The Problem
Every notes app I tried made the same mistake: it flattened everything into one text box. A YouTube video I want to watch later, a book I'm halfway through, a bank account, a login I need to remember, this week's tasks, a running list of expenses — they all got dumped into the same undifferentiated markdown blob and lost.
But those things aren't the same shape. A watchlist wants a poster and a "seen it?" toggle. A reading list wants an author and a progress state. A credential wants a masked field you can copy, not plaintext in a paragraph. A bank account is structured data, not prose. Treating them all as "a note" is the reason personal knowledge tools quietly rot.
So I built my own — a notes app where the type of a note determines its interface, and where an AI can actually read and act on the whole thing.
What I Built
My Notebook is organized around three pillars.
1. Typed notes with bespoke UIs. Creating a note starts by choosing what it is. Each type gets a purpose-built editor and view rather than a generic text field. The types that ship today:
| Note type | What it captures |
|---|---|
| Text note | Free-form writing, the classic default |
| YouTube | Videos to watch, saved with their context |
| Reading list | Articles and long-reads queued up |
| Music | Tracks and albums to come back to |
| Watchlist | Films and shows to watch |
| Books | Reading, with author and progress |
| Bank accounts | Structured account details |
| Credentials | Logins, stored as structured fields |
| Tasks | To-dos with state |
| Expenses | Money in and out |
| Contacts | People, as records rather than prose |
2. AI integration. The notebook isn't a passive archive — an AI layer can summarize, search across, and answer questions about everything in it, so the notes become something you can actually query instead of a folder you're afraid to open.
3. MCP support. The whole notebook is exposed over the Model Context Protocol, so external AI clients like Claude can connect to it as a set of tools and read or write notes directly. That turns the app from a place I type things into a place my AI assistants can operate on my behalf.
Why I Built It
This one started as a tool purely for myself. I wanted a single place that respected the difference between a task and a tweet and a bank login, and that my AI assistants could plug into rather than sit outside of. It became my daily driver — the notebook I reach for first — and a small proving ground for the same idea I keep coming back to in my other work: the interface should bend to the data, and AI should be a first-class citizen of the app, not a chat window bolted onto the side.