Supermemory

Supermemory is a context infrastructure and memory API that provides long-term memory for AI agents to recall user information.

Supermemory functions as a context infrastructure and memory API for AI agents. It enables agents to maintain long-term memory of individual users. Users initiate the process by pasting a prompt into their coding agent to connect memory to their project. The system includes modules for browsing memory, retrieval, user profiles, and connectors. It is designed to support continual learning for AI agents. The platform offers multiple implementation paths to fit different application and team requirements.

Supermemory at a glance

Best for: Software engineer, Founder
Runs on: Web
Pricing: Freemium
Released: February 2024
Category: AI agent tool
Website: supermemory.ai

Key features

Memory storage for AI agents
Retrieval system
User profile management
Connectors for external data
Memory browsing interface

Use it for

Providing long-term memory to coding agents
Implementing continual learning for AI agents
Managing user context for AI applications

Companion to

Tools whose articles name Supermemory as a companion, each with its job for them.

OpenClaw — Supermemory: Long-term memory

Alternatives to Supermemory

memU — It gives every connected agent a shared and inspectable memory layer.
SuperLocalMemory — It refuses to guess or bluff when information is missing from its memory store.
AgentMemory — It runs locally with zero external databases and achieves high retrieval recall.
Mem0 — It provides drop-in persistent memory for AI agents without changing pipelines.
LongMemory — Provides immutable, temporal, and governed recall instead of simple vector retrieval.
ReMe — It enables local-first, file-native long-term memory sharing across multiple AI agents.
Maximem — It delivers fast retrieval and structured memory across frameworks.
Agentmemoryrepo — Enables agents to navigate memories like a wiki and share knowledge across sessions.
Graphmemory — Provides bitemporal facts and a six-variable importance and decay model.
Memori — Reduces LLM token usage and spend by over 97% with targeted recall.
MemOS — It delivers ultra-persistent memory, hybrid-retrieval, and token savings.
Memmy — Shares one persistent memory foundation across your different AI tools.

All Supermemory alternatives