Build Your Own MCP Server with Python and Sevalla
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Learn how to build, deploy, and extend your own Model Context Protocol (MCP) server using Python and Sevalla to let AI models securely access real-world data.
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Artificial Intelligence models like ChatGPT are powerful but limited by their lack of system context. The Model Context Protocol (MCP) solves this by allowing AI to securely interact with APIs, files, and tools in real time. This guide walks you through building a simple MCP server in Python using the FastMCP library—from configuration and tool creation (like adding numbers or fetching weather data) to cloud deployment on Sevalla. By the end, you’ll understand how to make your AI context-aware, bridging the gap between static prompts and live data.
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