The closest category overlap of the bunch
Of the developer-memory tools, Supermemory is the one that lands nearest to Hjarni, because it is two things at once: a memory API and SDK for developers, and a consumer second brain app with a browser extension. So part of Supermemory really does compete with a notes app. The honest difference is in posture. Supermemory leans toward AI capturing memory for you, often automatically, with the API first. Hjarni leans toward a person writing Markdown notes that AI then reads.
Both ship an MCP server. Supermemory's is official and open-source, with read and write and OAuth or API-key auth, and works with Claude Desktop, Cursor, and VS Code. Hjarni's is built into the knowledge base. Both are model-agnostic.
Captured for you vs written by you
The browser extension is a good tell. Supermemory wants to capture what you read and turn it into recallable context with little effort. That is genuinely useful when you want memory to accumulate in the background.
Hjarni asks for a deliberate act: you write the note. The upside is that what your AI reads is exactly what you decided to write, in plain Markdown you own and can export as a ZIP at any time. The trade is effort for control.
Supermemory leans on capture. Hjarni leans on authorship.
The failure a memory product cannot afford
For any tool whose whole promise is memory, the worst outcome is a write that succeeds but never comes back. Supermemory users have reported exactly that: documents that show up in the product's own UI, in one case more than three thousand of them, that returned nothing through any recall path. API search, the MCP recall tool, and hybrid search all came back empty. When recall runs through an embedding and indexing pipeline you cannot see, the store and the index can drift apart silently, and you only find out when you go looking for something you know you saved.
Hjarni's edge here is architectural, not a track record. A note is plain Markdown you can open, list, and read back through the UI, REST, and MCP, and there is one search index that both the UI and the MCP search tool hit, so what you can see is what you can search. The case is not that Hjarni search is proven at scale, because it is young and we will not pretend otherwise. The case is that there is no hidden second copy that can quietly fail to index while the document still appears in your library.
When Supermemory is the better fit
If you want one product that is both a personal-memory app and a developer memory API, and automatic capture appeals to you, Supermemory is a strong pick. If you are also building on top of a memory API, having the consumer app and the developer surface in one place is convenient. Check their current pricing across the developer and consumer tracks before you commit.
When people choose Hjarni instead
Two reasons come up most. First, EU hosting: Hjarni runs in Germany, while Supermemory is US-based. Second, the Markdown-file knowledge base: people who want notes they author and own, with folder-level AI instructions, tend to prefer writing to reading back what a tool captured. If your source of truth is a note you write, Hjarni fits. If it is context an engine gathers, Supermemory fits.