The Model Context Protocol is becoming the standard for multi-agent AI orchestration. This live 6-hour workshop teaches you to build MCP-orchestrated agent systems from scratch — with context engineering, RAG, memory, and production safeguards included.
By Packt Publishing · Refunds up to 10 days before
MCP provides a vendor-neutral, open standard for connecting AI models to tools, data, and other agents. Building on MCP means your multi-agent architecture is portable, auditable, and future-proof. This workshop shows you how to use MCP effectively with context engineering.
Context engineering is the discipline of designing AI systems that provide the right information, tools, and context to LLMs at the right time — replacing brittle prompts with reliable, scalable production AI architectures.
Multi-agent systems are AI architectures where specialised agents collaborate to accomplish complex tasks. This workshop shows you how to orchestrate them reliably using the Model Context Protocol and semantic blueprints.
MCP is Anthropic's open standard for connecting AI models to tools, data sources, and other agents. This workshop teaches you to use MCP for building orchestrated multi-agent workflows that are transparent and controllable.
Context engineering and multi-agent systems have almost no quality hands-on resources. This 6-hour live workshop gives you a complete guided build with a bestselling AI author answering your questions throughout.
Six modules. Six hours. A production-ready context engine by the time you finish.
Design structured context that gives AI agents precise, goal-driven contextual awareness beyond simple prompting.
Orchestrate specialised agents using the Model Context Protocol for adaptable, context-rich reasoning workflows.
Engineer retrieval-augmented generation pipelines with citations, memory, and safeguards against hallucination.
Design AI memory systems that maintain context across long conversations and complex multi-step workflows.
Implement moderation, data poisoning protection, prompt injection prevention, and trust mechanisms for production AI.
Build a transparent, traceable Context Engine that gives you complete visibility and control over your AI system.
A working production system — not just architectural knowledge.
A fully working multi-agent system with context engineering
MCP-orchestrated agent workflows you can use in production
High-fidelity RAG pipeline with citations and memory
Semantic blueprints and agent architecture patterns
Production-ready safeguards against hallucination and injection
Certificate of completion from Packt Publishing
Denis Rothman has 30+ years in AI and deep experience with agent orchestration standards including MCP.
Denis Rothman is a bestselling AI author with over 30 years of experience in artificial intelligence, optimisation, and agent systems. He has written multiple cutting-edge AI books for Packt Publishing and is the author of the book “Context Engineering for Multi-Agent Systems.” In this workshop he guides you step by step through the practical architecture of production-ready multi-agent AI systems.
This is an intermediate to advanced workshop. You need the basics below.
Common questions about the workshop, what to expect, and how to prepare.
The Model Context Protocol (MCP) is Anthropic's open standard for connecting AI models to external tools, data sources, and other agents. It is becoming the de facto standard for multi-agent AI orchestration in 2026. Learning MCP means your multi-agent architectures are vendor-neutral, portable across AI providers, and aligned with where the industry is heading.
MCP is a protocol standard rather than a specific framework — it defines how AI models connect to tools and agents, not a complete orchestration framework. This means MCP works alongside LangGraph, AutoGen, and other frameworks. This workshop teaches you to use MCP as the integration layer that connects your agents, tools, and data sources.
You will build a complete MCP-orchestrated multi-agent system using context engineering principles — including semantic blueprints, agent tool connections through MCP, a high-fidelity RAG pipeline integrated via MCP, and memory engineering that persists context across agent interactions.
No. This workshop covers MCP from the ground up. The instructor explains the protocol, its design principles, and how to implement MCP connections for your agents step by step during the live session. Prior AI agent experience (at any level) is helpful context but not required.
Yes. MCP is model-agnostic — it works with any LLM provider including OpenAI, Anthropic, and local open source models. The MCP orchestration skills you learn in this workshop apply regardless of which AI models power your agents.
Yes. Tool integration — connecting your AI agents to external APIs, databases, file systems, and services through MCP — is a core component of this workshop. The instructor covers how to design and implement MCP tool connections that your agents can use reliably within your context engineering architecture.
6 hours. Live bestselling AI author. MCP multi-agent system working by the end. Seats are limited.
Register Now →Saturday April 25 · 9am to 3pm EDT · Online · Packt Publishing