Paid tool

supermemory™

Universal memory API for personalizing LLMs and building AI retrieval infrastructure easily.

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Intro

What is supermemory™?

supermemory™ is the universal memory API for the AI era designed to eliminate the need for building retrieval infrastructure from scratch. Acting as an advanced super memory layer, it allows developers to easily personalize LLMs for their users. By integrating the supermemory api, developers can bypass the tedious challenges of setting up vector databases, choosing embedding models, and handling complex format parsing. It essentially acts as a supermemory mcp (Model Context Protocol) and data hub that provides an unlimited context API, seamlessly connecting applications and data sources to supercharge agentic apps.

supermemory™ at a glance
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Pricing

supermemory™ Pricing Plans

Compare supermemory™ free options, supermemory™ paid pricing plans, and usage notes before you choose the best way to use this AI tool in 2026.

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Pricing updated:Jun 11, 2026

Features

supermemory™ AI Features

Universal memory API to add and search memories programmaticallyUnlimited context API via a simple OpenAI base URL switchModel-agnostic interoperability working with any LLM provider, AI SDK, or LangchainSeamless application sync connecting natively to external tools like Google Drive, OneDrive, and NotionEnterprise-grade performance with sub-400ms low-latency retrieval at scaleMulti-modal data support handling websites, PDFs, images, and video/audio files
Pros & Cons

supermemory™ Pros and Cons

Pros

  • Extremely simple integration requiring only a few lines of code
  • Model-agnostic infrastructure avoiding vendor lock-in
  • High performance with sub-400ms low latency and strong benchmark metrics
  • Flexible deployment options including cloud, on-prem, or directly on-device

Limitations

  • The developer platform currently requires an email, Google, or GitHub login to access granular usage metrics
  • Advanced features like vision model handling for images or transcription for audio/video can increase external reliance

supermemory™ FAQ

It fixes the traditional pain points of building RAG from scratch, such as expensive vector databases, confusing embedding performance trade-offs, broken document formatting layouts, and data source synchronization failures.