Supermemory Freemium

An API-first memory layer that gives AI apps long-term recall

Supermemory is a hosted memory API that lets AI apps and agents store and recall user context across sessions. You add one API call, and your chatbot stops forgetting everything after a refresh.

What is Supermemory?

Supermemory is a startup-backed memory layer built by Dhravya Shah’s team. Instead of running your own vector database and chunking pipeline, you POST text to /v3/memories and it handles embeddings, deduplication and retrieval for you. It also ships an MCP server, so tools like Cursor or Claude Desktop can read the same memory store.

The pitch is narrow but real: LLMs are stateless, and most teams waste weeks rebuilding memory. Supermemory sells that missing piece as infrastructure.

Supermemory features that actually matter

  • Automatic memory extraction: you send raw conversation text, and it decides what is worth keeping.
  • Semantic search: query with natural language and get ranked memory chunks with relevance scores.
  • MCP server: drop the connection URL into Cursor, Claude or any MCP client and it works without custom code.
  • Forgetting controls: memories carry expiry and can be deleted per user, which matters for GDPR requests.
  • SDKs: official TypeScript and Python clients, plus a plain REST API.

Product highlights

The onboarding is fast. You get a key, paste ten lines of code, and your app has memory in under fifteen minutes. The MCP path is even shorter — no code at all.

Because it is hosted, you skip the classic headache of index drift and re-embedding when you switch models. The trade-off is the usual one for managed infra: your users’ memory lives on someone else’s servers.

Who should use Supermemory

Good fit for indie devs and small teams shipping a consumer chatbot, a personal assistant, or a Cursor-style coding helper that needs to remember preferences. Poor fit if you are in a regulated industry with strict data-residency rules, or if you already run your own vector stack and only need a thin wrapper.

Common use cases

  • Chatbots that remember a returning user’s name, tone and past issues.
  • Coding agents that keep project conventions between sessions.
  • Support copilots that surface a customer’s earlier tickets automatically.
  • Personal AI journals that link today’s notes to last month’s.
  • Multi-agent systems sharing one memory namespace.

Pricing and limits

There is a free tier aimed at testing, then paid plans that scale with stored memories; the entry paid tier is around $19/month. Heavy production volumes get custom pricing. Check the site for current caps on memory count and API calls per month.

Quick Summary

  • Supermemory is a managed memory API for AI apps, not a full RAG platform.
  • Free tier exists; paid plans start near $19/month.
  • Works via REST, TypeScript/Python SDKs, and an MCP server.
  • Best for small teams that don’t want to build memory plumbing themselves.
  • Main caveat: your users’ data is stored on Supermemory’s infrastructure.