Bindu: Turn any AI agent into a living microservice - interoperable, observable, composable.

Experimental framework for multi-agent coordination and collaborative learning architectures. Research platform exploring agent-based learning systems, coordination protocols, and emergent behavior analysis. Progressive tutorials from reactive agents to AI-driven distributed systems.

Open Agent Communication Network - Fork of acn on fetchai/agents-aea

Stock Market modeled as a Multi-Agent System

🐇 The 'RabbitHole' framework provides the tools for asynchronous A2A communication and task management. 📡🐇 ✨ Build powerful AI agents that communicate and collaborate.

Using Java Agent Development Environment

W3C Semantic Agent Communication Community Group

The Agent & Tool Arbitration Protocol

A production-ready multi-agent system showcasing Agent Communication Protocol (ACP) and Model Context Protocol (MCP) capabilities through a collaborative research workflow.

Environment with Multiple Autonomous Agents

Agent-Creator is a framework for building and experimenting with multi-agent systems powered by Microsoft’s AutoGen. The project demonstrates how autonomous AI agents can collaborate, communicate, and solve tasks in a simulated environment. The main file world.py acts as the orchestrator, defining agent behaviors, interactions, and workflows.

MAPLE - Production-ready multi agent communication protocol with integrated resource management, type-safe error handling, secure link identification, and distributed state synchronization.

Framework for building and managing multi-agent systems with Model Context Protocol (MCP) and LangGraph support. Features a modern React UI, JWT-secured agent communication, and dynamic LLM provider integration (OpenAI, Azure, Google). Easily create, configure, and monitor agents that connect to external tools—all from a single interface.

🤖 Compare AI agent frameworks effortlessly with a standardized multi-agent workflow system, using Docker for easy setup and consistent testing.

Enterprise-grade Node.js authentication client for Traylinx Sentinel API with full A2A Protocol support

Exploring Google’s A2A AI System: Agent-to-Agent Workflows, Routing, and Conversation History

This framework enables secure, decentralized communication between AI agents using blockchain technology and smart contracts. It ensures the integrity, confidentiality, and verifiability of interactions through cryptographic identities, end-to-end encryption, and immutable audit trails.

Enterprise-grade Python authentication client for Traylinx Sentinel API with full A2A Protocol support

Core network infrastructure for agent communication

🔐 Streamline A2A authentication with Traylinx Auth Client for Node.js; enjoy secure token management and seamless integration for enterprise-level security.