What can MCP enable? Agents can access your Google Calendar and Notion, acting as a more personalized AI assistant. Claude Code can generate an entire web app using a Figma design. Enterprise chatbots can connect to multiple databases across an organization, empowering users to analyze data using chat. AI models can create 3D designs on Blender and print them out using a 3D printer. Key takeaways: The Model Context Protocol (MCP) is an open standard that aims to standardize how applications supply context to language models, essentially serving as a “universal port” that lets tools and AI models exchange information in a predefined format. MCP works by defining structured schemas for inputs and outputs (often using JSON and libraries like Pydantic for schema enforcement), so that every piece of information—be it a user query, a tool result, or some external data ... Discover what an MCP server is, how it works, and best MCP servers and clients you should use in 2025/2026. MCP (Model Context Protocol) is a new open protocol designed to standardize how applications provide context to Large Language Models (LLMs). Think of MCP like a USB-C port but for AI agents: it offers a uniform method for connecting AI systems to various tools and data sources. This post breaks down MCP, clearly explaining its value, architecture, and how it differs from traditional APIs. What is MCP? The Model Context Protocol (MCP) is a standardized protocol that connects AI agents to ...
