# Rememb

> Rememb — luizedupp-rememb. Use this tool when you need to provide persistent memory for AI agents, enabling them to retain information across interactions. It solves the problem of knowledge loss and improves agent performance by storing data locally with zero configuration. Ideal for use with AI platforms like Cursor, Windsurf, and Claude via MCP, with seamless integration using git.

Canonical page: https://skillsregistry.net/skills/luizedupp-rememb  
JSON: https://api.skillsregistry.net/v1/skills/luizedupp-rememb

## Description

Persistent memory for AI agents — local, portable, zero config. Works with Cursor, Windsurf, Claude via MCP.

## Trust

- **Trust score (0–1):** 0.44
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/LuizEduPP/Rememb)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "luizedupp-rememb"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/luizedupp-rememb` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/luizedupp-rememb/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt