# Apple Mail

> Use this tool when you need to automate and efficiently manage large mailboxes in Apple Mail, solving problems such as slow search times and cumbersome batch operations. It provides a comprehensive interface for parsing .emlx files, managing rules, and accessing signatures, with inputs including mailbox data and outputs including instant search results. Ideal for use cases requiring rapid email processing and organization, such as email archiving, filtering, and cleanup.

Canonical page: https://skillsregistry.net/skills/psychquant-apple-mail  
JSON: https://api.skillsregistry.net/v1/skills/psychquant-apple-mail

## Description

Provides comprehensive Apple Mail automation through 44 tools built in native Swift. Features SQLite-backed full-text search for instant queries across large mailboxes, .emlx file parsing, batch operations for up to 50 emails per call, rule management, and signature access. Outperforms AppleScript-based alternatives with millisecond search times.

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/psychquant-apple-mail)
- **Repository:** <https://github.com/psychquant/che-apple-mail-mcp>

## 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": "psychquant-apple-mail"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/psychquant-apple-mail` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/psychquant-apple-mail/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