Recently, a friend and I built a little tool called Open Machine. Basically, it uses MCP to connect ChatGPT to your local computer and remote servers, giving regular ChatGPT Codex-like capabilities, and in some cases even more flexibility. Things like running and editing code, managing remote servers, and handling browser tasks. We actually built it for ourselves at first. In our day-to-day work and model training, we kept running into the same problems: token and context limits, growing amounts of data that were hard to organize, and the hassle of sharing information and handing off work between teammates. Model training was especially frustrating. We often had to manage multiple servers and constantly switch between our local machines and different remote environments. So we wanted to build something that could bring all of this together and let AI handle more of the actual work. That's really how Open Machine started. We've now open-sourced it, although there's still a lot we want to improve. Next, we're planning to build Desktop and Cloud, making it easier to manage multiple remote servers from one computer, and to index, sync, and update local files and databases. The idea is to make it easier for individuals and teams to build and manage their own local knowledge bases. I'm sure a lot of people working on model training or software development have run into similar problems. If this sounds useful, feel free to check it out! We'd also love to hear your feedback and ideas. GitHub: github.com/OpenMachineLabs/o…