Azure AI Travel Agents is an AI solution for travel agencies leveraging Llamaindex.TS and MCP. This project provides features to automate travel planning and booking, designed to help users easily access travel information.
This is a quickstart template to easily build and deploy a custom remote MCP server to the cloud using Azure functions. You can clone/restore/run on your local machine with debugging, and `azd up` to have it in the cloud in a couple minutes. The MCP server is secured by design using
This sample demonstrates how to build an AI gateway for MCP servers using Azure API Management. It is based on the latest MCP authorization specification and utilizes Azure Functions to deploy secure remote MCP servers. The flow can be understood through a sequence diagram.
This is a quickstart template to easily build and deploy a custom remote MCP server to the cloud using Azure functions. You can clone/restore/run on your local machine with debugging, and azd up to have it in the cloud in a couple minutes. The MCP server is secured by design.
This project is a Python library for interacting with PostgreSQL databases on Azure. Users can easily connect to the database and execute queries. The documentation is comprehensive, making it user-friendly even for beginners.
This project showcases how to use the MCP protocol with Azure OpenAI. It provides a simple example to interact with OpenAI's API seamlessly via an MCP server and client.
This is a quick start guide that provides the basic building blocks to set up a remote Model Context Protocol (MCP) server using Azure Container Apps. The MCP server is built using Node.js and TypeScript, and it can be used to run various tools and services in a serverless environment.
This application is an MCP agent app written in .NET, utilizing Azure OpenAI. It connects with a remote MCP server written in TypeScript and features enhanced security. It runs on Azure Container Apps and is built using Blazor for the client app.
This project provides samples of AI agents and demonstrates a framework for automating various tasks. Users can easily create agents and apply them to specific business processes. The sample code is based on real-world business scenarios, promoting practical learning.
This is a quickstart template to easily build and deploy a custom remote MCP server to the cloud using Azure Functions with Python, and then load the MCP tools in Foundry Agent Service
This project is a comprehensive Java tutorial demonstrating the implementation of the Model Context Protocol (MCP) using a Quarkus server and LangChain4j client. It provides hands-on learning with a monkey species dataset and includes detailed guides for building MCP applications.
remote-mcp-functions-java is a library designed for implementing remote MCP (Multi-Core Processor) functionalities using Java. This library supports multi-threading and asynchronous communication, enabling efficient data processing. It particularly excels in remote operations and data synchronization, providing high performance in these scenarios.
