Juice is a lightweight, open-source alternative to tools like Cursor, Devin, and Claude Code, designed to run entirely client-side within a standard browser window.
Architecturally, it operates via a local Flask backend on your machine and communicates with LLM providers natively. It utilizes a bring-your-own-API-key model, with direct out-of-the-box support for Google AI Studio and OpenRouter. Because all communication occurs client-side, your source code and API keys remain local, private, and secure.
Key Capabilities
- Agentic Execution Loop: Juice runs a full agentic loop. It chains tool calls, executes them locally on your machine, feeds the results back to the model, and iterates autonomously until the high-level request is complete.
-
6 Core System Tools: Built-in capabilities to
read_file,write_file,edit_file(with red/green inline diff previews),list_dir,run_command, and perform local or SSH remotesearch_code. -
UX Enhancements: Features full
@filenameautocomplete for referencing codebase files, URL context scraping (paste a URL and Juice fetches the text), live streaming token responses, and automatic session state persistence.
Quick Start & Installation
To run Juice locally, you only need Python and a few basic dependencies.
1. Clone & Install
git clone https://github.com
cd juice
pip install flask requests beautifulsoup4
2. Launch the Backend
python3 juice.py
3. Open in Browser
Navigate to http://localhost:5000 to input your API key, select your working directory, and start an autonomous coding session.
Technical Feedback Welcome
The project is fully open-source under the AGPLv3 license. As the tool is currently in alpha, I am looking for deep technical feedback from the developer community regarding:
- Agent file-manipulation safety and terminal execution guards.
- Token context window management optimizations.
- General stability of the agentic loop when dealing with deeply nested repositories.
Repository: https://github.com/ayaangalaxy2012-hub/Juice

I'll be monitoring the comments below to answer any questions regarding the implementation, prompt engineering strategies, or backend architecture!
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