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 mobile-next · MCP Server · ★ 6.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mobile-mcp safe to install? View the security audit →
Mobile Next - MCP server for Mobile Development and Automation | iOS, Android, Simulator, Emulator, and Real Devices This is a Model Context Protocol (MCP) server that enables scalable mobile automation, development through a platform-agnostic interface, eliminating the need for distinct iOS or Android knowledge. You can run it on emulators, simulators, and real devices (iOS and Android). This server allows Agents and LLMs to interact with native iOS/Android applications and devices through structured accessibility snapshots or coordinate-based taps based on screenshots. <img src="https://img.shields.io/badge/license-Apache 2.0-blue.svg" alt="Mobile MCP is released
| Stars | 6,723 |
| Forks | 588 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 69.9997946198285/100 |
| Open Issues | 43 |
| Last Updated | 2026-09-16 |
| Created | 2025-03-28 |
| Platforms | mcp, node |
| Est. Tokens | ~18k |
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mobile-mcp is Model Context Protocol Server for Mobile Automation and Scraping (iOS, Android, Emulators, Simulators and Real Devices). It is categorized as a MCP Server with 6.7k GitHub stars.
mobile-mcp is primarily written in TypeScript. It covers topics such as agent, android, emulator.
You can find installation instructions and usage details in the mobile-mcp GitHub repository at github.com/mobile-next/mobile-mcp. The project has 6.7k stars and 588 forks, indicating an active community.
mobile-mcp is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to mobile-mcp on Agent Skills Hub include paseo, docker-android, gpt-researcher. 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: