Bindu turns your agent into a living server , the dot (Bindu) in the Internet of Agents.🌻🚀✨

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

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

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.

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.

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.

Core network infrastructure for agent communication

AI Agent Data Isolation System A universal framework to prevent data contamination in AI agent environments using vector databases. This system safeguards data integrity by detecting and filtering AI-generated content, applying session-based isolation, and preserving original data through configurable contamination detection patterns.

This repository contains an advanced Agent Communication Protocol (ACP) implementation that integrates with GitHub's AI model (OpenAI GPT-5) to provide intelligent responses. This guide will walk you through everything from setup to completion of the assignment.