supermemory™

A universal memory API designed for AI, personalized LLM, providing unlimited context and simplified retrieval.

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Introduction

Universal memory API for AI, personalizes LLMs, provides unlimited context, and simplifies retrieval.

What is supermemory™?

Super Memory is a universal memory API designed for the era of artificial intelligence to help developers stop building retrieval from scratch and personalize large language models (LLMs) for their users. It provides an unlimited context API that automatically provides long-term context in conversations. Built for publishing developers, it processes at any scale with enterprise-grade performance, enables seamless integration across teams and tools, and allows users to own their data while maintaining compliance and providing secure and controllable deployment options (cloud, private, on-device). It is model-agnostic, able to work with any LLM provider, and delivers sub-400ms latency based on optimal precision and recall.

How to use supermemory™?

Super Memory can be used by integrating its API or SDK into your application. To add a memory, send a POST request to `https://api.supermemory.ai/v3/memories` with content (text, URL, or PDF) and optional metadata. To search the memory, use query `q` to send a GET request to the same endpoint. To connect to applications such as OneDrive, use a specific connection endpoint (for example, `https://api.supermemory.ai/v3/connections/onedrive`). For OpenAI integration, simply change your OpenAI client's `baseUrl` to `https://api.supermemory.ai/v3/https://api.openai.com/v1/` to get automatic long-term context. The SDK is available for Python (`pip install supermemory`) and JavaScript (`npm install supermemory`).

core features of supermemory™

Universal memory API designed for the era of artificial intelligence
LLM’s unlimited context API
Low-latency retrieval for enterprise-class performance with billions of data points
Seamless integration across teams and tools (Notion, Google Drive, CRM, etc.)
Secure design, fully controllable deployment (cloud, private, local device)
Model-agnostic API (compatible with any LLM provider)
Achieve sub-400ms latency at scale
Excellent performance (strong precision and recall)
Compatible with AI SDK, Langchain, etc.
Language-agnostic SDK (Python, JavaScript)

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Updated：2026-11-07