Reverse engineer anything with agents, from app behavior down to native binaries.
By leveraging Python SDK / OpenAI API, the application isolates runtime dependencies while maintaining low-latency execution traces across multi-step LLM operations.
High-throughput parsing of complex documents (PDFs, Word docs, spreadsheets, presentations)
Structured table, key-value, and metadata extraction directly into agent memory buffers
Automated report generation and document synthesis from multi-source repositories
{
"mcpServers": {
"rea": {
"command": "python",
"args": [
"-m",
"rea"
]
}
}
}
Paste into your client configuration file (e.g. ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%/Claude/claude_desktop_config.json on Windows).
Clone morluto/rea from GitHub
Install dependencies with pip install -r requirements.txt (or uv sync)
Copy .env.example to .env and add your API keys
Run the skill server and connect your AI client via stdio or HTTP
Keeps heavy parsing and raw file structures external to the LLM. Only sanitized excerpts and structured returns are injected into agent memory turns.
Enforce explicit directory allowlists and permission scopes in client configuration to ensure autonomous tool calls never breach system boundaries.
Executes in an isolated local child process communicating strictly over JSON-RPC via stdio with explicit process timeouts.
Rea is an open-source document capability designed for AI clients and autonomous agents. Reverse engineer anything with agents, from app behavior down to native binaries.
Follow the step-by-step installation: 1) Verify your runtime (Python 3.10+), 2) Add the configuration snippet into your AI client settings (e.g. claude_desktop_config.json), 3) Restart the client to initialize tool execution.
Rea is compatible with all AI tools supporting tool-calling and the Model Context Protocol (MCP), including Claude Desktop, Cursor, Claude Code CLI, Windsurf, OpenCode, and custom agent runtimes.
Rea executes locally with strict directory allowlists and permission scopes. Heavy parsing and raw file structures stay external to the LLM context window to prevent memory saturation and unauthorized access.
Yes, Rea is published under the MIT open-source license. You can inspect the source code and contribute on GitHub at https://github.com/morluto/rea.
Explore open-source implementation code, license, and community releases.
Anthropic's official Claude Skills for working with document formats — fill, merge, and extract data from PDFs, Word files, PowerPoint decks, and Excel spreadsheets inside agent workflows.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
A Streamlit app that blends agent teamwork with agent-enabled routing and fallback, built entirely on AG2..
Advanced AI AgentsThe AI Competitor Intelligence Agent Team is a powerful competitor analysis tool powered by Firecrawl and Agno's AI Agent framework. This app helps businesses analyze their competitors by extracting structured data from competitor...
Advanced AI AgentsA powerful business consultant powered by Google's Agent Development Kit that provides comprehensive market analysis, strategic planning, and actionable business recommendations with real-time web research.