Build Azure Analysis Services-Powered Applications in Cursor with CData Code Assist MCP

Cursor is an AI-powered code editor that integrates agentic AI into everyday development workflows. With support for MCP, Cursor can connect to local tools and enterprise data sources directly from the editor, enabling natural language interaction with live systems without switching context.

Model Context Protocol (MCP) is an open standard for connecting LLM clients to external services through structured tool interfaces. MCP servers expose capabilities such as schema discovery and live querying, allowing AI agents to retrieve and reason over real-time data safely and consistently.

In this article, we guide you through installing the CData Code Assist MCP for Azure Analysis Services, configuring the connection to Azure Analysis Services, connecting the Code Assist MCP add-on to Cursor, and querying live Azure Analysis Services data from within the editor.

Step 1: Download and install the CData Code Assist MCP for Azure Analysis Services

1. To begin, download the CData Code Assist MCP for Azure Analysis Services 👁 Downloading the CData Code Assist MCP add-on installer
   
2. Find and double-click the installer to begin the installation
3. Run the installer and follow the prompts to complete the installation 👁 Completing the CData Code Assist MCP add-on installation
   

When the installation is complete, you are ready to configure your Code Assist MCP add-on by connecting to Azure Analysis Services.

Step 2: Configure the connection to Azure Analysis Services

1. After installation, open the CData Code Assist MCP for Azure Analysis Services configuration wizard 👁 The CData Code Assist MCP add-on configuration wizard
   

   NOTE: If the wizard does not open automatically, search for "CData Code Assist MCP for Azure Analysis Services" in the Windows search bar and open the application.

   👁 Opening the CData Code Assist MCP add-on configuration wizard (Google Sheets is shown).
   
2. In MCP Configuration > Configuration Name, either select an existing configuration or choose to create a new one 👁 Creating a new configuration
   
3. Name the configuration (e.g. "cdata_aas") and click OK 👁 Naming the configuration
   

4. Enter the appropriate connection properties in the configuration wizard

   To connect to Azure Analysis Services, set the Url property to a valid server, for instance, asazure://southcentralus.asazure.windows.net/server, in addition to authenticating. Optionally, set Database to distinguish which Azure database on the server to connect to.

   Azure Analysis Services uses the OAuth authentication standard. OAuth requires the authenticating user to interact with Azure Analysis Services using the browser. You can connect without setting any connection properties for your user credentials. See the Help documentation for more information.

   👁 Configuring the Code Assist MCP add-on connection
   
5. Click Connect to authenticate with Azure Analysis Services through OAuth
6. Then, click Save Configuration to save the Code Assist MCP add-on 👁 Saving the Code Assist MCP add-on configuration
   

This process creates a .mcp configuration file that Cursor will reference when launching the Code Assist MCP add-on. Now with your Code Assist MCP add-on configured, you are ready to connect it to Cursor.

Step 3: Connect the Code Assist MCP add-on to Cursor

1. Download the Cursor desktop application and complete the sign-up flow for your account
2. From the top menu, click Settings to open the settings panel 👁 Opening Cursor Settings
   
3. In the left navigation, open the Tools & MCP tab and click Add Custom MCP 👁 Tools & MCP tab with Add Custom MCP
   

Option 1: Manually add the MCP configuration

1. Cursor opens an mcp.json file in the editor
2. Add the code shown below and save the file

{
 "mcpServers": {
 "cdata-local": {
 "command": "C:/Program Files/Java/jdk-17/bin/java.exe",
 "args": [
 "-jar",
 "C:/Program Files/CData/CData Code Assist MCP for Azure Analysis Services/lib/cdata.mcp.aas.jar",
 "cdata_aas"
 ]
 }
 }
}

👁 Configuring the CData Code Assist MCP add-on in Cursor


NOTE: The command value should point to your Java 17+ java.exe executable, and the JAR path should point to the installed CData Code Assist MCP add-on .jar file. The final argument must match the MCP configuration name you saved in the CData configuration wizard (e.g. "cdata_aas").

Option 2: Copy the MCP configuration from the CData Code Assist MCP for Azure Analysis Services UI

1. After saving and testing your connection in the configuration wizard, click Next
👁 Selecting 'Next'

2. Select Cursor from the AI MCP Tool dropdown
👁 Choosing the required AI MCP tool

3. Follow the MCP Client Instructions to create the required folders for the MCP config
👁 MCP configuration instructions

4. Copy the displayed JSON code and paste it into your configuration file
5. In Cursor, open the project folder you created with the mcp.json config
4. The Code Assist MCP add-on should appear as Running under Installed MCP Servers 👁 CData Code Assist MCP add-on running in Cursor
   

Step 4: Query live Azure Analysis Services data in Cursor

1. From the top bar, click Toggle AI Pane to open the chat window
2. Ask questions about your Azure Analysis Services data using natural language. For example:

   "List all tables available in my Azure Analysis Services data connection."

   👁 Querying live data from Cursor
   

Cursor is now fully integrated with CData Code Assist MCP for Azure Analysis Services and can use the MCP tools exposed to explore schemas and execute live queries against Azure Analysis Services.

Build with Code Assist MCP. Deploy with CData Drivers.

Download Code Assist MCP for free and give your AI tools schema-aware access to live Azure Analysis Services data during development. When you're ready to move to production, CData Azure Analysis Services Drivers deliver the same SQL-based access with enterprise-grade performance, security, and reliability.

Visit the CData Community to share insights, ask questions, and explore what's possible with MCP-powered AI workflows.