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 CursorTouch · MCP Server · ★ 802
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Android-MCP safe to install? View the security audit →
🤖 Android MCP Android-MCP is a lightweight, open-source tool that bridge between AI agents and Android devices. Running as an MCP server, it lets LLM agents perform real-world tasks such as app navigation, UI interaction and automated QA testing without relying on traditional computer-vision pipelines or preprogramed scripts. ✨ Features Native Android Integration Interact with UI elements via ADB and the Android Accessibility API: launch apps, tap, swipe, input text, and read view hierarchies. Bring Your Own LLM/VLM Works with any language m
| Stars | 802 |
| Forks | 109 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.1914998143368/100 |
| Open Issues | 8 |
| Last Updated | 2026-07-01 |
| Created | 2025-06-11 |
| Platforms | mcp, python |
| Est. Tokens | ~14k |
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Android-MCP is MCP Server for interacting with Android Devices.. It is categorized as a MCP Server with 802 GitHub stars.
Android-MCP is primarily written in Python. It covers topics such as ai, android, automation.
You can find installation instructions and usage details in the Android-MCP GitHub repository at github.com/CursorTouch/Android-MCP. The project has 802 stars and 109 forks, indicating an active community.
Android-MCP is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Android-MCP on Agent Skills Hub include flutter-skill, rulego, better-chatbot. 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: