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liuboacean/agent-comm-hub

by Various

Multi-agent real-time communication & task scheduling infrastructure based on MCP + SSE

MCP

liuboacean/agent-comm-hub

Added 7 June 2026

#agent #communication #evolution-engine #infrastructure #mcp #memory-sharing #multi-agent #rbac

Overview

A Python-based infrastructure for real-time communication and task scheduling among multiple AI agents, built on the Model Context Protocol (MCP) and Server-Sent Events (SSE). It provides a hub that coordinates agent interactions and message routing.

Best for

Best for
Developers experimenting with multi-agent coordination using MCP and SSE in Python

Use cases

  • Orchestrating multi-agent workflows with real-time message passing
  • Scheduling and dispatching tasks across distributed agent instances
  • Building a central communication bus for MCP-compatible agents

How to use

Install

docker run -d -p 3100:3100 --name ach ghcr.io/liuboacean/agent-comm-hub

Tools exposed

  • docker
  • node

Example client config

[object Object]

Notes

A Python-based infrastructure for real-time communication and task scheduling among multiple AI agents, built on the Model Context Protocol (MCP) and Server-Sent Events (SSE). It provides a hub that coordinates agent interactions and message routing.

1 stars on GitHub. Last updated 2026-05-29. Licensed MIT.

Use cases

  • Orchestrating multi-agent workflows with real-time message passing
  • Scheduling and dispatching tasks across distributed agent instances
  • Building a central communication bus for MCP-compatible agents

Pros

  • Leverages standard protocols (MCP, SSE) for interoperability
  • Lightweight Python implementation suitable for prototyping
  • Enables real-time coordination without polling

Cons

  • Very early stage with only 1 star and minimal community adoption
  • Limited documentation and examples beyond the repository
  • Unclear production readiness or scalability characteristics

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Leverages standard protocols (MCP, SSE) for interoperability
  • Lightweight Python implementation suitable for prototyping
  • Enables real-time coordination without polling

Cons

  • Very early stage with only 1 star and minimal community adoption
  • Limited documentation and examples beyond the repository
  • Unclear production readiness or scalability characteristics

Open-source & AI alternatives

Swap-in tools that solve the same job. Weigh the trade-offs before you commit.

Pairs with

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