Integrate Cursor with Live Databricks Data via CData Connect AI

Cursor is an AI-powered code editor that embeds conversational and agent-style assistance alongside your development workflow. By extending Cursor with MCP (Model Context Protocol) tools, you can give its AI agents secure access to external systems such as APIs and databases.

Integrating Cursor with CData Connect AI via the built-in MCP server allows the editor's AI to query, analyze, and act on live Databricks data without copying data into the IDE. The result is a development experience where you can chat with your governed enterprise data directly from Cursor.

This article outlines how to configure Databricks connectivity in Connect AI, generate the required access token, register Connect AI's MCP Server in Cursor, and then use the AI chat pane to explore live Databricks data.

Getting Started

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Step 1: Configure Databricks connectivity for Cursor

Connectivity to Databricks from Cursor is made possible through CData Connect AI's Remote MCP Server. To interact with Databricks data from Cursor, start by creating and configuring a Databricks connection in CData Connect AI.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a connection in Connect AI

2. Select Databricks from the Add Connection panel
👁 Selecting data source

3. Enter the necessary authentication properties to connect to Databricks.

   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 a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab and update user-based permissions
👁 Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Cursor. It is best practice to create a separate PAT for each integration to maintain granular access control.

1. Click the gear icon () at the top right of the Connect AI app to open Settings
2. On the Settings page, go to the Access Tokens section and click Create PAT
3. Give the PAT a descriptive name and click Create
👁 Creating a new PAT

4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use

With the Databricks connection configured and a PAT generated, Cursor can now connect to Databricks data through Connect AI.

Step 2: Configure Connect AI in Cursor

Next, configure Cursor to use Connect AI. Cursor reads MCP configuration from an mcp.json file in the user configuration directory and exposes the registered servers under the Tools & MCP settings. Once configured, Cursor's AI chat can call the tools exposed by CData Connect AI.

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
   
4. Cursor opens an mcp.json file in the editor
5. Add the following configuration. Make sure to base64-encode your email:PAT before inserting into the header:

   {
    "mcpServers": {
    "cdata-mcp": {
    "url": "https://mcp.cloud.cdata.com/mcp",
    "headers": {
    "Authorization": "Basic your_base64_encoded_email_PAT"
    }
    }
    }
   }
   		

   👁 Configuring mcp.json with Connect AI
   
6. Save the file
7. Return to Settings and then select Tools & MCP. You can now see cdata-mcp enabled with an active indicator 👁 Connect AI enabled
   

Step 3: Chat with CData Connect AI from Cursor

1. From the top bar, click Toggle AI Pane to open the chat window 👁 Opening the AI pane
   
2. Test the connection by entering "List connections"
3. You can also run queries like "Query Databricks data and list the high priority accounts" 👁 Querying Databricks data from Connect AI
   

Cursor is now fully integrated with the CData Connect AI MCP Server and can act on live Databricks data directly from the editor.

Get CData Connect AI

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