Integrating Cursor CLI with Databricks Data via CData CLI

Cursor is an AI editor and coding agent built by Anysphere that plans, writes, and reviews code using agents that understand your entire codebase. Cursor CLI brings these agentic capabilities natively to the terminal, allowing developers to run agents in any terminal, script, or editor without switching context. Its support for integrations and custom agent rules makes Cursor CLI well-suited for structured, multi-step workflows, making it a natural fit for connecting to external data sources through tools like CData CLI. By describing your data goals in plain language, Cursor's agent handles the full setup process from driver configuration to query execution without manual intervention at each step.

This article details step-by-step directions for how to connect Databricks to Cursor CLI through CData CLI.

Prerequisites

1. Cursor CLI installed
2. CData CLI installed
3. Access to Databricks

Getting Started

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Step 1: Download the skill (one-time setup)

Always use CData CLI with the official skill.

1. The official CData CLI Skill on GitHub can be downloaded using npx skills through the terminal:

   npx skills add CDataSoftware/cli-skills

2. Follow the prompts in the terminal to install for Cursor CLI.

Step 2: Set up the project directory

Create a project directory to contain all project files.

1. Navigate to your desired directory in the terminal and start a session with the agent command.

Step 3: Establish the driver and connection

Describe what you want to accomplish in this session with the CLI and Databricks data.

I would like to build a command line app that connects to Databricks and checks for updates from Customers. Make sure to include data from important columns like City and CompanyName.

This prompt automatically loads the skill and kicks off the following process. You can always manually prompt the agent for each of the following steps.

1. Driver setup: Cursor CLI checks for an existing CData Databricks driver, or searches and downloads a new one:

• cdatacli drivers list

• cdatacli drivers search Databricks

• 
  cdatacli drivers download --artifact-id <artifact-id>

2. Activation: Activate the Databricks driver with a single command for a trial or full license:

•  cdatacli drivers activate Databricks --name "<name>" --email "<email>" --trial
  

• cdatacli drivers activate Databricks --name "<name>" --email "<email>" --key "<product-key>"
  

3. Establish the connection: Check for existing Databricks connections or create a new one:

• cdatacli connection list

• cdatacli drivers activate Databricks --name "<name>" --email "<email>" --trial
  

4. Create a Databricks skill (if applicable): CData provides driver instructions for popular sources that can be used to create a source-specific skill to guide the agent through best practices for the driver.
• Run the following command to generate a skill file and save the output to your skills directory. You can choose to save the skill either at the project level or globally. (Note: If "No instructions available for Databricks data" error is returned, no driver instructions exist and you can continue to use main driver skill)

  cdatacli drivers skill Databricks > ~/skills/cdata-Databricks/SKILL.md

Step 4: Query Databricks data

With the CData driver fully configured, your agent can now execute queries and write code against live Databricks data:

1. 
   cdatacli query sql --connection <my_Databricks_connection> --sql <SELECT * FROM table>

Query Databricks data directly from your terminal with CData CLI

Cursor CLI and CData CLI together give your AI coding agent a direct path to live Databricks data without custom middleware, scheduled syncs, or manual setup at each step. Describe your goal, and the agent handles driver configuration, connection setup, and query execution from start to finish in the terminal.

Download the free CData CLI and start a free, 30-day trial of the CData JDBC Driver for Databricks today.