Agent Comm Hub

This Skill addresses the lack of a standardized communication mechanism between multi-agent systems. In practical development, when you need two or more independent AI agents to collaborate—such as for message passing, task assignment, or context sharing—you often have to manually write complex network layers and consistency protocols, which is costly to develop and difficult to maintain. Agent Comm Hub provides an out-of-the-box MCP protocol communication layer, allowing agents to interact through standard interfaces like microservices.

Usage is straightforward: simply start the Hub server locally (in stdio or HTTP-SSE mode) and have each AI Agent connect via an MCP client. You can then use natural language commands to send messages, assign tasks, store shared memory, check online status, and more. The Hub comes with 58 built-in MCP tools covering identity registration, messaging, task orchestration, file transfer, context caching, memory management, evolution engine, and other functions, and includes a web management panel—all without writing any code.

It is well-suited for teams and individuals who need to coordinate multiple AI agents, especially those already using AI Agents like Claude, WorkBuddy, or Hermes that support the MCP protocol and want to enable real-time bidirectional communication, task pipeline orchestration, or shared memory between agents. Whether building complex AI workflows or setting up a multi-agent collaboration platform, it significantly reduces integration costs.

We recommend using this Hub as a unified communication middleware when building multi-agent systems. Note that it only supports stdio and HTTP-SSE modes, not WebSocket; message persistence relies on SQLite WAL, so performance should be monitored in high-concurrency scenarios. Additionally, agents must send a heartbeat every 30 seconds to maintain online status, and will be automatically marked offline after 90 seconds without a heartbeat.