Supermemory is an open source memory API for AI applications that stores, indexes, and retrieves user-specific context so that LLMs can deliver personalized responses without building a custom RAG pipeline from scratch.
The Problem
LLMs have no memory between conversations by default. Building long-term memory for AI applications requires designing a storage layer, an embedding pipeline, a vector search retrieval system, and a context injection mechanism. Doing this correctly for each new application is weeks of engineering work, and doing it poorly produces retrieval that is slow, imprecise, or returns irrelevant context.
How Supermemory Solves It
Supermemory provides a REST API that accepts memory entries (text, documents, web content), embeds them, and stores them in a vector database. When an LLM needs context, the application queries Supermemory with the current user ID and topic, and Supermemory returns the most relevant memories ranked by semantic similarity. Apache-2.0 licensed; self-host via Docker.
Key Features
- Memory ingestion API: add text, URLs, files, and browser extension bookmarks as memory entries
- Semantic retrieval: query memories by user and topic with vector similarity ranking
- Multi-user support: isolate memory spaces per user for multi-tenant AI applications
- Browser extension for adding web pages to memory without a direct API call
- Compatible with any LLM or framework: OpenAI, Anthropic, LangChain, or direct REST calls
- Apache-2.0 licensed; self-host via Docker
Who It's For
Supermemory is best for developers building personal AI assistants, customer-facing AI agents, or knowledge management applications who want a pre-built memory layer rather than assembling embedding pipelines and vector retrieval from scratch.
Compared to Mem0
Unlike Mem0, Supermemory is fully open source under Apache-2.0 and designed for self-hosting with no cloud dependency. Mem0 offers a managed service with additional memory management features and integrations; Supermemory gives full control over memory storage and retrieval at no variable cost.
