REA is an open-source reverse engineering tool: it helps you research how a finished program is built and how it works under the hood. It connects to Codex or Claude Code through MCP and gives the agent the ability to analyze applications even when their source code isn't available. The name stands for Reverse Engineer Anything.
Explosive Growth on GitHub
The project has literally taken off. As of October 12, REA already has more than 114,000 stars and currently sits at #1 on daily GitHub Trending. GitHub shows a gain of more than 25,000 stars in a single day. Interest in the tool is enormous.
How It Works
Noticed a clever feature in an app and want to understand how it actually works? With REA, you can hand that question straight to an agent. It can investigate desktop applications, websites, Android apps, and compiled executables. The specific toolset it uses depends on what exactly needs to be examined.
The process starts with a concrete question. How does an app preserve formatting when you copy text? Where does it store its settings? How does a particular game mechanic function? The agent explores the available files, traces the connections between them, and explains what it finds, pointing to the relevant functions, code sections, and other supporting evidence. From there, you can design and test a similar feature for your own project.
Under the Hood
REA's documentation includes a breakdown of Notion's clipboard mechanism and examples of recovering specific calculations from old games. For deep analysis of compiled programs, it relies on specialized tools like Hopper, Ghidra, or IDA, which the agent controls through REA itself.
Reviving Legacy Software
This approach is also useful for dealing with your own aging software. The source code is lost, the original developer left the company years ago, but the program is still running and holding onto important data. REA offers a way to investigate its behavior and figure out exactly what it would take to migrate it to a new system.
A Few Caveats
The name "Reverse Engineer Anything" should be read as an ambition rather than a guarantee. How thorough the analysis is depends on which files and tools are actually available. Any logic the agent uncovers still needs to be verified, and any new implementation built from it still needs proper testing.
Tools like REA point to a broader shift: AI agents are no longer limited to writing new code from scratch, they're increasingly capable of making sense of code that already exists, even without access to its source. For teams sitting on legacy systems or developers just curious how their favorite apps tick, that's a meaningfully different kind of capability worth keeping an eye on.