Contextberg
Local AI agent memory for macOS & Windows, served via MCP
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Contextberg - Local AI agent memory served via MCP

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Contextberg brings local AI agent memory to macOS and Windows. It captures screens, browser history, and agent conversations into a private, searchable archive, then serves relevant context to Codex, Claude Code, Cursor, and other agents over MCP. This launch adds native macOS capture, OCR screenshot search, source exclusions, and flexible model routing: use your existing Codex sign-in, a Gemini/OpenRouter API key, Contextberg Cloud, or a fully local model.

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Hey Product Hunt 👋 I’m Tiger, the solo founder of Contextberg. I built it because I was tired of re-explaining my work to AI agents. After every reset, task switch, or weekend away, the context already existed—in my screens, browser research, and previous agent conversations—but I had to reconstruct it manually. Contextberg turns that work into local, reusable memory and serves the relevant context to Codex, Claude Code, Cursor, and other agents over MCP. What’s new in this launch: 🍎 Native macOS app, alongside Windows 🔎 OCR search across captured screens 🛡️ App and source exclusions 🧠 Short-term, daily, and long-term memory 🔀 Use your Codex sign-in, Gemini/OpenRouter key, Contextberg Cloud, or a local model Your archive stays on-device. Only the context you choose to use is sent to the model provider you select. I’m building the memory layer under the agent—not another agent that locks you into one model. What part of your workflow does your AI agent forget most often? I’d love to hear how you currently reconstruct context.