Connecting LLMs to Your Data With Python MCP Servers - Real Python

MCP is an open protocol that standardizes how AI models connect to external systems. It uses a client-server architecture where an MCP client communicates with an MCP server. Core concepts include prompts, resources, and tools, which define how requests are expressed, what data can be accessed, and what actions can be performed. A Python MCP server can be built with customized tools that query data from an e-commerce source. A simple simulated e-commerce database can be used to keep learning focused. An AI agent such as Cursor can integrate with the MCP client to observe real tool calls during operation.

"The Model Context Protocol (MCP) is a new open protocol that allows AI models to interact with external systems in a standardized, extensible way. In this video course, you'll install MCP, explore its client-server architecture, and work with its core concepts: prompts, resources, and tools."

"You'll then build and test a Python MCP server that queries e-commerce data and integrate it with an AI agent in Cursor to see real tool calls in action. By the end of this video course, you'll understand: What MCP is and why it was created; What MCP prompts, resources, and tools are; How to build an MCP server with customized tools; How to integrate your MCP server with AI agents like Cursor."

"To keep the focus on learning MCP rather than building a complex project, you'll build a simple MCP server that interacts with a simulated e-commerce database. You'll also use Cursor's MCP client, which saves you from having to implement your own."

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