AI Agent Systems with LangGraph and MCP
Overview The AI Agent Systems with LangGraph and MCP Course is a CPD-accredited, fully online programme designed for learners who want to develop advanced AI agent development skills. This course introduces modern agent frameworks, workflow orchestration, and Model Context Protocol (MCP) concepts used to build intelligent and connected AI systems. …
Overview
Overview
The AI Agent Systems with LangGraph and MCP Course is a CPD-accredited, fully online programme designed for learners who want to develop advanced AI agent development skills. This course introduces modern agent frameworks, workflow orchestration, and Model Context Protocol (MCP) concepts used to build intelligent and connected AI systems.
Throughout the course, you will explore AI agent architectures, LangGraph workflows, MCP integrations, tool calling, agent memory, multi-step reasoning, automation pipelines, and intelligent application design. You will learn how developers create reliable AI agents that can interact with tools, data sources, and external systems.
This course is ideal for AI developers, Python programmers, software engineers, machine learning professionals, and technology specialists looking to advance their generative AI expertise. With flexible online learning, CPD accreditation, and practical AI engineering concepts, it helps learners build confidence in developing next-generation agent-based applications.
Key highlights:
- Understand AI agent system architectures
- Build workflows using LangGraph
- Explore Model Context Protocol integration
- Develop intelligent automation pipelines
- Flexible self-paced online learning with lifetime access
- CPD-accredited for advanced AI development
- Apply agent systems to practical projects
Accreditation & Recognition
The AI Agent Systems with LangGraph and MCP Course is CPD-accredited, supporting learners who want to develop practical artificial intelligence and advanced software engineering skills. The course provides structured learning focused on AI agents, workflow automation, tool connectivity, and modern generative AI development approaches.
- 100% online and flexible learning experience
- Designed for AI developers and programmers
- Includes CPD-accredited certificate upon completion
- Supports progression into AI careers
Assessment & Certification
Your understanding of AI agent systems with LangGraph and MCP is assessed through an online multiple-choice assessment designed to evaluate your knowledge of agent workflows, orchestration methods, MCP concepts, tool integration, and intelligent application development. You will receive instant results after completion and can retake the assessment if required. Upon successful completion, you can order your CPD Accredited certificate as evidence of your advanced AI engineering learning and professional development achievement.
Who Is This Course For?
- AI developers building agent systems
- Python programmers creating AI workflows
- Software engineers adopting AI automation
- Machine learning professionals advancing skills
- Technology specialists exploring generative AI
Career Opportunities & Progression
- AI Agent Engineer (£50,000 – £100,000)
- Generative AI Developer (£50,000 – £95,000)
- AI Engineer (£45,000 – £85,000)
- Machine Learning Engineer (£45,000 – £80,000)
- AI Solutions Architect (£60,000 – £110,000)
Key Skills You’ll Gain
- Designing AI agent architectures
- Building LangGraph workflows
- Understanding MCP integrations
- Creating multi-step AI processes
- Connecting AI agents with tools
- Developing intelligent automation systems
- Building scalable AI applications
Why Study with Royal Open College
Royal Open College is a trusted CPD-accredited training provider committed to helping learners develop practical and career-focused skills. Our online courses combine flexible study options with industry-relevant knowledge, allowing learners to build confidence and progress professionally.
- Expert-designed courses focused on practical skills
- 100% online learning with flexible access
- Affordable training with transparent pricing
- Trusted by learners developing future-ready skills
Enrol today in the AI Agent Systems with LangGraph and MCP Course to strengthen your AI engineering expertise, build advanced agent workflows, and prepare for the future of intelligent automation.
Curriculum
Curriculum
- 5 Sections
- 40 Lessons
- Lifetime Access
- Building AI Agentic Workflows in LangGraph24 Items
- 1.1Introducing the Project: Building Agentic Workflows in LangGraph3 Minutes
- 1.2Understanding LangGraph Components (Nodes, Edges and State Graph) and Features6 Minutes
- 1.3Building Your First Agentic AI Workflow in LangGraph: Part 15 Minutes
- 1.4Building Your First Agentic AI Workflow in LangGraph: Part 23 Minutes
- 1.5Trying the Practice Question on Testing the Summarization AI Agent in LangGraph1 Minute
- 1.6Walking Through the Practice Solution for Testing the Summarization AI Agent in LangGraph2 Minutes
- 1.7Building a Multi Node Agentic Workflow in LangGraph3 Minutes
- 1.8Trying the Practice Question on Adding a New Node (Sentiment) to the Agentic Workflow1 Minute
- 1.9Walking Through the Practice Solution for Adding a New Node (Sentiment) to the Agentic Workflow4 Minutes
- 1.10Developing an Agentic AI Workflow with One Tool and Conditional Edges: Part 15 Minutes
- 1.11Developing an Agentic AI Workflow with One Tool and Conditional Edges: Part 26 Minutes
- 1.12Trying the Practice Question on Calling Tools in LangGraph1 Minute
- 1.13Walking Through the Practice Solution for Calling Tools in LangGraph3 Minutes
- 1.14Creating and Adding a New Custom Tool to LangGraph Workflows2 Minutes
- 1.15Trying the Practice Question on Defining New Custom Tools in LangGraph1 Minute
- 1.16Walking Through the Practice Solution for Defining New Custom Tools in LangGraph3 Minutes
- 1.17Leveraging LangGraph to Perform Flight Search with the Amadeus Tool and ToolNode5 Minutes
- 1.18Trying the Practice Question on Adding a Hotel Search Tool Using Amadeus1 Minute
- 1.19Walking Through the Practice Solution for Adding a Hotel Search Tool Using Amadeus3 Minutes
- 1.20Bringing Everything Together and Building the AI Booking Agent2 Minutes
- 1.21Trying the Practice Question on Testing the AI Agent Booking Tool1 Minute
- 1.22Walking Through the Practice Solution for Testing the AI Agent Booking Tool2 Minutes
- 1.23Building a Gradio Integration for the Booking AI Agent in LangGraph3 Minutes
- 1.24Wrapping Up with a Summary and Thank You2 Minutes
- Build AI Agents with Model Context Protocol (MCP) & OpenAI Agents SDK13 Items
- 2.1Getting an Overview of the Project with MCP and the OpenAI Agents SDK4 Minutes
- 2.2Understanding Model Context Protocol (MCP)5 Minutes
- 2.3Installing Key Libraries and Configuring APIs4 Minutes
- 2.4Building and Configuring the MCP Server with Tools: Part 16 Minutes
- 2.5Building and Configuring the MCP Server with Tools: Part 23 Minutes
- 2.6Launching the MCP Server5 Minutes
- 2.7Trying the Practice Question on Adding a New Tool to the MCP Server1 Minute
- 2.8Walking Through the Practice Solution for Adding a New Tool to the MCP Server4 Minutes
- 2.9Exploring Tools on the MCP Server and Fetching the Manifest (Schema)3 Minutes
- 2.10Trying the Practice Question on the MCP Server Manifest (Schema)1 Minute
- 2.11Walking Through the Practice Solution for the MCP Server Manifest (Schema)2 Minutes
- 2.12Creating an AI Agent Using the OpenAI Agents SDK with MCP Tools4 Minutes
- 2.13Wrapping Up with a Conclusion, Summary and Thank You2 Minutes
- Resources1 Item
- Practice Lab1 Item
- Claim Your Certificate1 Item
Course Features
- Lectures 40
- Quiz 0
- Duration Lifetime access
- Skill level All Levels
- Language English
- Students 1311
- Assessments Yes
Payment methods possible
Company Registration No : 14422633
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