# Mynd

> Mynd — jaffarkeikei-mynd. Use this tool when you need to enhance AI capabilities with personalized memory and context. Mynd captures digital context and streams it securely to any AI via Model Context Protocol (MCP), enabling AIs to recall user decisions, preferences, and history. Ideal for use cases requiring AI to learn from user interactions and adapt to individual patterns, all while keeping data local and secure.

Canonical page: https://skillsregistry.net/skills/jaffarkeikei-mynd  
JSON: https://api.skillsregistry.net/v1/skills/jaffarkeikei-mynd

## Description

Mynd is a universal memory layer for AI that automatically captures your digital context and streams it securely to any AI via Model Context Protocol (MCP). Your AIs finally remember everything about you - your decisions, preferences, history, and patterns - while your data never leaves your device.

## Trust

- **Trust score (0–1):** 0.84
- **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/jaffarkeikei/Mynd)

## 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": "jaffarkeikei-mynd"
    }
  }
}
```

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