Developers can effortlessly connect, interact, and generate data insights with BigQuery datasets and data using natural language commands.

• Why Use the BigQuery Data Analytics Extension?
• Prerequisites
• Getting Started
  • Antigravity
  • Claude Code
  • Codex
• Installing using open agent skills tool
• Installing via a compatible Agent Plugins client
• Usage Examples
• Supported Skills
• Additional Extensions
• Troubleshooting

• Natural Language to data analytics : Find required BigQuery tables and ask analytical questions in natural language.
• Seamless Workflow: Stay in your CLI. No need to constantly switch contexts to the GCP console for generating analytical insights.
• Run advanced analytics : Generate forecasts, run a contributions analysis using built-in advanced skills.

Before you begin, ensure you have the following:

• One of these AI agents installed
  • Antigravity
    • Antigravity CLI version v1.6.0 or higher
    • Antigravity 2.0 version v2.0.0 or higher.
  • Claude Code version v2.1.94 or higher.
  • Codex v0.117.0 or higher.
• A Google Cloud project with the BigQuery API enabled.
• Ensure Application Default Credentials are available in your environment.
• IAM Permissions:
  • BigQuery User (roles/bigquery.user)
• (Optional) To use BigQuery AI/ML skills
  • Ensure that Vertex AI API is enabled
  • IAM permissions:
    • BigQuery Connection User (roles/bigquery.connectionUser)
    • Vertex AI User (roles/aiplatform.user)

Please keep these env vars handy during the installation process:

• BIGQUERY_PROJECT: The GCP project ID.
• BIGQUERY_LOCATION: (Optional) The dataset location.

To start interacting with your database, install the skills for your preferred AI agent, then launch the agent and use natural language to ask questions or perform tasks.

For the latest version, check the releases page.

You can use either of these two agents for Antigravity:

• Antigravity CLI version v1.6.0 or higher
• Antigravity 2.0 version v2.0.0 or higher.

💡 Tip — Migrating from Gemini CLI?
If you previously installed this extension with gemini extensions install, you can convert it to an Antigravity plugin instead of reinstalling from scratch:

• On first launch of Antigravity CLI, accept the Migration Options prompt to automatically convert your installed Gemini CLI extensions to Antigravity plugins.
• Or, from your terminal, run:

  agy plugin import gemini

See Migrating from Gemini CLI for details on plugins, context files (GEMINI.md / AGENTS.md), and MCP server config differences.

1. Clone the Repo:

git clone --branch 0.2.1 https://github.com/gemini-cli-extensions/bigquery-data-analytics.git

2. Install the skills:

Choose a location for the skills:

• Global (all workspaces): ~/.gemini/antigravity/skills/
• Workspace-specific: <workspace-root>/.agents/skills/

Copy the skill folders from the cloned repository's skills/ directory to your chosen location:

cp -R bigquery-data-analytics/skills/* ~/.gemini/antigravity/skills/

3. Set env vars: Set your environment vars as described in the configuration section.

(Tip: Antigravity 2.0 automatically discovers skills in these directories at the start of a session. You can verify they are active by running the /skills command in your active session.)

You can install plugins directly from a remote GitHub repository.

1. Install the plugin:

agy plugin install https://github.com/gemini-cli-extensions/bigquery-data-analytics

2. Set env vars: Set your environment vars as described in the configuration section.

1. Set env vars: In your terminal, set your environment vars as described in the configuration section.

2. Start the agent:

claude

3. Install the plugin:

/plugin install bigquery-data-analytics@claude-plugins-official

(Tip: Run /plugin list inside Claude Code to verify the plugin is active, or /reload-plugins if you just installed it.)

1. Install marketplace:

codex plugin marketplace add GoogleCloudPlatform/data-agent-kit

2. Install the plugin:

codex plugin add bigquery-data-analytics@data-agent-kit

3. Set env vars: Enter your environment vars as described in the configuration section.

4. (Optional) Update the marketplace:

codex plugin marketplace upgrade data-agent-kit

You can install skills using the npx skills command.

1. Install the skills:

Run the following command in your terminal to automatically download and register the skills:

npx skills add https://github.com/gemini-cli-extensions/bigquery-data-analytics/tree/0.2.1

For detailed info check out the Skills npm package.

2. Set env vars: Set your environment vars as described in the configuration section.

This repository is a valid Agent Plugins (v1) plugin. Any Agent Plugins–compatible client can install it directly using its own built-in plugin command — no extra tooling required — by pointing at this repository:

https://github.com/gemini-cli-extensions/bigquery-data-analytics

Beyond harnesses covered by the native install above, compatible clients include VS Code, Cursor, GitHub Copilot, and Kiro. See your agent's documentation for its exact install command.

Set env vars: Set your environment vars as described in the configuration section.

Interact with BigQuery using natural language right from your IDE:

• Find Data:

  • "Find tables related to PyPi downloads"
  • "Find tables related to Google analytics data in the dataset bigquery-public-data"

• Generate Analytics and insights:

  • "Using bigquery-public-data.pypi.file_downloads show me the top 10 downloaded pypi packages this month."
  • “Using bigquery-public-data.pypi.file_downloads can you forecast downloads for the last four months of 2025 for package urllib3?”

This extension provides a comprehensive set of skills:

• bigquery-data: Use these skills when you need to handle large-scale data exploration and dataset management. Use when users need to find data assets or run SQL at scale. Provides metadata discovery and query execution across the data warehouse.
• bigquery-analytics: Use these skills when you need to handle advanced data intelligence and predictive tasks. Use when a user asks "why" data changed or needs future projections. Provides automated insight generation and time-series forecasting.
• bigquery-ai-ml: Use these skills for BigQuery AI and Machine Learning queries using standard SQL and AI.* functions. Provides capabilities for text generation, classification, semantic search, and forecasting using pre-trained models without needing to manage custom models.

Find additional extensions to support your entire software development lifecycle at github.com/gemini-cli-extensions, including:

• BigQuery Conversational Analytics
• and more!

Use gemini --debug to enable debugging.

Common issues:

• "failed to find default credentials: google: could not find default credentials.": Ensure Application Default Credentials are available in your environment. See Set up Application Default Credentials for more information.
• "✖ Error during discovery for server: MCP error -32000: Connection closed": The database connection has not been established. Ensure your configuration is set via environment variables.
• "✖ MCP ERROR: Error: spawn /Users/USER/.gemini/extensions/bigquery-data-analytics/toolbox ENOENT": The Toolbox binary did not download correctly. Ensure you are using Gemini CLI v0.6.0+.
• "cannot execute binary file": The Toolbox binary did not download correctly. Ensure the correct binary for your OS/Architecture has been downloaded. See Installing the server for more information.