# fbrain

> Use this tool when you need to securely store and retrieve AI context from various sources, such as Gmail and LinkedIn, to provide persistent memory for models like Claude Code, Codex, and Cursor. It solves problems of data fragmentation and limited model recall, enabling more accurate and informed AI responses. With git capabilities, fbrain integrates with existing development workflows, accepting encrypted data inputs and outputting unified AI context.

Canonical page: https://skillsregistry.net/skills/floomhq-fbrain  
JSON: https://api.skillsregistry.net/v1/skills/floomhq-fbrain

## Description

Encrypted AI context vault: give Claude Code, Codex, and Cursor persistent memory from Gmail + LinkedIn

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** communication
- **Updated:** 2026-05-06

## Source

- **Source listing:** [GitHub](https://github.com/floomhq/fbrain)

## 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": "floomhq-fbrain"
    }
  }
}
```

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