I Built a Portable AI Memory Layer with MCP, AWS Bedrock, and a Chrome Extension

AI tools have memory now. Claude remembers your projects. ChatGPT has built a profile of how you work. Open a new conversation and the tool already has context - you don't have to re-explain yourself from zero every time. The problem is that this memory is platform-locked. Switch from ChatGPT to Claude and you lose six months of built-up context. The new tool doesn't know your projects, your preferences, your ongoing work. Technically it might be the better model for what you need right now - but it performs worse because it's starting blind. So you go back to your old tool. Not because it's better. Because it knows you. That's the lock-in. Not pricing, not features - context. And it's the problem MemoryMesh solves. MemoryMesh is a portable context layer: a Chrome extension + MCP server + AWS serverless backend that captures your context from any AI tool and injects it into any other. Your context travels with you when you switch. This article walks through how it's built. GitHub: gith