The problem it solves
Every AI tool keeps its own memory silo. Tell Claude your stack is "Next.js + Postgres," and ChatGPT still doesn't know. Cursor forgets your naming conventions the moment a session ends. You end up re-explaining yourself to each tool — the context tax.
The fix: externalize memory
Move memory out of the tools and into one store they all share. Each assistant becomes a stateless client; the state lives in a database you control.
Why MCP is the glue
The Model Context Protocol gives every compatible client the same way to call external tools. Your memory server exposes two capabilities — roughly store(text) and search(query) — and any MCP client (Claude, Cursor, and a growing list) can call them without custom integrations per app.
How recall actually works
Embeddings, not keywords
When you store "I prefer Tailwind over plain CSS," the server converts the sentence into an embedding — a vector of numbers capturing meaning. Later, the query "what styling does the user like?" is embedded too, and the store returns memories whose vectors sit closest, even though no words match exactly.
Why Cloudflare's free tier fits
A personal memory layer needs three cheap parts: an HTTP endpoint (Workers), a place for vectors (Vectorize), and a place for raw text (D1 or KV). Traffic is tiny — a few requests per conversation — so a personal deployment typically costs nothing.
Self-hosted = yours
Because you deploy it, your preferences, notes, and project facts never live inside any one vendor's product. Switch assistants next year; the brain comes with you.