Overview

Provides a standardized, Redis-backed caching layer for OpenClaw agents, focused on temporary and session-oriented data using a strict key namespace and optional TTLs.

Key Advantages

1.Simple, standardized Redis cache interface tailored for OpenClaw agents

2.Supports TTL-based expiration for managing temporary and session data lifecycles

3.Enforces a strict mema:* key namespace to avoid collisions and keep cache data organized

4.Includes basic maintenance tools: scan (with pattern) and ping health check

5.Uses JSON serialization, making it suitable for structured session and context objects (per description)

Use Cases

Caching API responses or other expensive computations for short periods to reduce latency and cost
Storing per-session context (mema:context:*) for conversational or workflow state between steps
Managing volatile, recomputable data (mema:cache:*) that benefits from quick retrieval and controlled TTLs
Tracking durable but still Redis-backed process state (mema:state:*) for agents that need fast access to workflow checkpoints
Health-checking and inspecting agent cache contents via scan and ping commands during development or debugging

Evaluation History (1)

7.2/103/19/2026darwin-arm64

▼

OS: darwin-arm64LLM: z-ai/glm-4.5-air

**Judgement:** A solid, minimal Redis-backed caching layer for OpenClaw agents that standardizes key naming and basic cache operations. Well-suited if you already have Redis available and want a consistent way for agents to manage temporary/session data. **What it does well:** - Wraps Redis with a clear mema:* naming convention (`mema:context:*`, `mema:cache:*`, `mema:state:*`). - Provides CLI-style workflows (`set`, `get`, `scan`, `ping`) using Python, with optional TTL control. - Aligns with typical agent needs: session context caching and short-lived data storage. **Key risks / limitations:** - Hard dependency on Redis (`REDIS_URL`) and Python 3; not suitable where Redis is unavailable or restricted. - No visible built-in access control, encryption, or data masking—storing secrets or PII in cache may introduce security/privacy risks. - CLI/script-centric interface may be less ergonomic than a full library/API integration and could add process overhead for very high-throughput use cases. **Recommended scenarios:** - OpenClaw agents running in environments where Redis is already provisioned and trusted (local dev, containerized infra, or simple cloud VMs). - Use as a session/context store and short-term cache for API results or intermediate computation outputs. - Projects that need a consistent, namespaced Redis usage pattern across multiple agents or skills, but do not require advanced cache features (sharding, eviction policies beyond TTL, metrics, or sophisticated security).

Memory Cache

Overview

Key Advantages

Use Cases

Evaluation Scores

Download Trend

Evaluation History (1)

Comments (0)

Post a Comment