Connect AI models to tools and data using Model Context Protocol.
Set up and run an MCP server with defined tools and resources.
Build MCP clients that communicate with the server.
Skills you'll gain
Category: Artificial Intelligence
Artificial Intelligence
Category: Generative AI Agents
Generative AI Agents
Category: Context Management
Context Management
Category: AI Integrations
AI Integrations
Category: Server Administration
Server Administration
Category: Servers
Servers
Category: Data Access
Data Access
Category: Interoperability
Interoperability
Category: Artificial Intelligence and Machine Learning (AI/ML)
Artificial Intelligence and Machine Learning (AI/ML)
Category: Tool Calling
Tool Calling
Category: Debugging
Debugging
Category: Real Time Data
Real Time Data
Tools you'll learn
Category: Model Context Protocol
Model Context Protocol
Category: Agentic Workflows
Agentic Workflows
Category: Generative AI
Generative AI
Category: AI Workflows
AI Workflows
Category: Anthropic Claude
Anthropic Claude
Category: OpenAI API
OpenAI API
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
1 assignment
Taught in English
91% of learners achieved a positive career outcome
Build your subject-matter expertise
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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 is 1 module in this course
MCP (Model Context Protocol) lets developers securely connect tools, APIs, and data sources to AI models like Claude, GPT, or Gemini. With MCP, your AI isn’t just a chatbot—it becomes a powerful, action-taking agent that can interact with the outside world.
MCP is an open protocol by Anthropic that bridges the gap between language models and real-world context. It standardizes how models access resources, tools, and prompts.
Whether you’re building local dev tools or production AI apps, MCP ensures your model always has the right context at the right time.
MCP is perfect for developers who want to build AI agents that take meaningful actions, fetch live data from APIs, files, or databases, connect LLM models to IDE plugins or command-line tools, develop composable, multi-server AI workflows, and debug and inspect AI integrations with ease.
What you'll build:
In this hands-on course, you’ll build your own Weather MCP Server in Node.js/TypeScript and add Tools, Resources, and Prompts. You'll also connect your server to MCP Client (Claude Desktop and MCP Inspector) and see your AI agent fetch live responses in real time!
What's included
1 assignment10 plugins
Show info about module content
1 assignment•Total 25 minutes
Intro to MCP Graded Assignment•25 minutes
10 plugins•Total 40 minutes
Welcome to interactive lessons!•1 minute
Introduction•3 minutes
Intro to MCP and its importance•4 minutes
Core MCP concepts & architecture•5 minutes
Setting up an MCP server and defining tools•7 minutes
Registering resources in the MCP server•4 minutes
Running the MCP server•6 minutes
Transports•3 minutes
MCP clients•4 minutes
Wrap Up•3 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.
Instructor
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Frequently asked questions
When will I have access to the lectures and assignments?
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.
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.