":"pip install -r requirements.txt"}]}}

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Memory Cache

Standardized Redis-backed caching system for OpenClaw agents.

Prerequisites

Binary: python3 must be available on the host.

Credentials: REDIS_URL environment variable (e.g., redis://localhost:6379/0).

Setup

1. Copy env.example.txt to .env. 2. Configure your connection in .env. 3. Dependencies are listed in requirements.txt.

Core Workflows

1. Store and Retrieve

Store: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py set mema:cache: [--ttl 3600]

Fetch: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py get mema:cache:

2. Search & Maintenance

Scan: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py scan [pattern]

Ping: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py ping

Key Naming Convention

Strictly enforce the mema: prefix:

mema:context:* – Session state.

mema:cache:* – Volatile data.

mema:state:* – Persistent state.