by morluto · MCP Server · ★ 260.1k
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🔒 Is rea safe to install? View the security audit →
English · 简体中文 · 日本語 · 한국어 · العربية REA: Reverse Engineer Anything Reverse engineer anything with agents, from app behavior down to native binaries. See a feature you like. Understand how it works, down to the binary level. Quick start · Current status · Investigation model · Tool catalog · Roadmap · How it works npm install --global rea-agents && rea setup See a feature in an app that you want in y
npx rea-agents setup
npx --yes rea-agents@latest setupTaken from the project's README on GitHub. Check the security audit before running it.
Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
| Stars | 260,133 |
| Forks | 65,429 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 64.8067594637531/100 |
| Open Issues | 928 |
| Last Updated | 2026-10-15 |
| Created | 2026-04-14 |
| Platforms | claude-code, cli, codex, mcp, node |
| Est. Tokens | ~26k |
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rea is Reverse engineer anything with agents, from app behavior down to native binaries.. It is categorized as a MCP Server with 260.1k GitHub stars.
rea is primarily written in TypeScript. It covers topics such as agent-skills, ai-agents, binary-analysis.
The README on GitHub (github.com/morluto/rea) gives: npx rea-agents setup , then npx --yes rea-agents@latest setup. Usage details are in the same README.
rea is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to rea on Agent Skills Hub include archify, awesome-claude-skills, marketingskills. 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.
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