Own your AI's context and memories across every model and device

Hey HN,I pay for ChatGPT, Claude, Cursor, and use Gemini through work. Four vendors, four separate conversation histories, four profiles of how I think. None of them talk to each other. Switch providers and you start over.So I built a system where the memory is mine. I run a knowledge graph in Postgres (Supabase, free tier) with pgvector for semantic search. A small MCP server reads and writes to it. That server sits behind an MCP Gateway on a $6/month VPS, along with Brave Search and a GitHub server. TypingMind connects to the gateway as a BYOK client -- any model, any device, same brain.https://github.com/kaspnilsson/digital-twin-playbookWhen I switch from Claude to GPT-5 to Gemini, the new model picks up where the old one left off. After three months of daily use, the AI knows my project architectures, my preferences, my side projects. I never re-explain any of it.The MCP server is MIT-licensed: https://github.com/kaspnilsson/mcp-memory-supabase The playbook walks through the full setup -- Supabase schema, VPS hardening, Caddy, systemd, the system prompt that makes tool routing work: https://github.com/kaspnilsson/digital-twin-playbookWhat it costs me: ~$45/month ($6 VPS + ~$36 API compute via OpenRouter + $3 amortized TypingMind license). More than a $20 subscription. But the $20 price is subsidized, and my data stays on my server. What does not work well: TypingMind is a PWA, not a native app. Voice is rough. iOS kills background processes on long tool chains. MCP config does not sync across devices. You are your own SRE.This is not a consumer product. If you want polish, use Claude.ai. If you want to own the context that makes your AI useful, this is how I did it!