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⇱ Advanced MCP & Tool Calling for AI Agents | Coursera

Advanced MCP & Tool Calling for AI Agents

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Advanced MCP & Tool Calling for AI Agents

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Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand MCP architecture, tool calling concepts, and practical setup for Gemini and OpenAI integration.

  • Master tool registration, function calling, and response generation in Gemini and OpenAI environments.

  • Learn to build and configure the MCP server, transport layer, and API routes for seamless client-server communication.

  • Gainexpertisein integrating OpenAI with MCP, setting up Angular for AI-assisted development, and creating agent-driven systems.

Details to know

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Recently updated!

April 2026

Assessments

24 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Agentic AI Engineering: RAG, MCP & MERN Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

Transform the way AI operates!

Building intelligent, autonomous AI agents begins with mastering MCP architecture and tool calling. The issue? Many AI courses offer theory without the practical skills needed for real-world applications. In this Agentic AI course, you’ll learn to create advanced AI agents with Gemini and OpenAI tools. From registering tools and managing function calls to generating dynamic responses, you will discover how to integrate powerful AI functionalities effortlessly. You’ll also master building an MCP server, managing transport layers, and optimizing API routes for top-tier system performance. What sets this course apart? You’ll not only learn the theory but also build and deploy real AI systems that solve real-world problems, giving you the confidence to work in production environments. Ideal for developers and AI enthusiasts eager to create scalable, agent-driven systems. This course will arm you with the tools to make AI smarter and more autonomous. Get ready to build AI that thinks, learns, and adapts. Enroll now and start mastering MCP and tool calling today!

Learn the fundamentals of MCP and native tool calling, including transport layers, architecture, and practical setup with Gemini and OpenAI tools. Implement initial tool functions and handle AI tool calls for real-world responses.

What's included

17 videos8 assignments

17 videos•Total 75 minutes
  • Course Introduction•1 minute
  • Understanding Transport Layer in MCP•9 minutes
  • MCP vs Tool Calling – Introduction & Concept•3 minutes
  • MCP vs Tool Calling – Architecture & Mechanism•6 minutes
  • MCP vs Tool Calling – Advantages & Practical Setup•3 minutes
  • Introduction and Project Setup for Gemini Tool Calling•5 minutes
  • Creating the generateWithTools Function and Initial Setup•5 minutes
  • Defining the Weather Tool and Its Parameters•5 minutes
  • Creating the Customer Tool and Registering Tools in Gemini•4 minutes
  • Configuring Function Calling Modes and Tool Configuration•3 minutes
  • Handling AI Tool Calls and Executing Functions•3 minutes
  • Sending Tool Results Back to Gemini and Generating Final Response•7 minutes
  • Introduction to OpenAI Tool Calling and Creating the OpenAI Service File•5 minutes
  • Setting Up OpenAI Package and Import Configuratio•4 minutes
  • Configuring Environment Variables and Initializing OpenAI Client•4 minutes
  • Implementing Generate Response and Embeddings Functions•4 minutes
  • Understanding OpenAI Responses API vs Chat Completions API•3 minutes
8 assignments•Total 144 minutes
  • Proficiency Quiz•20 minutes
  • Proficiency Quiz•20 minutes
  • Proficiency Quiz•20 minutes
  • Checkpoint Quiz•16 minutes
  • Checkpoint Quiz•16 minutes
  • Checkpoint Quiz•16 minutes
  • Proficiency Quiz•20 minutes
  • Checkpoint Quiz•16 minutes

Build a fully functional MCP server with session management, tool registration, and client-server communication. Explore MCP transport layer setup, route configuration, and testing for agentic AI systems.

What's included

18 videos8 assignments

18 videos•Total 89 minutes
  • Implementing the callLLM Function Using Responses API•4 minutes
  • Defining Tool Schemas and Function Parameters•5 minutes
  • Preparing Tools Array and Fixing Type Errors•5 minutes
  • Using Strict Schema and Finalizing Tool Configuration•6 minutes
  • Testing OpenAI Native Tool Calling in Frontend•5 minutes
  • Introduction to MCP and Updating the Gemini Model Configuration•5 minutes
  • Understanding MCP Concepts: Tools, Resources, and Prompts•5 minutes
  • Setting Up the MCP Folder Structure and Project Organization•4 minutes
  • Creating the MCP Server and Initial Server Configuration•5 minutes
  • Creating Tool Files for Customer, Order, and Weather Services•5 minutes
  • Registering the Customer Tool and Defining Input Schema•6 minutes
  • Implementing Output Schema and Completing the Tool Setup•7 minutes
  • Introduction to MCP Transport Layer and Controller Setup•5 minutes
  • Implementing Session Management and Transport Storage Logic•5 minutes
  • Creating Helper Functions for Session Transport and Transport Initialization•4 minutes
  • Implementing POST Handler for MCP Client-Server Communication•4 minutes
  • Implementing GET, DELETE Handlers and Configuring MCP Routes•5 minutes
  • Architecture Deep Dive: The Critical Role of the MCP Client•6 minutes
8 assignments•Total 162 minutes
  • Proficiency Quiz•20 minutes
  • Proficiency Quiz•20 minutes
  • Proficiency Quiz•25 minutes
  • Proficiency Quiz•25 minutes
  • Checkpoint Quiz•16 minutes
  • Checkpoint Quiz•16 minutes
  • Checkpoint Quiz•20 minutes
  • Checkpoint Quiz•20 minutes

Integrate MCP with OpenAI and Gemini clients, design agent loops, structured outputs, and AI-readable tool contexts. Test and refine your system to create scalable, real-world agentic AI applications.

What's included

23 videos8 assignments

23 videos•Total 115 minutes
  • Introduction to the Project Setup and Required Tools•5 minutes
  • Installing Node.js and Understanding the Runtime Environment•5 minutes
  • Installing and Setting Up Visual Studio Code•5 minutes
  • Verifying Node Installation and Running Basic Node Commands•5 minutes
  • Introduction to Angular and Navigating Angular Documentation•5 minutes
  • Installing Angular CLI Using NPM•5 minutes
  • Checking Angular CLI Version and Understanding CLI Setup•5 minutes
  • Opening and Setting Up the Project Environment in VS Code•5 minutes
  • Installing Essential VS Code Extensions for Angular Development•5 minutes
  • Preparing for AI-Assisted Development with Gemini and Next Steps•6 minutes
  • Introduction to MCP Integration with OpenAI•5 minutes
  • Copying and Setting Up the OpenAI Service in the Backend•5 minutes
  • Installing OpenAI Package and Reviewing Initial Code Changes•5 minutes
  • Updating the Agent Controller and Passing the MCP Client•5 minutes
  • Selecting the LLM Dynamically (Gemini vs OpenAI)•5 minutes
  • Loading MCP Tools Using the MCP Client•5 minutes
  • Transforming MCP Tools into AI-Readable Tool Context•5 minutes
  • Creating System Instructions for AI Tool Usage•5 minutes
  • Designing the Response Contract and Structured Output Format•4 minutes
  • Preparing Messages and Understanding the Agent Loop Concept•5 minutes
  • Testing MCP Tool Calling with OpenAI GPT Model•6 minutes
  • Interview Prep: MCP Architecture Questions•6 minutes
  • Course Summary•1 minute
8 assignments•Total 189 minutes
  • Proficiency Quiz•20 minutes
  • Proficiency Quiz•25 minutes
  • Proficiency Quiz•30 minutes
  • Proficiency Quiz•30 minutes
  • Checkpoint Quiz•16 minutes
  • Checkpoint Quiz•20 minutes
  • Checkpoint Quiz•24 minutes
  • Checkpoint Quiz•24 minutes

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Frequently asked questions

This course is perfect for developers, AI enthusiasts, and anyone eager to build scalable, agent-driven AI systems. If you're looking to transition into AI development or deepen your existing knowledge, this Agentic AI Engineering course will help you develop the skills needed to succeed.

Unlike theoretical courses, this course provides practical, hands-on training in building AI systems.You'llwork on live projects, from MCP tool integration to server and transport layer management, making sureyou'reready for real-world AI deployment.

While prior knowledge of programming is beneficial, the course is designed for developers at various skill levels.

Yes! By the end of the course,you’llbe equipped with the knowledge and hands-on experience to build scalable, autonomous AI agents that can integrate with external tools, solve complex tasks, and function dynamically.

You will be working with cutting-edge technologies like Gemini, OpenAI, and MCP, learning how to integrate and manage these tools effectively to build autonomous, intelligent AI systems.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,