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by s-morgan-jeffries · MCP Server · ★ 104
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🔒 Is apple-mail-fast-mcp safe to install? View the security audit →
Apple Mail MCP Server An MCP server that provides programmatic access to Apple Mail, enabling AI assistants like Claude to read, send, search, and manage emails on macOS. ⚠️ Pre-1.0 — expect breaking changes. The MCP tool surface (tool names, parameters, return shapes) is still evolving as the project matures. Pin to a specific version (for example, ) and review the CHANGELOG before upgrading. Tools (24) Grouped by lifecycle (10 read-only, 14 mutating): Discovery — , , , : enumerate what's configured (no external cache — call per account). Read — , , , , , : read messages/threads, pull an attachment's content inline, and render templates. Message actions — (read/flag/move in one pass), (→ Trash), (to disk, byte-capped). Drafts — (new / reply / forward, optionally
| Stars | 104 |
| Forks | 34 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 80.7365186742641/100 |
| Open Issues | 35 |
| Last Updated | 2026-09-09 |
| Created | 2025-10-09 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~17k |
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apple-mail-fast-mcp is 🤖 MCP server for Apple Mail - Manage emails with AI using Claude Desktop. Search, send, organize mail with natural language.. It is categorized as a MCP Server with 104 GitHub stars.
apple-mail-fast-mcp is primarily written in Python. It covers topics such as apple-mail, applescript, claude.
You can find installation instructions and usage details in the apple-mail-fast-mcp GitHub repository at github.com/s-morgan-jeffries/apple-mail-fast-mcp. The project has 104 stars and 34 forks, indicating an active community.
apple-mail-fast-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to apple-mail-fast-mcp on Agent Skills Hub include apple-mail-mcp, apple-mail-mcp, mac_messages_mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: