Extract Your AI Coding Data with This Open Source Tool
If you've been experimenting with AI-powered coding assistants like Cursor, Claude Code, or Windsurf, you might be curious about what data these tools are collecting from your sessions. It's not always clear what information these applications store locally or how they're tracking your coding patterns.
That's where this handy extraction tool comes in. It gives you a straightforward way to peek under the hood and see exactly what personal data and interaction history these AI coding assistants are keeping on your machine.
What It Does
This Python tool scans your local system for data stored by various AI coding assistants and extracts your personal interaction history into readable formats. It currently supports Cursor, Codex, Claude Code, Windsurf, and Trae, pulling conversation histories, code snippets, and other session data that these applications store locally.
The tool outputs organized JSON files that give you a clear picture of what information these tools are retaining from your daily coding sessions.
Why It's Cool
Beyond just satisfying curiosity, this tool serves some practical purposes. For developers concerned about privacy, it provides transparency into what data stays on your local machine. If you're researching AI coding patterns, you can analyze your own interaction history to understand how you use these tools. It's also useful for backing up your valuable AI conversations or migrating them between devices.
The implementation is straightforward Python that focuses on the specific file paths and data formats each AI assistant uses. It's not trying to be fancy—just effective at locating and parsing the data these applications leave behind.
How to Try It
Getting started is simple:
git clone https://github.com/0xSero/ai-data-extraction
cd ai-data-extraction
python extract.py
The script will automatically detect which AI tools you have installed and extract their available data. You'll find the results in the output directory, organized by application with timestamps and structured conversation history.
Final Thoughts
As AI coding assistants become more integrated into our workflows, understanding what data they collect feels increasingly important. This tool doesn't make judgments about whether the data collection is good or bad—it just gives you the visibility to make that determination yourself.
Whether you're privacy-conscious, just curious, or want to analyze your own AI coding patterns, this extraction tool provides a simple way to take control of your data. It's one of those utilities you might not need every day, but you'll be glad exists when you do.
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