Overview
Build ACP-compliant agent servers that wrap LangGraph, CrewAI & SmolAgent for universal communication, Master REST-based agent communication patterns for building scalable, interoperable multi-agent systems, Integrate MCP to give agents real-time tool access and external data source connectivity capabilities, Implement agent discovery systems and registries for seamless sharing and collaboration across teams, Design linear and hierarchical multi-agent workflows with router agents for intelligent task delegation
Agentic AI
Python
Transform isolated AI agents into powerful collaborative teams with this comprehensive course on Agent Communication Protocol (ACP) and Model Context Protocol (MCP) integration. In today's rapidly evolving AI landscape, agents built with different frameworks like LangGraph, CrewAI, and SmolAgent often operate in silos, unable to communicate effectively. This course breaks down those barriers by teaching you to build ACP-compliant systems that work like REST APIs for agent communication.
You'll master the fundamentals of wrapping existing agents in ACP servers, enabling seamless interoperability across any framework or platform. Through hands-on projects, you'll construct both linear and hierarchical multi-agent workflows, implement router agents for intelligent task delegation, and integrate MCP to provide your agents with powerful tool access capabilities. The course emphasizes practical application, teaching you to deploy discoverable agents that can automatically register their capabilities and coordinate complex tasks without human intervention.
Key learning outcomes include building ACP-compliant agent architectures, designing sophisticated multi-agent communication patterns, implementing dynamic agent discovery systems, and creating scalable workflows that adapt to changing requirements. You'll explore real-world scenarios where specialized agents collaborate on complex problems, from automated content creation pipelines to cross-platform enterprise integrations.
By course completion, you'll have created a comprehensive agent registry system, enabling easy sharing and discovery across development teams. You'll understand how to leverage ACP's open protocol design for flexible agent replacement, multi-agent collaboration, cross-platform integration, and even inter-company partnerships. This foundation prepares you to build the next generation of scalable, interoperable AI systems that transform how agents work together in production environments.
Perfect for developers, AI engineers, and system architects ready to move beyond single-agent solutions toward truly collaborative AI ecosystems.
Rahul Raj
Rahul Raj is Generative AI Engineer with over 10 years of experience in AI and software development. Over the past six years, He has been teaching students around the world and helping them understand complex AI concepts through practical, hands-on learning. He specializes in Generative AI, Large Language Models (LLMs), ChatGPT, LangChain, Python, Machine Learning, and Algorithmic Trading.
He is the Co-Founder of SRP AI Technology, where we build real-world AI applications for industries like healthcare, finance, and education. Along with product development, He also focus on supporting learners, developers, and entrepreneurs who want to grow their careers or businesses using AI.
His core teaching philosophy is to give people a future. He empowers students to be creators, not just consumers. He believe in using technology with wisdom, empathy, and purpose.His mission is to prepare the next generation to lead with knowledge,adapt with confidence, and build a world where humans and AI grow together
Whether you’re just getting started, switching careers, or looking to build your own AI projects or company, his courses are designed to guide you step-by-step through the most relevant tools and techniques used in the industry today.
If you're ready to build practical AI skills and stay ahead in this fast-moving field, He is here to help you every step of the way.