No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by witchan · MCP Server · ★ 643
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ios-mcp safe to install? View the security audit →
iOS MCP 中文 | English iOS MCP 是一个运行在越狱 iPhone 上的 MCP (Model Context Protocol) 服务器，让 AI 代理（Claude、Codex、Cursor 等）能够直接操控 iOS 设备。 功能概览 共 34 个 MCP 工具，覆盖 iOS 设备自动化的主要场景。 运行要求 越狱 iOS 设备 安装说明 支持环境 安装方式 方式一：从 Release 页面下载安装包 请根据越狱类型选择上表对应架构的 deb 包。 手动安装时请注意以下依赖： p
| Stars | 643 |
| Forks | 105 |
| Language | Objective-C |
| Category | MCP Server |
| License | MIT |
| Quality Score | 62.6126186941962/100 |
| Last Updated | 2026-09-11 |
| Created | 2026-04-07 |
| Platforms | mcp |
| Est. Tokens | ~16k |
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ios-mcp is iOS MCP: MCP management tool for jailbroken iPhones, enabling developers and AI agents to inspect and control devices.. It is categorized as a MCP Server with 643 GitHub stars.
ios-mcp is primarily written in Objective-C. It covers topics such as automation, developer-tool, ios.
You can find installation instructions and usage details in the ios-mcp GitHub repository at github.com/witchan/ios-mcp. The project has 643 stars and 105 forks, indicating an active community.
ios-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ios-mcp on Agent Skills Hub include flutter-skill, claude-code-plugins-plus-skills, mcp-router. 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: