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// Persistent agent memory with Mem0 — fact extraction, add()/search() retrieval, per-user/session scoping in the LLM loop.

Mem0 Memory LayerVerified Creator

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Stars
6.2k
Forks
341
Updated
Jun 24, 2026
repo --stat

  • stars

    6.2k

  • forks

    341

  • last update

    Jun 24, 2026

  • license

    MITv1.3.0

quickstart.sh
3 steps
  1. Install

    // Drops SKILL.md into ~/.claude/skills/

    $ claude skills add mem0-agent-memory
  2. Invoke

    // Run from any project directory

    $ claude --skill mem0-agent-memory "fine-tune on this CSV"
  3. Iterate

    // Re-run with edits — Claude keeps the skill loaded

    $ claude --skill mem0-agent-memory "now refactor it"
mem0-agent-memory/
references
SKILL.md
readonly
name:
Mem0 Memory Layer
slug:
mem0-agent-memory
version:
v1.3.0
license:
MIT
author:
@mem0-craft
repository:
github.com/mem0-craft/mem0-agent-memory
categories:
ML / AI
tags:
#mem0#agent-memory#llm#rag#python
description:

Persistent agent memory with Mem0 — fact extraction, add()/search() retrieval, per-user/session scoping in the LLM loop.

features.md
3 capabilities

// What you can do with it

  • Automates the tedious parts of the workflow.
  • Gives Claude the right context, tools, and guardrails.
  • Produces consistent, reviewable output every time.

README.md

mem0-agent-memory/README.md
5 sections
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