Lantor: A Local-First AI Agent Workspace

Research context and background

Lantor is a software tool built for developers who want to use artificial intelligence agents to write code. It acts as a private workspace where a human operator can manage multiple AI agents, such as Codex or Claude, to work together on projects. The main idea behind Lantor is that all data stays on the user's computer. There is no cloud server, no external backend, and no hosted control plane. This means chat history, tasks, and agent memories are stored locally on the user's Mac. This design ensures complete privacy and gives the user full ownership of their work context.

Benefits

Lantor offers several key advantages for developers who value privacy and control. First, it keeps all data local. Nothing leaves the user's machine, which is perfect for sensitive projects. Second, it gives users full control over their context. Users can inspect, back up, or extract chat history, tasks, and agent memories stored in specific folders on their disk. Third, it supports multi-agent coordination. A single human can manage multiple AI agents using features like channels, direct messages, and threads. This allows teams of AI to communicate and work on different parts of a project without confusion. Finally, it provides flexible access. Users can run a native desktop app on their Mac and also access a web interface from their mobile devices on the same trusted network without needing a separate mobile app.

Use Cases

Lantor is designed for developers who want to automate coding tasks using AI. A common use case involves a developer asking an AI agent to inspect GitHub issues. The agent processes the findings and converts them into actionable tasks. The system then preserves the context of the conversation so that if the work needs to be handed off to another agent, the new agent understands the full history and rationale. Another use case is managing complex projects where multiple AI agents need to collaborate. The human operator can assign tasks, set reminders, and track progress through a clean interface. Developers can also use the mobile web interface to check on their local AI agents while away from their desk, as long as they are on the same trusted network.

Pricing

Lantor is an open-source project available under the Apache-2.0 license. This means it is free to download, use, and modify. There are no subscription fees or hidden costs. Users can install it by cloning the repository from GitHub and following the provided setup instructions. The software requires a Mac, Node.js, and Rust to run, but there is no cost associated with the software itself.

Vibes

As an open-source tool, Lantor does not have public reviews or testimonials in the traditional sense. It is a new project hosted on GitHub by a single developer. The community reception is currently based on the code quality and the features available in the repository. The project has attracted attention from developers interested in local-first AI tools and privacy-focused workflows. Since it is still in development, users are encouraged to try it out and provide feedback directly to the maintainers.

Additional Information

Lantor is developed by a single creator and is available on GitHub. The project is built using modern web technologies and runs as a native macOS application. It uses a local SQLite database to store all workspace data. The architecture includes a local supervisor that manages agent runs and ensures only one active task runs at a time per agent. The project is actively maintained, with support for both desktop and web-only development modes. Users can contribute to the project by submitting issues or pull requests on the GitHub repository.