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This document provides a quickstart guide to building and deploying a remote Model Context Protocol (MCP) server using Azure Functions with .NET/C#.
This document provides a quickstart guide to building and deploying a custom remote Model Context Protocol (MCP) server using Azure Functions with Python.
Snippy is a serverless code snippet management service using Azure Functions, Durable Functions, Azure OpenAI, Microsoft Fabric, and Azure AI Agents.
This document provides a comprehensive guide to setting up a Remote Model Context Protocol (MCP) server using Azure Functions with Node.js/TypeScript. It includes instructions for local development, deployment to Azure, and integration with various tools and platforms.
The Azure Database for PostgreSQL MCP Server allows AI models to interact with data hosted in Azure Database for PostgreSQL using the Model Context Protocol (MCP) standard.
This guide provides instructions for setting up a remote Model Context Protocol (MCP) server using Azure Container Apps with Node.js and TypeScript.
Azure AI Vision Face MCP-Server is designed to integrate face liveness detection into AI workflows, ensuring proof of presence.
The Azure Content Understanding MCP Server integrates Azure Content Understanding capabilities with AI systems through a Model Context Protocol (MCP) server.
This document provides a comprehensive overview of a Model Context Protocol (MCP) server, detailing its features, tools, resources, and usage across different platforms.
This document provides a comprehensive guide on setting up a remote Model Context Protocol (MCP) server using Azure Functions with Java.
