What local memory means for AI agents
A practical look at recording work history locally and serving it to Claude Code, Cursor, and other agents through MCP.
Agents lose the context around your work
AI agents are useful for writing code and text, but they do not automatically know which screen you were looking at, which page you researched, or which command you just tried.
That forces you to repeat filenames, browser tabs, and intent. The friction is small in one prompt, but expensive across daily work.
Contextberg keeps work context local
Contextberg records screen, browser, and agent activity on your PC, then turns that history into structured memory you can inspect and reuse.
The default posture is local-first, so you can start without sending your personal work log to the cloud.
MCP makes that memory available to agents
The recorded context can be served to Claude Code, Cursor, and compatible tools through MCP.
That gives agents the context to answer based on what you were actually doing, reducing the need to restate everything manually.