tterm is a free, privacy-focused desktop app that combines a terminal, a real browser, and Claude Code into a single window. It is designed for developers who want to manage projects, browse the web, and interact with AI without leaving their terminal environment.
A terminal, a real browser, and Claude Code under one roof
- Developing and debugging code with integrated terminal and AI assistance
- Browsing the web with full Chrome integration while coding
- Managing multiple projects in separate rows within the same window
- Using Claude Code to modify the app itself in real-time
- Reviewing and committing code changes without leaving the terminal
- Download tterm from the website and unzip the file.
- Drag tterm.app to your Applications folder.
- Clear the macOS quarantine flag by running the provided command in Terminal.
- Open tterm and use ⌘K to ask Claude for features or modifications.
- Use ⌘B to access your Chrome cookies, bookmarks, and history.
- Use ⌘G to stage and commit code changes directly.
Scale PostgreSQL without changing your app
The easiest way to deploy a managed agent.
Platform for building with Google's Gemini AI models.
The AI database client for Mac
Caps Lock keeps your Mac awake, even with the lid closed
The web performance & security company
Full-Stack Platform for Training Small Language Models
A free, open source, Descript alternative. Runs in-browser.
Privacy-friendly web analytics with traffic and revenue.
Keep any Mac window visible in a floating mini screen
Control every aspect of model training and fine-tuning
AI-powered schematic design tool for PCB making
A private data-usage meter for your Mac menu bar
The terminal and Mac menu bar companion for Kickbacks.ai
Tamamon is a free macOS desktop pet that grows as you code with Claude Code. It reads your Claude usage to evolve the pet, but never accesses your code or data. The pet appears on your desktop, reacts to your activity, and can be fed and played with.
Give Claude Code and Codex a voice
See it once. Ask forever.
AI platform for deep video understanding
