microsoft

This project is a beginner-friendly resource for learning MCP (Machine Code Programming) using Python. It covers a wide range of topics from basic concepts to practical examples, making it ideal for those looking to grasp the fundamentals of programming. With its simple structure and abundant sample code, it is designed to be easily understandable for newcomers.

The Microsoft Model Context Protocol (MCP) is an open standard that enables seamless integration between AI applications and external data sources. It allows AI models to access the necessary context to perform tasks effectively. Based on a client-server architecture, it standardizes connections between host applications and servers.

MCP Gateway is a reverse proxy and management layer for MCP servers, facilitating scalable, session-aware routing and lifecycle management in Kubernetes environments. It offers a control plane for deploying, updating, and deleting MCP servers, along with enterprise-ready integration points such as telemetry, access control, and observability. The gateway supports session affinity for traffic routing and manages logical resources representing MCP servers.

A OneDrive MCP server implementation for local testing and community contribution

A comprehensive set of samples of creating and using MCP servers and clients with .NET

typespec-mcp is a type-safe API design tool for TypeScript. It allows developers to easily design API interfaces using type definitions, reducing errors. The automatically generated documentation makes it easier to use the API.

MCP server for Fabric Real-Time Intelligence (https://aka.ms/fabricrti) supporting tools for Eventhouse (https://aka.ms/eventhouse), Azure Data Explorer (https://aka.ms/adx, and other RTI services (coming soon)

The Clarity MCP Server is a Model Context Protocol (MCP) server designed for the Microsoft Clarity data export API. This tool allows you to easily fetch analytics data from Clarity, particularly integrating seamlessly with Claude for Desktop and other MCP-compatible clients. It enables filtering by up to three dimensions such as browser, device, country/region, and OS. This allows you to retrieve various metrics like scroll depth, engagement time, and traffic, making it a powerful tool for data analysis.