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Hjarni vs mem0

mem0 is a memory layer your agent's code writes to. Hjarni is a knowledge base a human writes in. Different audience, different job.

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Quick answer

mem0 is a developer memory layer: an SDK and API (plus the open-source OpenMemory MCP server) that your agent's code writes to and reads from automatically, so an application remembers across sessions. Hjarni is a Markdown knowledge base a person writes in, with a built-in MCP server that lets ChatGPT, Claude, and other clients read and update those notes. Pick mem0 if you are building an app or agent and need a programmatic memory backend. Pick Hjarni if you want notes you write and own that any AI assistant can read.

Hjarni mem0
Primary shape

mem0 is infrastructure your code calls. Hjarni is a notes app you write in.

Knowledge base a human writes Memory layer agents write to
MCP server

mem0 offers an official hosted cloud MCP server and OpenMemory, a self-hosted local MCP server (Docker, Postgres, Qdrant) with read and write tools. Hjarni's MCP server is built into the knowledge base.

Built-in, hosted Hosted cloud + self-hosted OpenMemory
Bring your own AI

Both are model-agnostic. You connect whichever AI you already use.

Who writes the content

mem0 extracts and stores memories from an agent's conversations. In Hjarni, a person writes the notes.

You do, in Markdown Your agent, automatically
Open source and self-host

mem0's core is open-source and you can self-host it. Hjarni is hosted SaaS only, with Markdown export anytime.

Apache-2.0 core, self-hostable
Editable notes UI

Hjarni is a notes editor a human writes in. mem0's OpenMemory dashboard browses the memories its agents wrote.

Full Markdown editor Dashboard browses memories
Folder-level AI instructions

Hjarni lets you set rules per folder an AI must follow. mem0 has no folder notion.

Built-in
Hosting region
EU (Germany) Check their docs
Free tier

Hjarni: 25 notes. mem0 cloud: reportedly around 10,000 memories and 1,000 retrievals. Check their current pricing.

Best fit

If a human is the author, Hjarni. If your agent is the author, mem0.

Notes a human writes Memory your code writes

A memory layer vs a notes app

mem0 calls itself a universal memory layer. It is plumbing: an SDK and API that extracts facts from an agent's conversations, stores them, and retrieves them later so the next session remembers what happened. The OpenMemory MCP server exposes that memory to clients like Claude Desktop, Cursor, and VS Code with read and write tools. The author of the content is your code, not a person.

Hjarni is a different product. You write notes in the app. They are plain Markdown, organized in folders, tagged, and linked. The built-in MCP server lets ChatGPT, Claude, and other clients search, read, and update them. The author is you.

Who writes, and who reads

With mem0, the agent writes and the agent reads. You wire it into an application, and it accumulates memories automatically as conversations happen. The OpenMemory dashboard lets you browse what was stored, but it is a window onto agent-written memory, not a place a person sits down to write.

With Hjarni, a human writes and any connected AI reads. You decide what goes in. The note you write is the one your assistant sees next, with no extraction step in between.

mem0 is the memory your agents build for themselves. Hjarni is the knowledge a person writes down on purpose.

When mem0 is the better fit

If you are a developer building an agent or application and you need a programmatic memory backend your code writes to, mem0 is built for exactly that. The core is open-source and Apache-2.0, you can self-host it, and there is a managed cloud with a free tier (reportedly around 10,000 memories and 1,000 retrievals; check their current pricing). That is the right tool when memory is a feature of software you are shipping.

When people choose Hjarni instead

The switch happens when the job is "I want to write notes my AI can read", not "I am building an app that needs to remember". Hjarni is the knowledge base and the MCP server in one hosted product. There is no SDK to wire in, no extraction pipeline, no vector store to run. You write a note, your AI reads it.

Folder-level AI instructions also matter here. Tell Claude to keep one folder formal and skip another when answering. mem0 has no folder notion because its unit is an extracted memory, not a document a person organizes.

When to use mem0

  • You are a developer building an agent or app
  • You need a programmatic memory backend your code writes to
  • You want open-source you can self-host

When to use Hjarni

  • You want a knowledge base a human writes in, not a backend
  • You want plain Markdown you own and can export anytime
  • You want folder-level AI instructions across ChatGPT, Claude, and Cursor

mem0 remembers for your agents. Hjarni remembers what you wrote down.

Common questions

Common questions

What is mem0?

A universal memory layer for AI: an SDK and API (plus the open-source OpenMemory MCP server) that extracts, stores, and retrieves memories so an agent or app remembers across sessions. The author of the content is your code, not a person.

Is mem0 a notes app like Hjarni?

No. mem0 is developer infrastructure a program writes to automatically. Its OpenMemory dashboard browses agent-written memories rather than being a place a person sits down to write. Hjarni is a Markdown knowledge base a human writes in, with the MCP server built in.

When should I pick mem0 over Hjarni?

Pick mem0 when you are building an application or agent and need a programmatic memory backend your code writes to. Its core is open-source (Apache-2.0) and self-hostable, with a managed cloud too. Pick Hjarni when you want notes a human writes and owns that any AI can read.

Does mem0 work with Claude and ChatGPT?

Yes. mem0 is model-agnostic, and OpenMemory is a local MCP server that works with clients like Claude Desktop, Cursor, and VS Code. Hjarni's MCP server is hosted and built in, so remote clients reach your notes from any device.

Can I use both mem0 and Hjarni?

Yes. Some teams use mem0 as the memory layer inside an app they are building and Hjarni as the place people write decisions and runbooks. An MCP client can connect to both servers in parallel.

Give your AI a memory

Write once. You both remember.

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