Mem0 vs Supermemory vs Hjarni: AI Memory Compared (2026)

Mem0 provides memory infrastructure for applications and coding agents, with managed and self-hosted options. Supermemory combines a memory API with hosted MCP access for personal and shared context. Hjarni is a Markdown knowledge base that you and connected assistants maintain together. Its notes remain available across chats, but the assistant still needs to retrieve them.

Start with the work you need memory to do. Building automatic fact extraction into an AI product? Compare Mem0 and Supermemory on your own conversations and queries. Maintaining project decisions and reference notes that ChatGPT and Claude can read and update? Hjarni is built for that workflow. Hosted MCP brings these products into overlapping territory, so the difference is how you create, organise and maintain context.

One disambiguation first: Mem0 is not Mem. Mem is an AI note app, and we compare it separately in Hjarni vs Mem.

Mem0 vs Supermemory vs Hjarni: side by side

	Mem0	Supermemory	Hjarni
Category	Application memory and agent integrations	Memory API and hosted MCP	Knowledge base with MCP and REST API
Memory model	Extracted facts or raw content; optional graph	Source documents plus extracted memories	Markdown notes, folders, tags
Created by	Extraction by default; raw storage available	Source ingestion or deliberate saves	You or your connected assistant
Reading and editing	Inspect records; update through API/MCP	Read sources and memories; review save drafts; update documents through API	Edit notes; inspect attributed history; restore versions
Instructions	Extraction guidance configured through SDK/API	Organisation and namespace context through SDK/API	Folder and team guidance supplied to assistants
MCP support	Hosted server; coding-agent integrations	Hosted OAuth server; personal and shared spaces	Built-in hosted server; Claude and ChatGPT directory setup
Setup	Platform account and supported client; browser authorisation or API key	Account, OAuth and space selection	Account sign-in and access consent in supported clients
Free tier	Platform: 10,000 add and 1,000 retrieval requests/month	API: $5 in monthly credits	25 personal notes; full MCP/API access
Paid from	Platform Starter: $19/mo	API Pro: $19/mo with $20 in monthly credits	Pro: $12/mo

USD monthly prices and allowances checked on 8 October 2026 against Mem0 pricing, Supermemory pricing and Hjarni pricing. API credits and request allowances are not retained-memory limits or a guarantee of separate MCP allowances. Your Claude or ChatGPT subscription is separate from Hjarni. Host plans and supported clients also affect access.

What Mem0 is

Mem0 provides memory infrastructure for AI applications. Your application sends content, and the default flow extracts and deduplicates facts for later retrieval. It also supports raw-content storage without inference and updates to memory text and metadata.

Mem0 offers managed Platform and open-source options. Its current MCP guide describes a hosted HTTPS server, browser authorisation, a Claude Desktop custom connector and coding-client setup. Its integration docs also cover coding agents such as Claude Code, Cursor and Codex.

Pick Mem0 when you need an application memory API, coding-agent integrations or graph memory. On the managed Platform, graph memory is listed on Pro and Enterprise. The checked monthly Platform prices are Starter at $19 and Pro at $249.

The trade-off: extracted records are a different workflow from maintaining project documents in folders. You can correct records, but you still need to decide how your application stores, retrieves and uses them, and whether its request allowances fit your workload.

What Supermemory is

Supermemory combines source ingestion, learned memories and retrieval through an API. Its pricing page advertises 187ms median server time for search and traversal. That is a vendor metric, not an end-to-end guarantee or a measured comparison with Mem0. If latency matters to your product, test your own queries, content and network path.

Its API pricing uses credits: Free includes $5 each month, and the $19 Pro plan includes $20 in monthly credits at the checked date. Estimate ingestion, search and other operations together when comparing costs.

Supermemory also runs a hosted MCP service. You authorise access over OAuth, choose personal or shared spaces, and can read source documents as well as inspect extracted memories. Its guided save opens a draft you can edit before submitting. That is deliberate, reviewable saving; it is distinct from changing an existing record. Source-document updates are documented through the API.

Pick Supermemory when you want to combine source ingestion with a memory API, evaluate credit-based pricing, or connect assistants to personal and shared source context over hosted MCP.

The trade-off: you need to understand how source documents and extracted memories relate, check what extraction kept, and budget for your usage. A readable source does not by itself guarantee that the assistant retrieves the right context.

What Hjarni is

Hjarni is a Markdown knowledge base that ChatGPT and Claude can read and update. You organise notes with folders and tags. Connected assistants can search, read, create and update notes through the built-in MCP server. You can review attributed note history and restore an earlier version.

Folders and teams carry AI instructions, giving connected assistants guidance on formatting, tags and where notes belong. These instructions help guide tool use; they do not guarantee that an assistant follows them or retrieves a note in every chat.

Pick Hjarni when you want maintained project decisions, instructions and reference notes to serve the assistants you use day to day. Follow the Claude or ChatGPT setup guide, sign in and authorise access. Check the guide for the host's supported plans and clients.

For example, ask your assistant to save a note titled "Website project decisions" with your stack and deployment choices. Open it in Hjarni to check the result. In a new chat, say "Check Hjarni for Website project decisions before we continue." When a decision changes, ask it to update the note and review the edit in its history. See how to make your assistant search your notes if retrieval is inconsistent.

The trade-off: Hjarni does not automatically extract user facts from every conversation. You or your assistant maintain the notes, and the assistant must retrieve them to use them. Hjarni also exposes a REST API, but if you need an extraction backend inside your own AI product, Mem0 or Supermemory is the closer fit.

The practical difference: how you maintain context

Extraction and written notes are workflows, not an absolute divide between these products. Mem0 can store raw content and update records. Supermemory can expose source documents and let you review a save draft. Hjarni centres the workflow on notes that you and your assistants maintain together.

A project note might say "Rails 8.1, PostgreSQL 18, deployed on Hetzner, no React" and explain why those decisions were made. When the stack changes, update the note. You and your assistant can read the same decision and correct it as the project changes.

Choose the workflow that fits who maintains the context. An application can extract facts from conversations; a person or team can maintain shared project documents. Both still need useful retrieval and checks when the saved context changes.

When to pick each

• Pick Mem0 when you need an application memory API, coding-agent integrations or graph memory on a suitable plan.
• Pick Supermemory when you want source ingestion and extracted memory together, or hosted MCP with personal and shared spaces. Test latency and credit costs against your workload.
• Pick Hjarni when you want readable project knowledge that ChatGPT, Claude and your team can search and update, with attributed note history and restoration. Free to start, no credit card required. Ask the assistant to check the saved context when you resume work.

For the wider field beyond these three, see the best MCP memory servers in 2026. For approaches that do not involve a server at all, see the best ways to give your AI memory.