I Connected Claude AI to My Local Machine with MCP | MCP + NGROK

What if Claude.ai could communicate directly with your local machine? In this video, we build a simple *local MCP server* that exposes CPU and memory usage from a local computer, then connect it to *Claude.ai* using **MCP + ngrok**. The result? You can ask Claude something as simple as: *“What is my current CPU usage?”* Claude connects through the tunnel, reaches the MCP server running on your local machine, executes the tool, and returns the result. In this tutorial, you'll learn: 🔹 What a local MCP server looks like 🔹 How to build an MCP server using Python and FastMCP 🔹 How to expose local tools through ngrok 🔹 How to configure a custom connector in Claude.ai 🔹 How Claude discovers and calls your local MCP tools 🔹 How Cloud AI and local computing can work together 🔹 How this architecture can be extended to more powerful local tools We're keeping the example intentionally simple with just two tools: 🖥️ *CPU Usage* 💾 *Memory Usage* But this is only the beginning. Imagine connecting Claude to local file processing, internal applications, private data, automation scripts, local AI models, or heavy computation — while keeping the actual processing on your machine. Architecture *Claude.ai → ngrok Tunnel → Local MCP Server → Local Tools* Simple architecture. Powerful possibilities. 🛠️ Technologies Used • Python • FastMCP • MCP • Claude.ai • ngrok • Local machine tools The complete project is available in the **Curious Architect GitHub space**. If you enjoyed the video, *like, subscribe, and turn on notifications* for more practical AI, MCP, local AI, and agent tutorials. Welcome to *The Curious Architect* — where we unravel the mysteries behind AI technologies. #ClaudeAI #MCP #ModelContextProtocol #AI #AIAgents #LocalAI #Python #ngrok #FastMCP #Claude