Build Azure Data Lake Storage-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 Data Lake Storage, configuring the connection to Azure Data Lake Storage, connecting the Code Assist MCP add-on to Cursor, and querying live Azure Data Lake Storage data from within the editor.

Step 1: Download and install the CData Code Assist MCP for Azure Data Lake Storage

1. To begin, download the CData Code Assist MCP for Azure Data Lake Storage
2. Find and double-click the installer to begin the installation
3. Run the installer and follow the prompts to complete the installation

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

Step 2: Configure the connection to Azure Data Lake Storage

1. After installation, open the CData Code Assist MCP for Azure Data Lake Storage configuration wizard

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

   
2. In MCP Configuration > Configuration Name, either select an existing configuration or choose to create a new one
3. Name the configuration (e.g. "cdata_adls") and click OK

4. Enter the appropriate connection properties in the configuration wizard

   Authenticating to a Gen 1 DataLakeStore Account

   Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

   For this, an Active Directory web application is required. You can create one as follows:

   1. Sign in to your Azure Account through the .
   2. Select "Entra ID" (formerly Azure AD).
   3. Select "App registrations".
   4. Select "New application registration".
   5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
   6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
   7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

   To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen1.
   • Account: Set this to the name of the account.
   • OAuthClientId: Set this to the application Id of the app you created.
   • OAuthClientSecret: Set this to the key generated for the app you created.
   • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

   Authenticating to a Gen 2 DataLakeStore Account

   To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen2.
   • Account: Set this to the name of the account.
   • FileSystem: Set this to the file system which will be used for this account.
   • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
   
5. Click Connect to authenticate with Azure Data Lake Storage through OAuth
6. Then, click Save Configuration to save the Code Assist MCP add-on

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
3. In the left navigation, open the Tools & MCP tab and click 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 Data Lake Storage/lib/cdata.mcp.adls.jar",
        "cdata_adls"
      ]
    }
  }
}



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_adls").

Option 2: Copy the MCP configuration from the CData Code Assist MCP for Azure Data Lake Storage UI

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

2. Select Cursor from the AI MCP Tool dropdown

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

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

Step 4: Query live Azure Data Lake Storage data in Cursor

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

   "List all tables available in my Azure Data Lake Storage data connection."

   

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

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 Data Lake Storage data during development. When you're ready to move to production, CData Azure Data Lake Storage 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.