Contextberg

About Contextberg

Contextberg is a local memory application that captures your on-screen activity, browser history, and agent conversation logs to provide persistent context for AI agents. It runs in the background and delivers curated memory to agents via an MCP endpoint so they can reference past work without repeated explanations.

Review

Contextberg takes a passive-capture approach to building agent memory: it stores raw signals, compresses them into short-term memories frequently, and synthesizes long-term memories on a slower cadence. The app is presented as a lightweight desktop client with options to limit what is recorded and the ability to process memory locally for users who prefer that.

Key Features

• Passive capture of screens, browser activity, and agent conversations to create an immutable raw data layer.
• Periodic compression pipeline that generates short-term and long-term memory representations from raw captures.
• Memory served over MCP with callable skill/command interfaces so agents can request context when needed.
• Local processing options and user controls for disabling specific capture types to limit sensitive data collection.
• Simple installer and a free entry point to try the service without an initial payment.

Pricing and Value

Contextberg launches with a free tier that lets users try core capture and memory features at no cost. The value proposition centers on saving time and reducing repetitive context-sharing by preserving session history for AI agents. For users who rely on repeated agent sessions, the time savings and smoother handoffs can justify paid plans if those appear later; however, the long-term value will depend on pricing for advanced features and any storage or processing limits that may be introduced.

Pros

• Maintains continuity across agent sessions so you spend less time re-explaining projects.
• Passive capture can surface important context that users might forget to save manually.
• Local processing options and explicit capture toggles give users more control over sensitive data.
• MCP integration and skill/command interfaces make memory access query-driven rather than always injected.

Cons

• Collecting screenshots, browser history, and keystrokes raises real privacy and security concerns that require strong controls and auditing.
• Passive capture produces noisy data; without good compression and retrieval filtering, irrelevant content could degrade usefulness.
• Initial platform focus is desktop-first, so users on other platforms may have limited support until additional releases.

Contextberg is a solid fit for developers and power users who want agents to retain project context across sessions and who are willing to configure privacy settings carefully. It works best for workflows where saving time on context transfer matters and where users can accept the tradeoffs of passive capture in exchange for richer, automatically gathered memory.

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