The Model Context Protocol (MCP) is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, simplifying how new context is integrated into AI applications. MCP, developed by Anthropic, is based on a client-server architecture. It defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client and running locally, or an independent process running remotely.
In this hands-on course, you’ll learn the core concepts of MCP and how to implement it in your AI Application. You’ll make a chatbot MCP-compatible, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers.
Course Objectives:
In this course, you will learn to:
- Understand why MCP makes AI development less fragmented and how it standardizes connections between AI applications and external data sources.
- Learn the core components of the client-server architecture of MCP and the underlying communication mechanism.
- Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application.
- Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector.
- Create an MCP client inside your chatbot to dynamically connect to your server.
- Connect your chatbot to reference servers built by Anthropic’s MCP team such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown.
- Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients.
- Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications.
- Learn about the roadmap for future MCP development such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication.
Course content
1. MCP fundamentals & server development
- Start with understanding MCP’s architecture and why it exists
- Build your first MCP server with tools using the Python SDK, then test it with the built-in inspector.
2. MCP client implementation & advanced features
- Build the client side to communicate with MCP servers
- Implement resources for direct data access and prompts for pre-built instructions
- See how everything connects in a complete application flow.
3. Chatbot Example
4. Creating an MCP Server
5. Creating an MCP Client
6. Connecting the MCP Chatbot to Reference Servers
7. Adding Prompt and Resource Features
8. Configuring Servers for Claude Desktop
9. Creating and Deploying Remote Servers
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Course Prerequisites
- Basic Python programming experience
- Understanding of async/await patterns
- Familiarity with API concepts
- Basic understanding of AI and LLM concepts
- Familiarity with software development principles and API concepts
Who can attend
- Engineers who want to integrate Claude with external tools and services without writing tons of boilerplate integration code
- It’s helpful to be familiar with Python and have a basic understanding of LLM prompting and LLM application development.
Number of Hours: 25hrs
Certification
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- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
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