memU ✖ LazyLLM: Build a Long-Term Memory Q&A Assistant

The easiest and laziest way to create multi-agent LLM applications with long-term memory.

LazyLLM provides a modular framework to quickly build multi-agent LLM applications with minimal effort. MemU adds robust long-term memory, enabling your AI to remember past interactions, user context, and knowledge across sessions. Together, they let you create intelligent, memory-enabled Q&A assistants effortlessly.

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What You Can Build with LazyLLM + MemU

With this integration, you can quickly create memory‑enabled agents for diverse use cases. Typical examples include:

Knowledge‑based Q&A assistants that remember past conversations and context
Personalized chatbots that recall user preferences across sessions
Multi‑agent workflows combining tools, retrieval, memory and logic — all in a unified pipeline

Try It Now

Dive into the full tutorial and see exactly how to build a memory‑enabled AI agent in minutes.

View Tutorial LazyLLM x MemU

Install memU Through Your Agent

Give your agent the canonical memU skill. It identifies the right host adapter, configures one shared memory backend, and verifies both memorization and retrieval.

Agent-Guided Setup

Codex, Claude Code, Cursor, OpenClaw, Hermes, WorkBuddy, and other agents can read SKILL.md, select their adapter, and follow the packaged install guide with verification at every step.

One Shared Memory

Connected agents use one configured local or cloud backend, so useful context and reusable skills can carry across sessions, agents, and devices without exposing a public API.

Start Building Smarter AI Today

Explore MemU and see how long-term memory can enhance your AI projects. Begin creating AI that remembers, learns, and adapts.

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