✨ New course! Enroll in MCP: Build Rich-Context AI Apps with Anthropic

:arrow_forward: Enroll Now!


Join MCP: Build Rich-Context AI Apps with Anthropic, a short course created in partnership with Anthropic and taught by Elie Schoppik.

Connecting AI applications to external systems to bring rich context to LLMs has often meant writing custom integrations for each use case. This has fragmented AI development between teams within a company and across the industry.

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.

Thanks for sharing this, looks like a great step toward making integration with LLMs more standardized. Curious how flexible MCP is when dealing with more dynamic or real-time data sources. Has anyone here started experimenting with it yet? It would be cool to hear early impressions.