Introduction
Supermemory is a high-performance, scalable memory engine and companion app that provides a Memory API for efficiently storing, indexing, and retrieving structured and unstructured content. The project combines backend services and frontend demos to let users ingest content (webpages, PDFs, notes) as memories and interact through natural-language chat with retrieved context, making it well suited for long-term memory management and RAG scenarios.
Key Features
- Ingest content from URLs, files, and text, with indexing and vectorization for efficient retrieval.
- High-throughput Memory API optimized for low-latency retrieval and concurrent access.
- Integrations and connectors for common AI tools (including MCP), plus demo applications for quick evaluation.
Use Cases
- Building chat assistants or customer support systems with persistent memory to improve dialogue continuity and context awareness.
- Powering RAG Q&A and knowledge discovery over large document collections.
- Serving as a memory or knowledge layer in production systems that require low-latency, large-scale vector retrieval.
Technical Highlights
- Implemented with TypeScript and modern frontend frameworks; includes backend service examples and deployment guides.
- Designed for deployment flexibility, supporting Cloudflare Pages/Workers and multiple storage backends.
- Open-source (MIT), active community, and comprehensive docs and contribution guidelines for extension and integration.