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 firerpa · MCP Server · ★ 8.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lamda safe to install? View the security audit →
FIRERPA Android ｜ AI-Powered Automation An all-in-one next-gen Android automation framework blending robust on-device services with AI-ready agents and extensible tool-calling capabilities. Documentation llms-full.txt Core Capabilities FIRERPA is a lightweight, on-device Android automation stack with no external dependencies. It unifies low-latency remote desktop with 160+ APIs for device discovery/status/logs, system and app control, UI automation, OCR/image matching, file I/O, storage, scheduling, and shell execution, plus distributed deployment via Hub/FRP/OpenVPN. Built-in ADB/SSH/SCP,
| Stars | 8,258 |
| Forks | 1,109 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 56.961593844762/100 |
| Open Issues | 41 |
| Last Updated | 2026-08-30 |
| Created | 2022-07-10 |
| Platforms | browser, cli, mcp, python |
| Est. Tokens | ~14k |
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lamda is Android Full-Stack Device Control Platform: WebRTC/H.264 remote desktop, UI/OCR/image-matching automation, one-click MITM, built-in Frida, proxy/VPN/frp/P2P networking, MCP/Agent, 160+ APIs, designed . It is categorized as a MCP Server with 8.3k GitHub stars.
lamda is primarily written in Python. It covers topics such as adb, agents, ai.
You can find installation instructions and usage details in the lamda GitHub repository at github.com/firerpa/lamda. The project has 8.3k stars and 1109 forks, indicating an active community.
lamda is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to lamda on Agent Skills Hub include jadx-ai-mcp, gpt-researcher, trigger.dev. 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: