Qurt is an open-source desktop AI coworker for Windows and macOS. It is built for working with multiple AI models from one app, with a focus on research, drafting, terminal work, and file-based tasks.
The product says it can research the web, write drafts, run terminal commands, and read files. Its feature set also includes an agent mode for more direct task execution: AI can browse the web, run workspace-restricted terminal commands, and edit files in a controlled environment where every action is reviewed before it runs. Qurt also supports real-time search across providers, controlled web automation through a browser, file editing with checkpoint revert, and chat attachments for files and images so that analysis, summaries, and answers can be grounded in the attached content. It offers a single model selector for providers such as GPT-5.2, Claude Opus 4.6, Gemini 3.1 Pro, and Grok 4, along with the ability to adjust reasoning effort per message and compare outputs across providers.
Qurt is described as desktop-native rather than browser-based, and it is available for Windows and macOS. The site says it is available for Windows and macOS, and the download flow is presented as a simple install-and-start process with no account needed. Users add their own API key from a supported provider and then begin chatting.
Pricing and access are presented as free, with no subscription and no lock-in. The app is open source, and the page says users can view the code, file issues, and contribute features. It also states that chats, keys, and files stay on the user’s machine and are not stored on the company’s servers.
Qurt sits in PulseGate's Other agents category. It focuses on using multiple AI models for research, writing, and automation tasks on the desktop without vendor lock-in. It is built as a consumer product for knowledge workers. Qurt costs nothing to use. It ships for the command line, macOS, and Windows.
Qurt first shipped in 2026. The project is developed in the open on GitHub with 11 stars. Among its 8 catalogued features are multi-model support, file analysis, and web research.
Summary written by a language model from the project’s public pages.
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