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Universal Memory MCP

Universal Memory MCP

Your memories, in every LLM you use.

Website supermemory.ai
Overview

What it is

You've been collecting bookmarks on the internet for all this while- it's finally time to use them. Supermemory is a hub for organizing and utilizing saved information, with a search engine, writing assistant, canvas and more.

Intent

I need it when

Build AI agents that maintain persistent, evolving user context across sessions

Supermemory provides a knowledge graph that learns and updates user facts in real-time, creating coherent user profiles that persist across conversations. Agents remember user preferences, behavior, and identity without restarting from zero each session, enabling personalized and consistent interactions.

Ingest and sync data from multiple sources without manual ETL

Supermemory includes built-in connectors for Slack, Notion, Drive, Gmail, GitHub, S3, and custom sources with automatic real-time syncing. The platform handles extraction from PDFs, images, audio, and raw files automatically, eliminating the need for separate extraction providers or manual data imports.

Deploy AI infrastructure with enterprise security and compliance requirements

Supermemory offers SOC 2 Type II certification, GDPR compliance, HIPAA BAA support, and flexible deployment options: on-premises, in customer VPC (AWS/GCP/Azure), or fully air-gapped. Enterprise plans include dedicated account managers, uptime SLAs, and custom contracts with data ownership guarantees.

Unify memory, RAG, and user profiles in a single queryable system

Supermemory consolidates memory graphs, user profiles, and document retrieval into one API and unified graph structure. Developers query a single entity model instead of managing three separate systems, reducing complexity and enabling coherent context traversal across all data types.

Reduce latency and token costs in production AI applications

Supermemory achieves sub-300ms retrieval latency (10× faster than Mem0, 25× faster than Zep) and deduplicates content at the token level, providing a 100% prompt-cache discount. Production agents using memory loops consume 40-50% fewer tokens than RAG-only approaches while maintaining faster response times.

Drop

Not a fit when

  • User needs simple vector database without memory graph or entity resolution capabilities
  • Organization requires fully offline deployment without any cloud connectivity or managed instance option
  • Use case involves only static document retrieval without user profiling or evolving context needs
  • Budget is extremely constrained and cannot accommodate any monthly subscription or usage-based billing
  • Application requires sub-millisecond latency below Supermemory's ~300ms p50 retrieval time
  • Team needs a solution without TypeScript/Python SDK support or prefers different language ecosystems
Commercials

Pricing

USD0 - USD399 / monthly View pricing