# BigQuery Plugin > **Availability:** DataHub Cloud only > **Note**: Ask DataHub Plugins is currently in **Private Beta**. To enable this feature, please reach out to your DataHub customer support representative. The **BigQuery Plugin** connects Ask DataHub to [Google BigQuery](https://cloud.google.com/bigquery) via the [BigQuery MCP server](https://docs.cloud.google.com/bigquery/docs/use-bigquery-mcp), enabling conversational analytics directly from the chat. Like the Snowflake and Databricks plugins, DataHub acts as the **semantic layer** — finding the right data — while BigQuery serves as the **data layer** — executing queries and returning results. ## Why Connect BigQuery? With the BigQuery plugin enabled, Ask DataHub can: - **Conversational analytics** — ask questions in plain language and get answers backed by real data. DataHub finds the right tables using metadata (descriptions, ownership, lineage), then BigQuery executes the query. - **Data exploration** — understand dataset structure, preview sample data, and inspect column values to evaluate data quality or fitness for a use case. - **Data debugging** — investigate data issues detected by DataHub assertions by inspecting the actual data: check for nulls, duplicates, unexpected values, or freshness problems at the source. Because the plugin uses **Google OAuth**, each user authenticates with their own Google account. Users only see data they are authorized to access via IAM — no need to manage separate policies in DataHub. **Example prompts:** - _"Query the top 10 customers by revenue this quarter"_ - _"How many null values are in the email column of the customers table?"_ - _"Show me 5 sample rows from the orders table"_ - _"List all datasets in my project"_ ## Prerequisites - A Google Cloud project with the BigQuery API enabled - The [BigQuery MCP server enabled](https://docs.cloud.google.com/bigquery/docs/use-bigquery-mcp) in the project (see Step 1 below) - Users must have the [required IAM roles](https://docs.cloud.google.com/bigquery/docs/use-bigquery-mcp#required_roles) on the project (including `roles/bigquery.dataViewer`, `roles/bigquery.jobUser`, and `roles/mcp.toolUser`) - DataHub Cloud with Ask DataHub Plugins enabled - Platform admin access in DataHub to configure the plugin ## Admin Setup The BigQuery plugin uses **User OAuth** authentication — each user authenticates with their own Google account. Setup involves enabling the BigQuery MCP server, creating an OAuth client in Google Cloud, then configuring the plugin in DataHub. ### Step 1: Enable the BigQuery MCP Server Enable the BigQuery MCP server in your Google Cloud project using the [`gcloud` CLI](https://docs.cloud.google.com/sdk/docs/install): ```bash gcloud beta services mcp enable bigquery.googleapis.com \ --project=YOUR_PROJECT_ID ``` :::tip gcloud version This command requires a recent version of the gcloud CLI beta component. If you see `Invalid choice: 'mcp'`, run `gcloud components update` to update to the latest version. ::: For more details, see the [Google Cloud documentation](https://docs.cloud.google.com/mcp/enable-disable-mcp-servers). ### Step 2: Create an OAuth Client and Collect Credentials Create a **Web application** OAuth client in [Google Auth Platform > Clients](https://console.cloud.google.com/auth/clients). When configuring the client, add your DataHub OAuth callback URL as an **Authorized redirect URI**: ``` https:///integrations/oauth/callback ```

:::caution Redirect URI The **Authorized redirect URI** must match the OAuth Callback URL shown in the DataHub plugin creation form exactly (e.g. `https://your-org.acryl.io/integrations/oauth/callback`). You can copy this URL from the DataHub form when creating the plugin in Step 3. ::: After creating the client, copy the **Client ID** and **Client Secret** immediately — the client secret won't be shown again.

For detailed instructions, see [Obtain OAuth 2.0 credentials](https://developers.google.com/identity/protocols/oauth2#1.-obtain-oauth-2.0-credentials-from-the-dynamic_data.setvar.console_name.) in the Google documentation. ### Step 3: Create Plugin in DataHub 1. Navigate to **Settings > AI > Plugins** in DataHub 2. Click **+ Create** and select **Custom MCP** 3. Fill in the plugin details: | Field | Value | | ----------------------- | -------------------------------------- | | **Name** | `BigQuery` | | **Description** | A description for the plugin | | **MCP Server URL** | `https://bigquery.googleapis.com/mcp` | | **Authentication Type** | `User OAuth (Each user authenticates)` | 4. DataHub will automatically discover the OAuth configuration from Google. Provide the following: | Field | Value | | ------------------ | ------------------------------------------ | | **Client ID** | From Step 2 | | **Client Secret** | From Step 2 | | **Default Scopes** | `https://www.googleapis.com/auth/bigquery` |

:::info OAuth Scopes The `https://www.googleapis.com/auth/bigquery` scope grants read and write access to BigQuery. For a full list of available scopes, see [BigQuery OAuth scopes](https://developers.google.com/identity/protocols/oauth2/scopes#bigquery). ::: 5. Optionally add **Instructions for the AI Assistant**, ensure **Enable for Ask DataHub** is on, and click **Create** ## User Setup Navigate to **Settings > My AI Settings**, find the **BigQuery** plugin, and click **Connect**. You'll be redirected to Google to authenticate, then back to DataHub. See the [overview](./overview.md#user-setup-enabling-plugins) for more details. :::note OAuth Consent Screen If your OAuth consent screen is set to **Internal**, only users within your Google Workspace organization can authenticate. If set to **External** and not yet verified, users may see a warning — they can proceed by clicking **Advanced > Go to \**. For production use, consider [verifying the consent screen](https://support.google.com/cloud/answer/10311615). ::: ## Capabilities Once connected, Ask DataHub can use the BigQuery MCP server to: - **Run SQL queries** — execute SELECT queries against your BigQuery data (read-only; write operations are not supported) - **Browse datasets and tables** — list datasets in a project and tables in a dataset - **Inspect table metadata** — view schema, row counts, and other table details For the full list of available tools, see the [BigQuery MCP reference](https://docs.cloud.google.com/bigquery/docs/reference/mcp). ## Troubleshooting ### OAuth Fails - Verify the **Authorized redirect URI** in Google Cloud matches the OAuth Callback URL shown in DataHub exactly - Ensure the Client ID and Client Secret are entered correctly - Check that the [OAuth consent screen](https://console.cloud.google.com/auth/audience) is configured for your Google Cloud project ### Permission Errors - Ensure the user has the [required IAM roles](https://docs.cloud.google.com/bigquery/docs/use-bigquery-mcp#required_roles) on the project - Verify the BigQuery MCP server is enabled in the project ### Query Failures - Verify the user has access to the datasets and tables they're querying - Note that `execute_sql` queries are [limited to 3 minutes](https://docs.cloud.google.com/bigquery/docs/use-bigquery-mcp#limitations) by default — longer queries are canceled automatically - BigQuery MCP does not support querying Google Drive external tables