📘Introduction

Welcome to this hands-on FastMCP tutorial! In this guide, we’ll walk step-by-step through how to run a FastMCP Server. By the end, you’ll have a fully working server with a custom tool that AI clients can call and interact with.

✅ Prerequisites

Before you begin, make sure you have the following:

🐍✅ Installed Python
📦✅ Installed Pip
🌐✅ Created and activated a virtual environment (venv)
⚡✅ FastMCP installed inside your venv
⚙️✅ Created a FastMCP Server instance
🛠️✅ At least one tool added to your FastMCP Server

💡What does running a FastMCP server mean?

Running a FastMCP Server exposes your Python code and custom tools to AI clients in real time. It acts as a bridge, allowing AI apps like ChatGPT to request data, execute functions, and receive results dynamically. Essentially, your server turns your code into an interactive service that AI can safely call and use.

🔌 Example FastMCP Server

We've already created a FastMCP Server instance called Deep Learning Nerds MCP Server 📘 and added a tool list_tutors() to the MCP Server. Our FastMCP Server should be able to return a static list of the Deep Learning Nerds tutors.

➕1️⃣ Add Run Statement

At the bottom of your Python file (e.g., mcp_server.py), add:

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