# mem

> mem — bytefolk-mem. Use this tool when you need to manage and access a unified memory space across multiple interfaces, solving integration and consistency issues for AI agents. It provides a portable and self-hosted solution, accepting various inputs and outputting unified memory data. Ideal for use cases requiring seamless data exchange between API, CLI, UI, and MCP, with version control capabilities via git.

Canonical page: https://skillsregistry.net/skills/bytefolk-mem  
JSON: https://api.skillsregistry.net/v1/skills/bytefolk-mem

## Description

A portable, self-hosted memory plane for AI agents — one core across API, MCP, CLI, and UI.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/bytefolk/mem)

## 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": "bytefolk-mem"
    }
  }
}
```

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

---
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