# BigQuery MCP Server The BigQuery Model Context Protocol (MCP) Server enables AI-powered development tools to seamlessly connect, interact, and generate data insights with your BigQuery datasets and data using natural language commands. ## Features An editor configured to use the BigQuery MCP server can use its AI capabilities to help you: - **Natural Language to Data Analytics:** Easily find required BigQuery tables and ask analytical questions in plain English. - **Seamless Workflow:** Stay within your CLI, eliminating the need to constantly switch to the GCP console for generating analytical insights. - **Run Advanced Analytics:** Generate forecasts and perform contribution analysis using built-in advanced tools. ## Prerequisites * [Node.js](https://nodejs.org/) installed. * A Google Cloud project with the **BigQuery API** enabled. * Ensure [Application Default Credentials](https://cloud.google.com/docs/authentication/gcloud) are available in your environment. * IAM Permissions: * BigQuery User (`roles/bigquery.user`) ## Install & Configuration 1. In the Antigravity MCP Store, click the "Install" button. > [!NOTE] > On first use, the installation process automatically downloads and uses > [MCP Toolbox](https://www.npmjs.com/package/@toolbox-sdk/server) > `>=0.26.0`. To update MCP Toolbox, use: > ```npm i -g @toolbox-sdk/server@latest``` > To always run the latest version, update the MCP server configuration to use: > ```npx -y @toolbox-sdk/server@latest --prebuilt bigquery```. 2. Add the required inputs in the configuration pop-up, then click "Save". You can update this configuration at any time in the "Configure" tab. > [!NOTE] > If you encounter issues with Windows Defender blocking the execution, you may need to configure an allowlist. See [Configure exclusions for Microsoft Defender Antivirus](https://learn.microsoft.com/en-us/microsoft-365/security/defender-endpoint/configure-exclusions-microsoft-defender-antivirus?view=o365-worldwide) for more details. You'll now be able to see all enabled tools in the "Tools" tab. ### Usage Once configured, the MCP server will automatically provide BigQuery capabilities to your AI assistant. You can: * **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?" ## Server Capabilities The BigQuery MCP server provides the following tools: | Tool Name | Description | |:-----------------------|:----------------------------------------------------------------| | `execute_sql` | Executes a SQL query. | | `forecast` | Forecast time series data. | | `get_dataset_info` | Get dataset metadata. | | `get_table_info` | Get table metadata. | | `list_dataset_ids` | Lists dataset IDs in the database. | | `list_table_ids` | Lists table IDs in the database. | | `analyze_contribution` | Perform contribution analysis, also called key driver analysis. | | `search_catalog` | Search for tables based on the provided query. | ## Custom MCP Server Configuration The BigQuery MCP server is configured using environment variables. ```bash export BIGQUERY_PROJECT="" export BIGQUERY_LOCATION="" # Optional export BIGQUERY_USE_CLIENT_OAUTH="true" # Optional export BIGQUERY_SCOPES="" # Optional ``` Add the following configuration to your MCP client (e.g., `settings.json` for Gemini CLI, `mcp_config.json` for Antigravity): ```json { "mcpServers": { "bigquery": { "command": "npx", "args": ["-y", "@toolbox-sdk/server", "--prebuilt", "bigquery", "--stdio"] } } } ``` ## Documentation For more information, visit the [BigQuery documentation](https://cloud.google.com/bigquery/docs).