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REA (Reverse Engineer Anything) connects AI coding agents to reverse-engineering tools through the Model Context Protocol (MCP) and a command-line interface. Startup Fortune reported that the open-source project reached number one on GitHub Trending shortly after launching on October 7, 2026. That headline describes reported attention, not proof that REA can analyze every program or recover its original source code.
What is REA?
REA is an orchestration layer: it connects a supported coding agent to tools and workflows for examining software artifacts and behavior. Rather than doing every kind of analysis itself, it registers an MCP server and workflow instructions with an agent. The command-line interface uses the same workflows.
A user can ask an agent to investigate a feature. The agent calls REA tools, receives findings and supporting evidence, and can use those results to explain how the feature works or help implement something similar. REA’s broad “reverse engineer anything” pitch is not a guarantee that every target is supported.
The project’s documentation says: “Analysis runs locally, and results include the evidence and limitations behind each conclusion.” The outputs can include artifacts such as pseudocode and assembly; they are not proof that the target’s original source code has been recovered. The official REA repository describes its current workflows and qualifications.
#1 Best Overall
What can REA analyze?
The repository lists workflows for a range of software and artifacts. Available depth depends on the target, operating system, and installed analysis tools.
| Target | Documented inspection | Important dependency or qualification |
|---|---|---|
| Native binaries | Pseudocode, assembly, strings, symbols, calls, and references | Deep analysis requires a configured provider such as Hopper, Ghidra, or IDA. |
| JavaScript and Electron applications | Modules, imports, source maps, routes, IPC, and native add-on relationships | Static inspection can work without a native analysis engine. |
| Websites | Page structure, scripts, network observations, and requested screenshots | Uses a Chrome-family browser. |
| .NET assemblies | Metadata, CIL instructions, native dependencies, and build comparisons | Static inspection can work without a native analysis engine. |
| Android APKs | Manifest declarations, classes, decompiled methods, and references | Uses headless JADX and a full JDK. |
| Firmware | Extraction results and handoffs to native analysis | Uses Binwalk or Unblob on Linux. |
| Other documented workflows | Go binaries, WebAssembly, EVM bytecode, recorded Linux crashes, Android devices, JEB projects, resources and packages, saved network captures, and process behavior | Requirements and platform support vary by workflow. |
Static inspection and runtime capture are different kinds of work. Runtime capture runs or interacts with a target using the user’s permissions, so the target environment and access level matter. The repository also cautions that feature availability can differ between the repository and the latest npm release.
Which agents and runtime versions does it support?
The repository names Claude Code, Codex, Cursor, Gemini CLI, and Grok Build as supported agents. Setup requires Node.js and npm. The listed supported Node.js versions are 22.x (at least 22.19), 24.x (at least 24.11), or 26 and later.
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- Run
npx rea-agents setupto propose configuration changes for an agent. - Review and approve the proposed changes before using REA.
Check the repository’s current setup instructions before installing, since supported workflows and release availability may change.
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Does REA upload the software being inspected?
The project says analysis runs locally, but that does not mean no information reaches an AI provider. The connected agent receives REA’s tool results, and the model provider applies its own data-handling policy. Consider both the target’s sensitivity and the provider’s policy before asking an agent to analyze proprietary or personal material.
What did the GitHub Trending claim actually report?
In an October 9, 2026 report, Startup Fortune reported that REA launched October 7, received roughly 2,956 stars in 24 hours, had more than 10,400 total stars when the article was published, and reached the top of GitHub Trending. Those are the outlet’s launch-era figures and ranking claim; they are not an independently verified dated archive of GitHub Trending.
The official repository displayed 125.5k stars when retrieved on October 12, 2026. That is a later, volatile snapshot, not the launch-day count. The two figures refer to different dates and should not be combined.
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What are REA’s licensing and responsible-use limits?
The project describes REA as intended for lawful research, education, interoperability, software preservation, and analysis of software a user owns or is authorized to examine. Its MIT license covers REA, not commercial analysis engines. The repository says users must obtain and use tools such as IDA Pro/Hex-Rays, Hopper, or JEB under their own applicable terms; REA does not provide a license, key, or activation entitlement.
Because analysis results are evidence-based interpretations rather than recovered original source, users should evaluate the evidence and limitations before relying on an agent’s conclusion or using it to recreate a feature.
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