Visual mapping versus AI-readable memory
Heptabase is a visual knowledge tool. You place note cards on infinite whiteboards and arrange them spatially to map how ideas connect, alongside a journal, tags, and a card library. If you think visually, that canvas is a genuinely different and powerful way to work.
Hjarni is built around a different goal: making your notes something AI can read and write. It is a knowledge base of plain Markdown notes with an official MCP server, so assistants work from the same context across conversations. The shape is a clean note store, not a canvas.
Two official MCPs with different shapes
The MCP difference used to be existence; now it is shape. Heptabase added an official MCP in late 2025. Its official hosted MCP lets external assistants search, read, create, and edit cards and journal entries. See Heptabase’s MCP tool documentation for the supported operations.
Hjarni's MCP is the core of the product rather than a feature beside the canvas. An assistant can search your notes, open one, update it in place, and file new notes into folders, with per-folder instructions steering how it writes. Choose between a folder-based Markdown workflow and a visual card-and-whiteboard workflow; both let assistants edit existing content.
If you think spatially and want whiteboards, Heptabase is excellent. If you prefer Markdown notes organized in folders, Hjarni is a strong fit.
Built-in AI and external assistants
Heptabase leads with its own built-in AI chat, and its MCP now opens your cards to outside assistants as well. The workflow, though, is designed around the AI in the app.
Hjarni does not bundle a model. You connect Claude, ChatGPT, Codex, Cursor, or any MCP client, and the same notes serve every assistant. The knowledge does not live inside one product's AI.
How each one holds up as it fills up
The spatial canvas has a cost that shows up at scale. Heptabase's own help docs acknowledge that once a single whiteboard holds roughly 100 to 150 or more cards, you start to see noticeable lag, and the suggested remedy is to split your content across several whiteboards. That is not a bug so much as the nature of the paradigm: the browser has to lay out and render every card on the canvas, so the more you map, the more there is to draw.
Hjarni avoids that ceiling by not having a canvas at all. Notes are plain Markdown and search runs on the server, so the interface does not slow down as the knowledge base grows; finding something is a backend query, not a screen full of cards the browser has to paint. The honest tradeoff is that you give up the visual map. If spatial layout is how you think, that is a real loss. But if you mainly want a store that stays responsive as it fills with years of notes, a query beats a canvas.
When Heptabase is the better fit
If you think spatially and want to organize and connect notes visually on whiteboards, Heptabase is a strong, distinctive choice. Its Markdown export is first-class too, so your data stays portable even though the workflow is visual.
When teams pick Hjarni instead
The case for Hjarni is an MCP that maintains notes (reading, updating, and creating them in place), bring-your-own-AI across devices, and a plain-text Markdown knowledge base with a free tier. If your priority is AI that maintains your notes rather than a visual canvas, Hjarni fits better.
Hjarni notes are plain Markdown you own, exportable as a ZIP anytime, hosted in the EU.