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URL: https://www.cdata.com/kb/tech/bigquery-jdbc-cli-cursor.rst

⇱ Integrating Cursor CLI with BigQuery Data via CData CLI

Integrating Cursor CLI with BigQuery 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 BigQuery to Cursor CLI through CData CLI.

Prerequisites

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

About BigQuery Data Integration

CData simplifies access and integration of live Google BigQuery data. Our customers leverage CData connectivity to:

  • Simplify access to BigQuery with broad out-of-the-box support for authentication schemes, including OAuth, OAuth JWT, and GCP Instance.
  • Enhance data workflows with Bi-directional data access between BigQuery and other applications.
  • Perform key BigQuery actions like starting, retrieving, and canceling jobs; deleting tables; or insert job loads through SQL stored procedures.

Most CData customers are using Google BigQuery as their data warehouse and so use CData solutions to migrate business data from separate sources into BigQuery for comprehensive analytics. Other customers use our connectivity to analyze and report on their Google BigQuery data, with many customers using both solutions.

For more details on how CData enhances your Google BigQuery experience, check out our blog post: https://www.cdata.com/blog/what-is-bigquery


Getting Started


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. 👁 Installing the CData CLI skill 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. 👁 Starting a Cursor CLI session

Step 3: Establish the driver and connection

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

I would like to build a command line app that connects to BigQuery and checks for updates from Orders. Make sure to include data from important columns like OrderName and Freight.

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 BigQuery driver, or searches and downloads a new one: 
    • cdatacli drivers list
    • cdatacli drivers search --driver "BigQuery"
    • cdatacli drivers download --artifact-id <artifact-id>
  2. Activation: Activate the BigQuery driver with a single command for a trial or full license: 
    •  cdatacli drivers activate "BigQuery" --name "<name>" --email "<email>" --trial

    • cdatacli drivers activate "BigQuery" --name "<name>" --email "<email>" --key "<product-key>"
  3. Establish the connection: Check for existing BigQuery connections or create a new one: 
    • cdatacli connection list
    • cdatacli connection create --driver GoogleBigQuery --name my_googlebigquery_connection --connectionstring "Prop1=value1;Prop2=value2;..."
  4. Create a BigQuery 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 BigQuery data" error is returned, no driver instructions exist and you can continue to use main driver skill) 
      cdatacli drivers skill "BigQuery" > ~/skills/cdata-googlebigquery/SKILL.md

Step 4: Query BigQuery data

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

  1. cdatacli query sql --connection my_googlebigquery_connection --sql "SELECT * FROM Orders"

Query BigQuery data directly from your terminal with CData CLI

Cursor CLI and CData CLI together give your AI coding agent a direct path to live BigQuery 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 Google BigQuery today.

Ready to get started?

Download a free trial of the Google BigQuery Driver to get started:

 Download Now

Learn more:

👁 Google BigQuery Icon
Google BigQuery JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Google BigQuery data including Tables and Datasets.