Integrating Cursor CLI with Azure Data Lake Storage Data via CData CLI

Justin Floyd
Justin Floyd
Product Business Analyst
CData CLI gives AI coding agents direct, command-line-native access to CData Drivers across hundreds of data sources, allowing agents to manage licenses, configure connections, run SQL queries, and explore schema metadata, all without leaving the terminal.

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 Azure Data Lake Storage to Cursor CLI through CData CLI.

Prerequisites

  1. Cursor CLI installed
  2. CData CLI installed
  3. Access to Azure Data Lake Storage

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 Azure Data Lake Storage data.

I would like to build a command line app that connects to Azure Data Lake Storage and checks for updates from Resources. Make sure to include data from important columns like FullPath and Permission.

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 Azure Data Lake Storage driver, or searches and downloads a new one:
    • cdatacli drivers list
    • cdatacli drivers search Azure Data Lake Storage
    • 
      cdatacli drivers download --artifact-id <artifact-id>
  2. Activation: Activate the Azure Data Lake Storage driver with a single command for a trial or full license:
    •  cdatacli drivers activate Azure Data Lake Storage --name "<name>" --email "<email>" --trial
      
    • cdatacli drivers activate Azure Data Lake Storage --name "<name>" --email "<email>" --key "<product-key>"
      
  3. Establish the connection: Check for existing Azure Data Lake Storage connections or create a new one:
    • cdatacli connection list
    • cdatacli drivers activate Azure Data Lake Storage --name "<name>" --email "<email>" --trial
      
  4. Create a Azure Data Lake Storage 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 Azure Data Lake Storage data" error is returned, no driver instructions exist and you can continue to use main driver skill)
      cdatacli drivers skill Azure Data Lake Storage > ~/skills/cdata-Azure Data Lake Storage/SKILL.md

Step 4: Query Azure Data Lake Storage data

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

  1. 
    cdatacli query sql --connection <my_Azure Data Lake Storage_connection> --sql <SELECT * FROM table>

Query Azure Data Lake Storage data directly from your terminal with CData CLI

Cursor CLI and CData CLI together give your AI coding agent a direct path to live Azure Data Lake Storage 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 Azure Data Lake Storage today.

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