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

The Agent & Tool Arbitration Protocol

W3C Semantic Agent Communication Community Group

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

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

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

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.

🧠 Claude Collective Intelligence: AI Agent Swarm Framework | Transform isolated Claude Code sessions into collaborative AI collectives | 8 mechanisms: Brainstorming, Voting, Rewards, Penalties, Mentorship, Battle, Leaderboard, Orchestrator | MCP Server

Environment with Multiple Autonomous Agents

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.

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.

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

🧠 Accelerate AI collaboration with Claude's agent swarm framework, leveraging message queues for enhanced brainstorming, voting, and mentorship.

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.