Développement
potpie
A context graph for the AI-native SDLC — so agents and humans share one map of the codebase.
★ 5,7 k étoilesApache-2.0
Voir le guide →rea est un projet de développement open source, créé par morluto (morluto/rea sur GitHub). Il compte 21 368 étoiles sur GitHub et 2 305 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.
Reverse engineer anything with agents - from app behavior down to native binaries
Choose the app, binary or code path whose behavior you need to understand.
Run the one-command setup with npx - no manual clone is needed for normal use.
Let the setup register REA's MCP server and skill with your agent, then restart the agent.
Ask your agent to analyze the target and review the evidence-backed findings it returns.
A single MCP server covers binaries, applications and runtime behavior for your agent.
Returns modules, imports, boundaries and the evidence behind each conclusion, not just guesses.
Works with established analysis tools - the project tags Ghidra and Hopper among its ecosystem - for native analysis.
The same workflows run through your agent via MCP or from the terminal via the rea command.
The README demonstrates cases like tracing Notion's Electron clipboard bridge and reconstructing game logic from a DOS binary.
You can start in demo mode before activating any license the setup prompts for.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/morluto/rea.git
cd reaOne npx command installs and registers REA with your coding agent.
npx rea-agents setupIf you use npx, refresh your agent registrations and skill with the latest package.
npx rea-agents@latest setup # see README Update sectionIt is maintained by morluto and contributors on GitHub.
REA is MIT licensed and free to use as open source; the setup may offer demo mode or license activation for parts of the product - see the README for details.
REA works through your own AI agent, so you need a Claude Code, Codex or similar agent setup with its own model access; REA itself is the analysis layer.
Compared with driving Ghidra or a disassembler by hand, REA lets the agent orchestrate the analysis and returns structured, evidence-linked findings in natural language.
Run npx rea-agents setup, restart your agent, and ask it to analyze a target - the README's showcases show the style of questions it handles.
A context graph for the AI-native SDLC — so agents and humans share one map of the codebase.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.