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Connecting LLMs to Your Data With Python MCP Servers (Overview)

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

You’ll get hands-on experience with Python MCP by creating and testing MCP servers and connecting your MCP to AI tools. 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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Course Slides (.pdf)

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Sample Code (.zip)

22.3 KB

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