ai-agent-protocols

glaforge
9
This deep dive explores key protocols and frameworks essential for building AI agents, including MCP, A2A, ACP, ADK, Arc, Quarkus, and LangChain4j. Attendees will learn their merits, practical implementation, and interoperability through detailed walkthroughs and demos, gaining clarity on their roles in effective LLM-based agent development.

Overview

What is ai-agent-protocols

ai-agent-protocols is a comprehensive exploration of essential protocols and frameworks for building AI agents, including MCP, A2A, ACP, ADK, Arc, Quarkus, and LangChain4j. It focuses on their merits, practical implementation, and interoperability for effective LLM-based agent development.

How to Use

To use ai-agent-protocols, developers can explore the provided examples in the repository, utilize the Google Agent Development Kit (ADK) for building agents, and implement communication through the Model-Context-Protocol (MCP) and Agent-to-Agent (A2A) protocols.

Key Features

Key features include agent development using the ADK, remote tool usage via MCP, agent-to-agent communication through A2A, and the use of modern Java frameworks like Quarkus for efficient service development.

Where to Use

ai-agent-protocols can be used in various fields such as AI development, chatbot creation, multi-agent systems, and any application requiring sophisticated agent interactions and workflows.

Use Cases

Use cases include building chatbots, implementing collaborative workflows, creating multi-agent systems for task delegation, and integrating agents with external services through standardized protocols.

Content