Mnemoverse vs Supermemory
Mnemoverse vs Supermemory in 2026
Memory that learns which facts help from outcome feedback, next to a context platform built around ingesting your documents. Compared honestly.
Mnemoverse vs Supermemory: which memory should an AI agent use in 2026?
Short answer: these two are closer neighbors than most pairs on this hub, and both reach the same editors over MCP, so the choice is not about coverage. Choose Supermemory when the job is turning your documents, mail and drives into one queryable memory graph for an app you are building. Choose Mnemoverse when you want the memory itself to get smarter with use: importance scored on write, associations that strengthen with co-recall, and outcome feedback that re-ranks what comes back. Free tier: 1,000 queries/day, no credit card.
Side by side
Where they differ
| Mnemoverse | Supermemory | |
|---|---|---|
| What it is | A persistent memory API: one memory, reachable from every supported tool | A context-engineering platform: a memory graph over your ingested documents and sources |
| Cross-tool reach | Claude Code, Cursor, VS Code, Python, REST with one key or OAuth; ChatGPT via a Custom GPT action | Hosted MCP server (OAuth) for Claude Desktop, Cursor, Windsurf, VS Code and Claude Code, plus editor plugins; TypeScript and Python SDKs and a REST API |
| Memory organization | Concept associations that strengthen with co-recall (Hebbian, Rescorla-Wagner) | A custom vector graph engine with ontology-aware edges |
| How memory changes over time | Reporting outcomes re-ranks what comes back next | Facts are updated and contradictions resolved automatically; time-bound facts expire |
| Ingestion | You (or your agent) write memories explicitly | Extractors for PDFs, images, video and code; connectors for Google Drive, Gmail, Notion, OneDrive and GitHub |
| User modeling | Importance and valence per memory | User profiles extracted from behavior (intent, preferences, context) |
| Free to start | 1,000 queries/day, 10,000 atoms, no credit card; Pro $29/mo | Free tier with usage credit included; Pro $19/mo, Max $100/mo, Scale $399/mo |
| Self-hosting | Managed service only | Prebuilt single-binary local server (macOS, Linux, Windows) that can run offline; connectors and their hosted MCP stay cloud-only |
| Openness and research | MCP server and Python SDK are MIT; SLoD framework on arXiv (2603.08965), peer-reviewed and accepted at the GRAAI workshop (IEEE WCCI 2026) | Repository is MIT and holds the SDKs, MCP server and app; the memory engine ships as a prebuilt binary rather than source |
Both are real memory systems, and both maintain themselves over time. Supermemory updates facts, resolves contradictions and expires time-bound ones automatically. Mnemoverse changes what surfaces based on what actually worked: you report an outcome, and recall re-ranks.
Honest take
When to choose which
Choose Supermemory when…
- You need to ingest documents, mail and drives into one queryable memory graph for your own application.
- Multimodal extraction matters: PDFs, images, video and code, with connectors to the sources you already use.
- You want a free local mode you can run offline on one machine, accepting that the engine ships as a prebuilt binary.
Choose Mnemoverse when…
- You want the AI tools you already use to share one memory, with nothing to build or host.
- You want recall that improves as you work — importance on write, associations that strengthen with co-recall, outcome feedback that re-ranks results.
- You want published research (SLoD on arXiv) behind the mechanism.
Questions
Mnemoverse vs Supermemory FAQ
Supermemory's repository is MIT-licensed and contains the SDKs, the MCP server and the app. The memory engine is distributed as a prebuilt binary for local use rather than as source. Mnemoverse is similar in shape: the MCP server and Python SDK are open source (MIT), the memory engine is hosted.
Yes. Supermemory is strong at ingesting your documents and sources into a memory graph for an app you are building. Mnemoverse is strong at giving the AI tools you already use one shared memory that learns from outcomes. They solve different halves of the problem.
Supermemory retrieves from a vector graph over ingested content using hybrid search that combines document retrieval and memory in one query. Mnemoverse scores importance when a memory is written, strengthens associations between concepts recalled together, and re-ranks recall from outcome feedback, so results shift with use rather than staying fixed.
Free tier: 1,000 queries/day and 10,000 atoms, no credit card. Add one API key (or connect over OAuth) to Claude Code, Cursor, or VS Code, or reach it from ChatGPT via a Custom GPT action, and write your first memory.
One memory. Every AI tool.
Try the free tier — 1,000 queries a day, 10,000 memories, no credit card — and see the difference for your own agents.