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

通过 Coursera Plus 提高技能，仅需 239 美元/年（原价 399 美元）。立即节省

Advanced MCP & Tool Calling for AI Agents

本课程是 Agentic AI Engineering: RAG, MCP & MERN 专项课程的一部分

位教师：LearnKartS

包含在中

了解更多

3个模块

深入了解一个主题并学习基础知识。

高级设置等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

3个模块

深入了解一个主题并学习基础知识。

高级设置等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

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.

要了解的详细信息

可分享的证书

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Agentic AI Engineering: RAG, MCP & MERN 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有3个模块

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.

涵盖的内容

17个视频8个作业

17个视频总计75分钟

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

8个作业总计144分钟

Proficiency Quiz20分钟
Proficiency Quiz20分钟
Proficiency Quiz20分钟
Checkpoint Quiz16分钟
Checkpoint Quiz16分钟
Checkpoint Quiz16分钟
Proficiency Quiz20分钟
Checkpoint Quiz16分钟

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.

涵盖的内容

18个视频8个作业

18个视频总计89分钟

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

8个作业总计162分钟

Proficiency Quiz20分钟
Proficiency Quiz20分钟
Proficiency Quiz25分钟
Proficiency Quiz25分钟
Checkpoint Quiz16分钟
Checkpoint Quiz16分钟
Checkpoint Quiz20分钟
Checkpoint Quiz20分钟

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.

涵盖的内容

23个视频8个作业

23个视频总计115分钟

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

8个作业总计189分钟

Proficiency Quiz20分钟
Proficiency Quiz25分钟
Proficiency Quiz30分钟
Proficiency Quiz30分钟
Checkpoint Quiz16分钟
Checkpoint Quiz20分钟
Checkpoint Quiz24分钟
Checkpoint Quiz24分钟

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

LearnKartS

157 门课程191,771 名学生

提供方

LearnKartS

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常见问题

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

您将学到什么

要了解的详细信息

了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识

该课程共有3个模块

MCP Architecture and Native Tool Calling

涵盖的内容

17个视频总计75分钟

8个作业总计144分钟

Building the MCP Server and Transport Layer

涵盖的内容

18个视频总计89分钟

8个作业总计162分钟

MCP Client Integration and Agentic AI System Design

涵盖的内容

23个视频总计115分钟

8个作业总计189分钟

获得职业证书

位教师

提供方

从 Software Development 浏览更多内容

MCP Servers & Agentic AI Architecture

Build AI Agents using MCP

Build Production AI Agents with RAG & MCP

Developing MCP-Powered Agentic AI Systems

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

通过 Coursera Plus 开启新生涯

通过在线学位推动您的职业生涯

加入超过 3400 家选择 Coursera for Business 的全球公司

常见问题

更多问题

Advanced MCP & Tool Calling for AI Agents

Advanced MCP & Tool Calling for AI Agents

您将学到什么

要了解的详细信息

了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识

该课程共有3个模块

MCP Architecture and Native Tool Calling

涵盖的内容

Building the MCP Server and Transport Layer

涵盖的内容

MCP Client Integration and Agentic AI System Design

涵盖的内容

获得职业证书

位教师

提供方

从 Software Development 浏览更多内容

MCP Servers & Agentic AI Architecture

Build AI Agents using MCP

Build Production AI Agents with RAG & MCP

Developing MCP-Powered Agentic AI Systems

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

通过 Coursera Plus 开启新生涯

通过在线学位推动您的职业生涯

加入超过 3400 家选择 Coursera for Business 的全球公司

常见问题

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?

更多问题