MemU

A closer look at MemU

memU gives every agent a user uses one shared, inspectable memory layer with source-linked recall: agent-driven memory, cross-agent memory, automatic skill extraction, memory retrieval and storage in readable Markdown, plus a skill file agents can fetch with an API key.

Editorial guidance based on published documentation. The workflow below is a suggested starting point, not a measured product result.

When to choose MemU

• Agent users whose agents forget context between sessions and who want one shared memory across agents and devices.
• Builders who want inspectable memory with source links, so a recalled fact can be traced back to its source.
• Teams working with several agents who want automatic skill extraction and readable Markdown storage rather than a black-box store.

When to choose something else

• Users who do not want to paste a skill file or use an API key, since the stated setup fetches a SKILL.md file with an API key as a Bearer token.
• Users looking for a single consumer chatbot, since memU is a memory layer for agents, not a chat product.

A practical starting workflow

1. Fetch the memU SKILL.md file into your agent, using an API key as instructed on the homepage.
2. Let agents store memories, skills and context in the shared layer as they work.
3. Retrieve a memory with its source link when an agent needs earlier context.

Check before committing

• The homepage states paste-into-agents use is 100% free, but no $0 plan amount or plan table appears in the text read, so no free allowance fact is recorded.
• The guessed pricing path returns a 404 page, so pricing here is limited to the homepage statements.

Common questions

Compare approaches for this task

• Mem0 — Developers building agents or apps that must remember user preferences and past facts across sessions instead of starting each conversation blank.; Teams that want memory as infrastructure, with add and search calls from an SDK rather than building their own store and retrieval layer.; Builders testing memory features first, since the pricing page describes a Free plan for developers building and testing with Mem0.
• MemoryLake — People and teams whose memory must work across many AIs and agents instead of being locked inside one chat product.; Claude Code and Codex users who want to install memory once and keep the same memory in the terminal.; Teams that want to meter memory use by token and pay on demand beyond a plan, rather than buying seats.