Rememb — AI skill for Claude Code


[](https://glama.ai/mcp/servers/LuizEduPP/Rememb) [](https://lobehub.com/mcp/luizedupp-rememb)

Operate AI agents without losing context between sessions. `rememb` is a local-first persistent memory layer: structured entries, keyword search, versioning, diff, restore, and audit trail — no cloud service required.


The problem

Teams using agents at real velocity rarely fail because they lack generation. They fail because operating agents every day creates context debt:

• too much re-explaining project facts every session
• too little durable memory outside the chat window
• too little audit trail for why something changed
• too much noise when recalling the right context

Every team or solo developer operating agents professionally hits this wall:

Session 1: "We're using PostgreSQL, auth at src/auth/, prefer async patterns."
Session 2: Agent starts from zero. You explain everything again.
Session 3: Same thing.

Existing solutions often center on hosted memory layers, API keys, or opaque context pipelines. What you actually need is to **resume the next session with the minimum correct context and a trail you can inspect**.

`rememb` is built around four memory problems:

• durable facts and decisions instead of session-only chat memory
• keyword search instead of rereading everything (agents judge relevance)
• non-destructive versioning instead of silent overwrites
• local-first audit trail for AI work, not opaque cloud logs

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Install

pip install rememb

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Quick Start

With MCP (recommended)

Zero friction. No CLI commands. Na