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

AI Agent Orchestrator with Skills System - Give Claude Code agents superpowers: memory search, code graph queries, agent-to-agent messaging. Manage Claude, Aider, Cursor from one dashboard. Multi-machine support.

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

Independent agent to agent communication

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.

The Agent & Tool Arbitration Protocol

Using Java Agent Development Environment

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.

🧠 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

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.

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.

Environment with Multiple Autonomous Agents

Multi-agent AI system for autonomous task management and focus session orchestration. Built with LangGraph and OpenAI API, implements agent communication protocols and collaborative decision-making for intelligent task planning and execution.

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.

Core network infrastructure for agent communication