Will I be able to create my own AI agents after completing this course?

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.

What technologies will I work with in this AI Agents Development course?

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.

What will I get if I subscribe to this Specialization?

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.

Is financial aid available?

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.

Advanced MCP & Tool Calling for AI Agents

Advanced MCP & Tool Calling for AI Agents

This course is part of Agentic AI Engineering: RAG, MCP & MERN Specialization

Instructors: LearnKartS

Included with

Learn more

3 modules

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

3 modules

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

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

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 videosTotal 75 minutes

Course Introduction1 minute
Understanding Transport Layer in MCP9 minutes
MCP vs Tool Calling – Introduction & Concept3 minutes
MCP vs Tool Calling – Architecture & Mechanism6 minutes
MCP vs Tool Calling – Advantages & Practical Setup3 minutes
Introduction and Project Setup for Gemini Tool Calling5 minutes
Creating the generateWithTools Function and Initial Setup5 minutes
Defining the Weather Tool and Its Parameters5 minutes
Creating the Customer Tool and Registering Tools in Gemini4 minutes
Configuring Function Calling Modes and Tool Configuration3 minutes
Handling AI Tool Calls and Executing Functions3 minutes
Sending Tool Results Back to Gemini and Generating Final Response7 minutes
Introduction to OpenAI Tool Calling and Creating the OpenAI Service File5 minutes
Setting Up OpenAI Package and Import Configuratio4 minutes
Configuring Environment Variables and Initializing OpenAI Client4 minutes
Implementing Generate Response and Embeddings Functions4 minutes
Understanding OpenAI Responses API vs Chat Completions API3 minutes

8 assignmentsTotal 144 minutes

Checkpoint Quiz16 minutes
Checkpoint Quiz16 minutes
Checkpoint Quiz16 minutes
Proficiency Quiz20 minutes
Checkpoint Quiz16 minutes
Proficiency Quiz20 minutes
Proficiency Quiz20 minutes
Proficiency Quiz20 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 videosTotal 89 minutes

Implementing the callLLM Function Using Responses API4 minutes
Defining Tool Schemas and Function Parameters5 minutes
Preparing Tools Array and Fixing Type Errors5 minutes
Using Strict Schema and Finalizing Tool Configuration6 minutes
Testing OpenAI Native Tool Calling in Frontend5 minutes
Introduction to MCP and Updating the Gemini Model Configuration5 minutes
Understanding MCP Concepts: Tools, Resources, and Prompts5 minutes
Setting Up the MCP Folder Structure and Project Organization4 minutes
Creating the MCP Server and Initial Server Configuration5 minutes
Creating Tool Files for Customer, Order, and Weather Services5 minutes
Registering the Customer Tool and Defining Input Schema6 minutes
Implementing Output Schema and Completing the Tool Setup7 minutes
Introduction to MCP Transport Layer and Controller Setup5 minutes
Implementing Session Management and Transport Storage Logic5 minutes
Creating Helper Functions for Session Transport and Transport Initialization4 minutes
Implementing POST Handler for MCP Client-Server Communication4 minutes
Implementing GET, DELETE Handlers and Configuring MCP Routes5 minutes
Architecture Deep Dive: The Critical Role of the MCP Client6 minutes

8 assignmentsTotal 162 minutes

Checkpoint Quiz16 minutes
Checkpoint Quiz16 minutes
Checkpoint Quiz20 minutes
Checkpoint Quiz20 minutes
Proficiency Quiz20 minutes
Proficiency Quiz20 minutes
Proficiency Quiz25 minutes
Proficiency Quiz25 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 videosTotal 115 minutes

Introduction to the Project Setup and Required Tools5 minutes
Installing Node.js and Understanding the Runtime Environment5 minutes
Installing and Setting Up Visual Studio Code5 minutes
Verifying Node Installation and Running Basic Node Commands5 minutes
Introduction to Angular and Navigating Angular Documentation5 minutes
Installing Angular CLI Using NPM5 minutes
Checking Angular CLI Version and Understanding CLI Setup5 minutes
Opening and Setting Up the Project Environment in VS Code5 minutes
Installing Essential VS Code Extensions for Angular Development5 minutes
Preparing for AI-Assisted Development with Gemini and Next Steps6 minutes
Introduction to MCP Integration with OpenAI5 minutes
Copying and Setting Up the OpenAI Service in the Backend5 minutes
Installing OpenAI Package and Reviewing Initial Code Changes5 minutes
Updating the Agent Controller and Passing the MCP Client5 minutes
Selecting the LLM Dynamically (Gemini vs OpenAI)5 minutes
Loading MCP Tools Using the MCP Client5 minutes
Transforming MCP Tools into AI-Readable Tool Context5 minutes
Creating System Instructions for AI Tool Usage5 minutes
Designing the Response Contract and Structured Output Format4 minutes
Preparing Messages and Understanding the Agent Loop Concept5 minutes
Testing MCP Tool Calling with OpenAI GPT Model6 minutes
Interview Prep: MCP Architecture Questions6 minutes
Course Summary1 minute

8 assignmentsTotal 189 minutes

Checkpoint Quiz16 minutes
Checkpoint Quiz20 minutes
Checkpoint Quiz24 minutes
Checkpoint Quiz24 minutes
Proficiency Quiz20 minutes
Proficiency Quiz25 minutes
Proficiency Quiz30 minutes
Proficiency Quiz30 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

LearnKartS

157 Courses191,032 learners

Offered by

LearnKartS

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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.

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.

Advanced MCP & Tool Calling for AI Agents

Advanced MCP & Tool Calling for AI Agents

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

There are 3 modules in this course

MCP Architecture and Native Tool Calling

What's included

17 videosTotal 75 minutes

8 assignmentsTotal 144 minutes

Building the MCP Server and Transport Layer

What's included

18 videosTotal 89 minutes

8 assignmentsTotal 162 minutes

MCP Client Integration and Agentic AI System Design

What's included

23 videosTotal 115 minutes

8 assignmentsTotal 189 minutes

Earn a career certificate

Instructors

Offered by

Explore more from Software Development

Agentic AI Foundations with MERN, RAG & MCP

Build Production AI Agents with RAG & MCP

Agentic AI Systems with Vector DBs & RAG

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

More questions

Advanced MCP & Tool Calling for AI Agents

Advanced MCP & Tool Calling for AI Agents

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

There are 3 modules in this course

MCP Architecture and Native Tool Calling

What's included

Building the MCP Server and Transport Layer

What's included

MCP Client Integration and Agentic AI System Design

What's included

Earn a career certificate

Instructors

Offered by

Explore more from Software Development

Agentic AI Foundations with MERN, RAG & MCP

Build Production AI Agents with RAG & MCP

Agentic AI Systems with Vector DBs & RAG

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

Who is this course ideal for?

How will this course help me in real-world AI applications?

Do I need prior experience in AI development to take this course?

More questions