Deploy Remote MCP Servers in Python (Step by Step)

🚀 MCP Servers over Streamable HTTP (Step-by-Step Guide) Want to connect remote tools to your AI assistant like microservices? Meet MCP (Model Context Protocol) — the protocol that lets your LLM-based agents call external tools hosted on separate servers. Links - 📝 Written Tutorial: https://www.aibootcamp.dev/blog/remote-mcp-servers - 👉 Code: https://github.com/alejandro-ao/mcp-streamable-http - 🚀 AI Engineer Bootcamp: https://www.aibootcamp.dev/ - ❤️ Buy me a coffee... or a beer (thanks!): https://buymeacoffee.com/alejandro.ao References: - 🔗 https://modelcontextprotocol.io/quickstart/server - 🔗 https://heeki.medium.com/building-an-mcp-server-as-an-api-developer-cfc162d06a83 In this video, I’ll walk you through how to create your first remote MCP server using Python and expose it over streamable HTTP. You’ll learn how to: 🔧 Build an MCP server from scratch 🌐 Expose tools (like a web search API) over HTTP 🧠 Connect your MCP server to an AI assistant like Cursor 🧪 Use the MCP Inspector to debug your server ⚡️ Mount MCP servers on FastAPI routes 🧩 Set up multiple MCP servers within a single app 🧵 Chapters: 00:00 Intro to MCP 02:10 What is MCP 07:49 Building a Remote MCP Server 14:53 Debugging Remote MCP Servers 17:15 MCP Server Demo with HTTP 19:29 Multiple MCP Servers in a FastAPI App 24:04 Deploy Multi-MCP Server