memU: Persistent Memory for 24/7 Agents

Persistent memory infrastructure for 24/7 agents. Replaces flat-file memory with a three-layer architecture (Resource → Memory Item → Memory Category) that r...

This Skill is a packaging/documentation wrapper around the open-source memU client (memu-py). Before installing or enabling it: 1) Confirm you are comfortable providing an OpenAI-compatible API key (OPENAI_API_KEY) because the examples and default llm_profiles use it for extraction and retrieval. 2) If you plan to persist memory, secure the PostgreSQL connection string (MEMU_DB_URL) rather than using the example credentials shown. 3) The README mentions an optional memU Cloud (api.memu.so) which would require a separate memU Cloud API key if you choose that mode. 4) Note the project is AGPL-3.0 — if you modify and redistribute components you may have obligations; review the license. 5) As with any third-party Skill, prefer installing memu-py from the official PyPI/repo and verify the upstream memU project (https://github.com/NevaMind-AI/memU) if you need to audit code changes.

Type: OpenClaw Skill Name: memu Version: 1.0.0 The memu skill bundle is a legitimate integration of the NevaMind AI memU framework, designed to provide persistent, hierarchical memory for agents. The bundle consists of comprehensive documentation (README.md, FAQ.md) and several well-structured Python examples (e.g., example_2_openclaw_integration.py, example_3_production.py) that demonstrate how to store and retrieve structured 'memory items' using either in-memory storage or a PostgreSQL database. The code follows security best practices by utilizing environment variables for sensitive credentials like OPENAI_API_KEY and lacks any signs of data exfiltration, malicious execution, or prompt injection attacks.