Six months ago, I spent two weeks building a “smart” customer support agent. It could answer questions, look up order status, and even process refunds. I was proud of it. The integration code was a ...

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 ...

This MCP server provides access to 228 tools across 17 toolsets covering the complete CATS API v3. The toolset architecture allows agents to load only what they need, optimizing token usage and ...

Written by Ken Huang, CSA Fellow, Co-Chair of CSA AI Safety Working Groups and Dr. Ying-Jung Chen, Georgia Institute of Technology. This implementation guide provides a comprehensive, hands-on ...

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 ...