BrowserOS neo

BrowserOS neo is an open-source AI browser built for coding agents that need to use the real web, not a blank sandbox. It gives Claude Code, Codex, Cursor, Cowork, OpenClaw, Hermes, and other MCP-compatible agents a separate local browser where they can navigate pages, click buttons, fill forms, read content, and work inside logged-in accounts while the user watches. The product is best understood as a second browser for agents rather than a Chrome replacement for people. The main workflow starts with installing BrowserOS neo, importing logins from Chrome, and connecting an agent through MCP. After that, the user gives a task from a terminal or IDE and the agent drives BrowserOS neo in its own tabs. The agent can work on tasks such as checking dashboards, using GitHub, cleaning inboxes, filing forms, pulling reports, or testing web apps that require authentication. BrowserOS says sessions, screenshots, and history stay on the local machine. BrowserOS neo stands out because it focuses on observability. Users can watch active sessions live from the cockpit dashboard, see what site an agent is visiting, and replay saved sessions later as a video with an action timeline. That makes it easier to audit mistakes, tune prompts, and decide whether an agent should be trusted with more complex browser tasks. The product also claims to reduce token usage by sending compact page snapshots and batching browser actions instead of dumping raw HTML into the model context. For developers and AI builders, BrowserOS neo is useful when headless browser automation is too sterile and cloud browsers are too detached from a user's real work. It can use real sessions, local files when permitted, and existing browser context, while keeping the agent separate from the user's main browsing window. The open-source AGPL-3.0 repository also makes it inspectable for teams that want to understand how agent browser control is implemented. Pricing is simple: BrowserOS neo is presented as free and open source. Teams should still budget for the model or agent they connect to it, plus any API usage created by those agents. The safest starting point is to run it as a secondary browser, connect one agent, test low-risk workflows, and review session replays before giving agents access to sensitive accounts or irreversible actions. Because BrowserOS neo is agent-facing, its strongest fit is controlled automation. Start with reversible tasks, inspect replays, then expand access only after the agent handles the workflow reliably.