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

Getting Started

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Step 1: Download and install the CData Code Assist MCP for Databricks

1. To begin, download the CData Code Assist MCP for Databricks 👁 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 Databricks.

Step 2: Configure the connection to Databricks

1. After installation, open the CData Code Assist MCP for Databricks 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 Databricks" 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_databricks") and click OK 👁 Naming the configuration
   

4. Enter the appropriate connection properties in the configuration wizard

   To connect to a Databricks cluster, set the properties as described below.

   Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.

   • Server: Set to the Server Hostname of your Databricks cluster.
   • HTTPPath: Set to the HTTP Path of your Databricks cluster.
   • Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
   👁 Configuring the Code Assist MCP add-on connection
   
5. Click Connect to authenticate with Databricks
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 Databricks/lib/cdata.mcp.databricks.jar",
 "cdata_databricks"
 ]
 }
 }
}

👁 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_databricks").

Option 2: Copy the MCP configuration from the CData Code Assist MCP for Databricks 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 Databricks data in Cursor

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

   "List all tables available in my Databricks data connection."

   👁 Querying live data from Cursor
   

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

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 Databricks data during development. When you're ready to move to production, CData Databricks 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.