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

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

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.

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.

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.

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

A research-grade Python implementation of decentralized multi-agent coordination using auction-based task allocation, designed for autonomous robotics and AI studies.

Production-ready AI Agent Integration Hub. Connect AI agents (LangChain, OpenAI, Gemini) to Slack, Discord, Email, and Webhooks with a unified FastAPI gateway, Redis queuing, and WebSocket support.

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.