Hivemind: Shared Memory for AI Agents

Introduction

As artificial intelligence advances at breakneck speed, coordinating multiple AI assistants has become the norm—yet the problem of information silos continues to frustrate developers. Hivemind was built to solve this: it is a shared memory system designed specifically for AI agents. With a single command, you can give mainstream AI assistants like Claude Code, OpenClaw, Codex, Cursor, Hermes, and pi a unified, persistent memory space. After installing via npm, Hivemind automatically detects every assistant on your machine, allowing them to share context and avoid redundant work, dramatically improving overall efficiency.

Key Features

• Cross-assistant memory sharing: all connected AI agents can read from and write to the same persistent memory pool, enabling seamless information flow.
• Automatic detection and integration: after installation, Hivemind automatically identifies locally deployed assistants such as Claude Code, OpenClaw, Codex, Cursor, Hermes, and pi—no manual configuration required.
• Persistent storage: memory data is stored locally, so even after restarts or project switches, historical context is never lost.
• Simple command-line operation: install globally via npm and start syncing all agents with a single command.
• Real-time synchronization: when one assistant updates its memory, other assistants immediately become aware of and can leverage the new information.

Highlights

• Zero learning curve: install and go—no need to modify existing workflows; Hivemind runs quietly in the background.
• Breaks down tool barriers: no matter which AI coding assistant you use, everyone collaborates on the same knowledge base.
• Local-first design: all data stays on your machine, ensuring privacy and security.
• Lightweight and efficient: consumes minimal resources and does not impact the performance of other applications.
• Open-source and extensible: supports custom plugins, allowing you to connect additional AI tools or data sources.

Who It's For

Hivemind is built for AI developers and researchers who need multiple models to collaborate on complex tasks while keeping context coherent; software engineers who use several coding assistants like Claude Code or Cursor daily and want to cut down on redundant input; technical team leads looking to unify their team's AI tool knowledge base for better collaboration; AI tool enthusiasts who love experimenting with new assistants but don't want to deal with fragmented memory; and automation workflow builders who need different agents to hand off tasks in end-to-end pipelines.