Aurahub

Common Context MCP – Shared Memory and Coordination for AI Agents Common Context MCP is an open-source Model Context Protocol (MCP) server designed to solve one of the biggest challenges in multi-agent AI development: context fragmentation. AI agents often work independently, losing important decisions, task history, progress, and knowledge between sessions. Common Context MCP provides a shared context layer that enables AI agents to preserve, retrieve, and coordinate information across workflows. Through a collection of MCP tools, agents can: - Share Context: Access information and knowledge recorded by other agents. - Persistent Memory: Store and retrieve important project information. - Checkpoint & Recovery: Save progress and resume unfinished tasks. - Decision Tracking: Preserve technical decisions and their reasoning. - Failure Tracking: Record previous failures to avoid repeating mistakes. - Task Coordination: Coordinate work and manage file ownership. By providing a common context infrastructure, Common Context MCP helps developers build more consistent, collaborative, and reliable AI agent workflows. Our vision: One Context. Every AI Agent.