context

I got tired of my AI agent hitting rate limits right when I was actually getting work done. I’d be using an MCP server for docs, and suddenly the assistant would start hallucinating old API patterns because the cloud service I was using hit its cap or was lagging. It felt kind of ridiculous that we’re paying monthly subscriptions and dealing with network latency just to query markdown files. These docs don't change every five minutes—they change per version. So I spent the last week building a local-first version called Context. The idea is pretty simple: you "build" a library's docs into a local SQLite file once. From then on, your AI can query it in under 10ms with zero internet. A few things I realized while building it: - FTS5 is underrated: Everyone wants to jump straight to Vector DBs and embeddings, but for docs, simple full-text s