Advanced Strands Agents with MCP

  • IntermediateLevel

  • 346+Students Enrolled

  • 1 Hr 30 MinsDuration

  • 4.7Average Rating

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About this Course

  • Learn to build production-ready AI agents with Strands Agents MCP, mastering the Model Context Protocol (MCP) for scalable real-world automation and next-gen Agentic AI development
  • Master agent concepts like agent class, agentic loop, and context flow to gain deep insights into the Strands Agents MCP course online ecosystem powering intelligent AI systems.
  • Configure and integrate model providers like OpenAI, Anthropic, Amazon Bedrock, and Ollama to boost interoperability and adaptability in your advanced agentic AI course projects.
  • Build and control custom agent logic using hooks to modify behaviors across event lifecycle points, applying MCP fundamentals for building AI agents in real-time decision pipelines
  • Manage context-rich, stateful conversations with sliding window and summarization managers, leveraging Model Context Protocol (MCP) for efficient memory and persistence handling.
  • Gain end-to-end practical experience to build agents using MCP with robust orchestration, observability, and deployment best practices for enterprise-grade Agentic AI systems.

Learning Outcomes

Agentic AI Foundations

Build autonomous agents with models, memory, and session management

Intelligent Agent Design

Learn to configure, extend, and deploy agents using Strand’s SDK

Production-Ready Agents

Refine agentic loops, tool orchestration, and multi-model integration

Who Should Enroll

  • Professionals working on LLM apps who want to integrate memory, tools, and control layers.
  • Teams building autonomous workflows with multiple model providers and state management.
  • Advanced learners exploring the intersection of LLMs, orchestration, and enterprise AI deployment.
  • Designed for AI engineers building advanced agentic systems with Strand's SDK and Bedrock.

Course Curriculum

Learn from foundational concepts to deploying fully functional agents with hooks, tools, persistent sessions, and memory.

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  1. 1. Getting Started with Agent AI: Setup & Foundations

  2. 2. Building Your First Agent: Architecture & Configuration

  3. 3. Exploring Model Providers: Configuration & Integration

  4. 4. Advanced Response Handling: Hooks & Event Processing

  5. 5. Empowering Agents with Tools: Creation & Execution

  6. 6. Managing Conversations: Session State & Persistence

  7. 7. Enhancing Agents with Memory: Storage & Retrieval

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Du’An Lightfoot

Sr. AI Engineer (AI/ML), AWS

Du'An Lightfoot is a Senior AI Engineer at AWS with 20+ years of experience. A frequent AWS re:Invent speaker and mentor, he helps teams build and scale agentic AI systems using Strands SDK and MCP integrations.

Get this Course Now

With this course you’ll get

  • Du’An Lightfoot

    Instructor

  • 4.7

    Average Rating

  • Intermediate

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Industry-Recognized Credential
  • Career Advancement Credential
  • Shareable Achievement
certificate

Frequently Asked Questions

Looking for answers to other questions?

The Advanced Strands Agents with MCP course teaches how to build production-ready AI agents using the Model Context Protocol (MCP), covering advanced agentic workflows, lifecycle hooks, and deployment practices for scalable, enterprise-grade AI systems.

Basic understanding of Python and AI concepts is recommended. The advanced agentic AI course builds upon these fundamentals, introducing hands-on skills to design, configure, and manage agents using Strands Agents SDK and MCP fundamentals.

The Model Context Protocol (MCP) serves as the communication layer that links reasoning models, memory, and tools. It’s fundamental to building adaptive, reliable, and context-aware AI agents using Strands Agents.

Unlike traditional frameworks, Strands Agents MCP introduces a Model Context Protocol (MCP) that enables seamless agent coordination, contextual reasoning, and tool integration — empowering developers to build scalable and intelligent agentic ecosystems.

You’ll use Strands Agents SDK, Model Context Protocol (MCP), OpenAI, Anthropic, Bedrock, and Ollama APIs. These tools empower learners to build agents using MCP that are adaptable, explainable, and efficient.

Strands Agents use the Model Context Protocol (MCP) to handle data flow and context management efficiently. Together, they enable structured communication, better reasoning, and smoother decision-making within agentic AI workflows.

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