Papr vs Supermemory
A side-by-side comparison of Papr and Supermemory, two Memory tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Papr | Supermemory |
|---|---|---|
| Category | Memory | Memory |
| Pricing | FREEMIUM | FREEMIUM |
| License | Open core | Open core |
| Deployment | Hybrid | Hybrid |
| Platforms (differs) | Web, API | API, Web |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | Papr | Supermemory |
| Capabilities (differs) |
|
|
The honest brief
Papr
Predictive memory graph that surfaces anticipated context to agents, rather than only returning similarity-matched chunks like a vector store.
- Open-source AGPL-3.0 core
- TypeScript and Python SDKs
- Managed cloud or self-hostable
- Automatic chat-memory compression
- Newer, smaller ecosystem
- Memory-only scope
- AGPL may deter some commercial use
Supermemory
MIT-licensed memory engine you self-host or call as a managed API — one recall endpoint across any model.
- MIT-licensed, self-host or managed
- Single recall API across any model
- Connectors: Drive, Gmail, Notion
- Ships MCP server and SDKs
- Younger project, evolving API
- Smaller track record than peers
- Self-hosting needs infra work
When to pick which
Both cover Agent memory, Vector search, and RAG pipeline.
Pick Papr if you need Knowledge graph.
- Knowledge graph (primary capability)
Pick Supermemory if you need MCP server and Document parsing (structured).
- MCP server (secondary capability)
- Document parsing (structured) (secondary capability)