Second Brain for AI - Persistent memory for Claude, ChatGPT & Cursor. Free.

Hey Product Hunt, I'm Rahil. I built Second Brain.

I got tired of explaining myself to every AI tool during each session. A new Claude window is a blank slate. A new Cursor project doesn’t know my stack. It adds up quickly.

Second Brain is a self-hosted memory layer that connects to Claude, ChatGPT, Cursor, and any MCP client. You store context once and recall it by meaning across any session. Everything lives in your own Cloudflare account, not on a third-party server. There's a free tier, and you don't need a subscription. You also get a web UI to browse and manage everything visually.

What makes it different:

• It works with all your AI tools—not tied to one app.

• It uses semantic recall, which finds memories by meaning instead of exact keywords.

• It’s self-hosted, so your data stays in your own Cloudflare account.

• There’s a free tier, so it costs nothing to run.

• The web interface lets you browse, search, and manage memories visually.

II’m really curious: what context do you find yourself re-entering most? That has influenced my roadmap more than anything else.

Ask me anything. Big shout out to @fmerian for his support!

Quick update since launch. Here are a few things worth noting:
We shipped the Second Brain CLI today. If you use the terminal, you can now capture and recall memories without leaving it.

npm install -g second-brain-cf-cli

For those asking about integrations, Second Brain works with Claude, ChatGPT, Cursor, Windsurf, and any MCP-compatible client. There’s also an Obsidian plugin in the community directory, a Chrome extension, iOS Shortcuts in the repo, and a web UI if you prefer managing everything visually.

CLI, Obsidian, Chrome extension, iOS Shortcuts, MCP… same memory, every interface.

How does duplicate detection handle near-duplicates or nuanced variations in context? I've found that tricky in my own memory tools.

The between-session memory problem is real and this solves it well. The harder problem - at least for how I use AI - is within-session overflow. My conversations regularly hit 100K+ words before they die/lag to unusble. The context window can't hold it all anyway, so even within a single session I'm losing early context. What I actually want is a rolling summarizer that compresses as the thread grows - keeping the essential through-line while shedding weight. That plus persistent cross-session memory would be the full solution. This a great idea tho, one I really like!

the memory problem is so underrated in AI tooling right now. you spend 20 minutes setting up context in a conversation and then it just... vanishes. self-hosted is the right call too, especially for teams dealing with proprietary code. how does it handle conflicting memories across different tools?