In this course, you'll discover how to build powerful AI applications using the Model Context Protocol, a revolutionary approach that eliminates tedious integration code when connecting Claude to external services and data sources. This course takes you from understanding MCP's core architecture to building fully functional MCP servers and clients that can interact with real-world systems.
You'll learn the three essential MCP primitives - tools, resources, and prompts - and understand when to use each one. Through hands-on implementation, you'll create your own MCP server with the Python SDK, defining tools that Claude can call autonomously, resources that provide data to your applications, and prompts that deliver professionally crafted workflows to end users.
By building both client and server components, you'll gain complete insight into how MCP enables seamless communication between AI models and external services. You'll work with the MCP Inspector to test your implementations, understand transport protocols, and see exactly how messages flow through the entire system. Whether you're building GitHub integrations, document management systems, or custom AI workflows, this course gives you the practical skills to leverage MCP's standardized approach and dramatically reduce your development burden.
Get started with the Model Context Protocol (MCP). Learn what MCP is, why it matters, and how MCP clients communicate with MCP servers.
Build your first MCP server from scratch. Set up a Python project, define tools, and test your server using the official inspector.
Implement an MCP client to connect to servers. Learn how to define resources, access them, work with prompts, and integrate everything into a complete application.
Review key concepts and apply what you've learned. Complete a final assessment to test your understanding of MCP.
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Anthropic is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (88/100).
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