Summary
Context management for AI-assisted coding has matured into a rich ecosystem: convention files, repository maps, memory banks, and full-blown memory frameworks all compete to keep a coding agent grounded in your codebase.
But step outside the terminal and ask an assistant about your health or your finances, and the tooling nearly vanishes. Your personal context lives in one vendor’s memory feature, locked to that vendor, or it lives nowhere.
This article argues that the missing piece is not a smarter memory system but a separation of concerns: put personal context in storage the user owns, independent of any AI vendor, and let every assistant connect to it. It describes a working open source implementation of that principle, a Git-hosted Markdown vault served to multiple LLM surfaces through a single remote MCP endpoint, along with the trade-offs that design accepts.
Running that system on edge infrastructure also surfaced a problem that reaches well beyond it: edge platforms forbid runtime code generation, which silently disables the fast path of the TypeScript ecosystem’s standard validation library.
