Own your AI's context and memories across every model and device
Details
- External ID
- 47303645
- Source
- HN
- Company
- —
- Product
- Own your AI's context and memories across every model and device
- Website domain
- github.com
- Launched
- March 9, 2026
- Cohort
- —
- Upvotes
- 7
- Upvotes percentile
- 0.4108241082410824
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
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!
Enrichment
- Theme
- AI visibility and marketing tools
- Vertical
- Horizontal
- Function
- Agent / copilot
- Audience
- B2C
- AI stance
- AI-native
- Project type
- Commercial product
- Normalized one-liner
- portable context and memory for ai assistants
- Manually corrected
- False
Could you build this?
Yes It involves setting up a central PostgreSQL/pgvector database with an API or MCP server to store and retrieve contextual notes across different AI tools.
Discussion
1 comment analyzed.
Competitors
Other products that read as similar to this one — 224 launches clear the similarity bar, closest 8 shown.
Attention rank: #131 of 225 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 119 days after the earliest competitor.
- Living Memory · ph · 2026-09-30 · 3 upvotes · similarity 0.52
- Memoro · ph · 2026-09-17 · 2 upvotes · similarity 0.50
- Second Brain for AI · ph · 2026-05-31 · 284 upvotes · similarity 0.50
- Sensefold · ph · 2026-09-17 · 1 upvotes · similarity 0.48
- Build AI Trading Agents in Cursor/Claude with an MCP Server · hn · 2026-03-27 · 6 upvotes · similarity 0.48
- WhileAI · ph · 2026-09-28 · 1 upvotes · similarity 0.47
- AI Visibility Tracking · ph · 2026-09-21 · 1 upvotes · similarity 0.47
- CalAI Solutions · ph · 2026-09-10 · 2 upvotes · similarity 0.46
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a agent / copilot tool for Agriculture yet.