Python MCP Servers make it easy to connect Large Language Models (LLMs) securely with real-world data and tools. The Model Context Protocol standardizes safe, efficient communication between AI models ...

The FastMCP examples all include a main file that declare the tool(s) or resource(s). This strategy requires me to have a central file that includes all tools/resources. Creation of a tool, or ...

An MCP Server is a simple program that lets AI models securely access data and tools using the Model Context Protocol (MCP). FastMCP is a Python framework that helps you build MCP servers and clients.

HANDS ON Getting large language models to actually do something useful usually means wiring them up to external data, tools, or APIs. The trouble is, there's no standard way to do that - yet.

In this tutorial, you will learn how to build a full-featured Retrieval-Augmented Generation (RAG) server using IBM Watsonx.ai, ChromaDB for vector indexing, and expose it via the Model Context ...

In this Colab‑ready tutorial, we demonstrate how to integrate Google’s Gemini 2.0 generative AI with an in‑process Model Context Protocol (MCP) server, using FastMCP. Starting with an interactive ...