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Integrate MCP Tools with Azure AI Agents

  Integrate MCP Tools with Azure AI Agents Why Tool Discovery Matters As AI agents become more powerful, they need access to many tools and services Manually: Registering tools Updating integrations Managing authentication becomes complex and time-consuming Dynamic tool discovery solves this problem Microsoft Connector Protocol (MCP) What is MCP? MCP = Microsoft Connector Protocol A standard way for AI agents to: Discover tools Authenticate securely Use tools dynamically at runtime Advantages of MCP for AI Agents 1. Dynamic Tool Discovery AI agents automatically receive: List of available tools Tool descriptions and capabilities No hardcoded APIs in agent code “ Integrate once ” approach Reduces maintenance when tools change 2. Interoperability Across LLMs MCP works with multiple LLMs You can: Switch models Test different LLMs without rewriting integrations 3. Standardized Security MCP provides consiste...
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Develop an AI app with the Microsoft Foundry SDK

Develop an AI app with the Microsoft Foundry SDK Microsoft Foundry provides a REST API to work with: AI Foundry projects Resources inside those projects It also offers language-specific SDKs  to make coding easier. Using the SDK, developers can: Connect to a Foundry project Access project resources and models Perform AI operations (e.g., send prompts to generative AI models and process responses) Core SDK Library The main library is Azure AI Projects It allows you to: Connect to a Microsoft Foundry project Access all resources defined in the project Available SDKs: Azure AI Projects for Python Azure AI Projects for .NET Azure AI Projects for JavaScript Each SDK is developed independently, so features may differ slightly across languages. Language Used in This Module This module uses Python examples Equivalent examples are available in other SDK documentation Install the Azure AI SDK : pip install azure-ai-projects C...
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Build scalable data solutions with SQL database in Microsoft Fabric

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  Exercise 1 - Setting up the Environment Task-1: Create a New Fabric Workspace Task-2: Create a SQL Database in Microsoft Fabric Task-3: Load the database with Sample data Task-4: Working with the SQL database in Microsoft Fabric Task-5: Exploring SQL analytics Endpoint Exercise 2 - Copilot Capabilities for SQL database in Microsoft Fabric --Create a query to get the product that is selling the most Task-2: Copilot Quick Actions within the Query Window SELECT c.CustomerID, c.FirstName,c.LastName, COUNT(so.SalesOrderID) AS TotalPurchases, SUM(so.SubTotal) AS TotalSpent, AVG(so.SubTotal) AS AverageOrderValue, MAX(so.OrderDate) AS LastPurchaseDate FROM SalesLT.Customer AS c JOIN SalesLT.SalesOrderHeader AS so ON c.CustomerID = so.CustomerID GROUP BY c.CustomerID, c.FName, c.LName ORDER BY TotalSpent DESC; Task-3: Using Copilot Chat Pane - Natural Language to SQL Task-4: Chat Pane - Get results from Copilot Task-5: Chat Pane - Write (with approval) Exercise 3 - RAG Implementation with...
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