MCP
# Building an MCP Server in Python with FastMCP Artificial intelligence is evolving rapidly. Modern AI models can **reason**, **write**, **code**, and **analyze** in ways that once seemed impossible. However, there’s still one important limitation: **context**. Most AI models cannot directly access your **local files**, **APIs**, or **real‑time data*
MCP
Introduction to MCP MCP (Model Context Protocol) is a simple, standardized framework that allows AI models (LLMs) to communicate with APIs and data sources. You can think of it like a universal connector — if both sides support MCP, they can seamlessly integrate and work together. An MCP server is any
API
APIs vs MCPs — Understanding the Difference APIs and MCPs both enable communication between systems. At first glance they may seem alike — both allow one piece of software to request data or perform an action from another. However, their purpose, operation, and intended audience differ significantly. --- Table of Contents * What
MCP
MCP (Model Context Protocol): A Standard for AI Interaction with Tools and Data MCP is a unified protocol standard for enabling AI models to interact with external data sources and tools — similar to giving AI a USB-C–style universal interface. This article explores the essence, value, usage, and development of
Flutter
# MCP (Model Context Protocol) for Dart & Flutter Developers Software development is rapidly moving toward **AI-assisted workflows** and **smart tooling**. From IDEs that autofill your code, to AI assistants that analyze projects, and automated test pipelines — these all need a **standardized way to exchange information**. That’s where the **Model
Next.js
# Running a Full Next.js App Natively Inside ChatGPT When **OpenAI announced the Apps SDK with Model Context Protocol (MCP) support**, it enabled embedding rich web applications directly inside ChatGPT. But serving static HTML in an iframe is straightforward — running a full **Next.js app** with client-side navigation, React Server