Google BigQuery

Tool to retrieve BigQuery dataset metadata including location via the datasets.get API. Use this before creating jobs/queries if the workflow has been failing with location mismatch to confirm the dataset's region and correct the job location accordingly.

Tool to retrieve information about a specific BigQuery job. Returns job configuration, status, and statistics. Use this to check job status after running queries or to get details about job execution.

Tool to get the results of a BigQuery query job via RPC. Use this to retrieve results after running a query, or to check job completion status and fetch paginated results.

Tool to fetch a BigQuery table's schema and metadata without querying row data. Use before generating SQL queries to avoid column name typos and confirm field types and nullable modes. This is especially useful when INFORMATION_SCHEMA access is restricted.

Tool to list datasets in a specific BigQuery project, including dataset locations. Use after identifying an accessible project to discover available datasets and their locations before querying. The dataset location is critical for avoiding location-related query/job errors.

Tool to list all jobs that you started in a BigQuery project. Job information is available for a six month period after creation. Jobs are sorted in reverse chronological order by creation time. Use to monitor query execution, track job statuses, and retrieve job history.

Tool to list all BigQuery ML models in a specified dataset. Requires READER dataset role. Use this to discover available models before getting detailed information via models.get method.

Tool to list BigQuery projects to which the user has been granted any project role. Returns projects with at least READ access. For enhanced capabilities, consider using the Resource Manager API.

Tool to list the content of a BigQuery table in rows via the REST API. Use this to retrieve actual data from a table without writing SQL queries. Returns paginated results with row data in the native BigQuery format.

Tool to list tables in a BigQuery dataset via the REST API. Use this early in exploration to discover accessible tables without relying on INFORMATION_SCHEMA, especially when SQL-based metadata queries are blocked or restricted. This provides a deterministic inventory of tables even when dataset-level permissions prevent INFORMATION_SCHEMA access.

Tool to create a new listing in a BigQuery Analytics Hub data exchange. Use when you need to share a BigQuery dataset with specific subscribers or make it available for discovery. The dataset must exist and be in the same region as the data exchange.

Tool to create a new BigQuery dataset with explicit location, labels, and description using the BigQuery Datasets API. Use when the workflow needs to set up a staging/warehouse dataset and correctness of region is critical to avoid downstream job location mismatches. Surfaces 409 Already Exists errors cleanly without retrying.

Tool to create a new user-defined routine (function or procedure) in a BigQuery dataset. Use when you need to define SQL, JavaScript, Python, Java, or Scala functions/procedures for reusable logic, data transformations, or custom masking. Supports scalar functions, table-valued functions, procedures, and aggregate functions with comprehensive type definitions.

Tool to create a new, empty table in a BigQuery dataset. Use when setting up data infrastructure for standard tables, external tables, views, or materialized views. Supports partitioning, clustering, and encryption configuration.

Tool to start a new asynchronous BigQuery job (query, load, extract, or copy). Use when you need to run a query as a job, load data from Cloud Storage, extract table data to GCS, or copy tables. For dry-run validation without execution, set dryRun to true in configuration.

Tool to start a new BigQuery load job with file upload. Uploads a file (CSV, JSON, etc.) and loads it into a BigQuery table in a single operation. Use when you need to upload data from a local file directly to BigQuery rather than loading from Cloud Storage.

Tool to stream data into BigQuery one record at a time without running a load job. Use when you need immediate data availability or inserting small batches. Supports row-level deduplication via insertId and error handling via skipInvalidRows.

Tool to create a new Analytics Hub data exchange for sharing BigQuery datasets. Use when you need to set up a container for data sharing with descriptive information and listings.

Tool to create a new listing in a data exchange using Analytics Hub API. Use when publishing a BigQuery dataset to make it available for subscription by other users or organizations.

Tool to create a new query template in a BigQuery Analytics Hub Data Clean Room (DCR) data exchange. Use when you need to define predefined and approved queries for data clean room use cases. Query templates must be created in DCR data exchanges only.

Tool to update an existing BigQuery dataset using RFC5789 PATCH semantics. Only replaces fields provided in the request, leaving other fields unchanged. Use when you need to modify dataset properties like description, labels, expiration settings, or access controls without affecting other configuration.

Tool to update specific fields in an existing BigQuery ML model using PATCH semantics. Use when you need to modify model metadata like description, friendly name, labels, or expiration time without replacing the entire model resource.

Tool to update specific fields in an existing BigQuery table using RFC5789 PATCH semantics. Only the fields provided in the request are updated; unspecified fields remain unchanged. Use when you need to modify table metadata like description, friendly name, labels, or expiration time without replacing the entire table resource.

Tool to undelete a BigQuery dataset within the time travel window. If a deletion time is specified, the dataset version deleted at that time is undeleted; otherwise, the most recently deleted version is restored.

Tool to update information in an existing BigQuery dataset using the PUT method. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. Use when you need to modify dataset properties like description, access controls, or default settings.

Tool to update an existing BigQuery table. The update method replaces the entire Table resource, whereas the patch method only replaces fields that are provided. Use when you need to modify table properties like schema, description, labels, partitioning, or clustering configuration.

Tool to set the IAM access control policy for a BigQuery routine resource. Use this to grant or modify access permissions for users, service accounts, or groups. Include the etag from getIamPolicy to prevent concurrent modifications.

Tool to update a specified BigQuery connection using the BigQuery Connection API. Use when you need to modify connection properties such as friendly name, description, or connection-specific settings. For security reasons, credentials are automatically reset if connection properties are included in the update mask.

Tool to update an existing BigQuery routine (function or stored procedure). This replaces the entire routine resource with the provided definition. Use when modifying routine logic, arguments, return types, or other configuration. Ensure all required fields are provided as this is a full replacement operation.

Tool to delete a BigQuery dataset specified by datasetId via the datasets.delete API. Before deletion, you must delete all tables unless deleteContents=True is specified. Use when cleaning up test datasets or removing unused data warehouses. Immediately after deletion, you can create another dataset with the same name.

Tool to delete a BigQuery ML model from a dataset. Use when you need to remove a trained machine learning model permanently. The operation deletes the model and cannot be undone.

Tool to delete a BigQuery table from a dataset. Use when you need to remove a table and all its data permanently. The operation deletes all data in the table and cannot be undone.

Tool to cancel a running BigQuery job. This call returns immediately, and you need to poll for the job status to see if the cancel completed successfully. Note that cancelled jobs may still incur costs.

Tool to delete the metadata of a BigQuery job. Use when you need to remove job metadata from the system. If this is a parent job with child jobs, metadata from all child jobs will be deleted as well.

Tool to delete a BigQuery routine by its ID. Use when you need to remove a stored procedure, user-defined function, or table function from a dataset. This operation is irreversible.