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Connect your AI agent to Google BigQuery

Google BigQuery is a fully managed data warehouse for large-scale data analytics, offering fast SQL queries and machine learning capabilities on massive datasets

Set it up in Melso

  1. 1In Melso, open Settings → Agent Apps and hit Connect on Google BigQuery.
  2. 2Finish the OAUTH2 / GOOGLE_SERVICE_ACCOUNT sign-in in the window that opens. Melso stores the connection, not your credentials.
  3. 3Open your agent, go to its Agent Apps tab, and allow Google BigQuery.
  4. 4Give the agent a task. It calls Google BigQuery itself when the work needs it.
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Google BigQuery
googlebigquery
63
tools
0
triggers
OAUTH2 / GOOGLE_SERVICE_ACCOUNT
auth
#80
rank
DatabasesAnalytics
What you get

What Google BigQuery gives your agent

The tools, permissions, and events Google BigQuery exposes — the same ones your agent can use once the app is authorized.

What you sign in with

Google BigQuery connects with OAUTH2 / GOOGLE_SERVICE_ACCOUNT.

  • Client id
  • Client secret

Permissions

https://www.googleapis.com/auth/bigqueryhttps://www.googleapis.com/auth/cloud-platformhttps://www.googleapis.com/auth/userinfo.email

Tools Google BigQuery exposes

GOOGLEBIGQUERY_CANCEL_JOB

Cancel BigQuery Job

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.

GOOGLEBIGQUERY_CREATE_CAPACITY_COMMITMENT

Create Capacity Commitment

Tool to create a new capacity commitment resource in BigQuery Reservation. Use when you need to purchase compute capacity (slots) with a committed period of usage for BigQuery jobs. Supports various commitment plans (FLEX, MONTHLY, ANNUAL, THREE_YEAR) and editions (STANDARD, ENTERPRISE, ENTERPRISE_PLUS).

GOOGLEBIGQUERY_CREATE_CONNECTION

Create BigQuery Connection

Tool to create a new BigQuery connection to external data sources using the BigQuery Connection API. Use when setting up connections to AWS, Azure, Cloud Spanner, Cloud SQL, Salesforce DataCloud, or Apache Spark.

GOOGLEBIGQUERY_CREATE_DATA_EXCHANGE

Create Analytics Hub Data Exchange

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.

GOOGLEBIGQUERY_CREATE_DATAEXCHANGES_LISTINGS

Create Analytics Hub Listing

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.

GOOGLEBIGQUERY_CREATE_DATASET

Create BigQuery Dataset

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.

GOOGLEBIGQUERY_CREATE_LISTING

Create Analytics Hub Listing

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.

GOOGLEBIGQUERY_CREATE_LOCATIONS_DATAPOLICIES

Create BigQuery Data Policy (v2beta1)

Tool to create a new data policy under a project with specified location using the v2beta1 BigQuery Data Policy API. Use when you need to set up data masking rules or column-level security for sensitive data. The v2beta1 endpoint uses a nested request structure.

Example prompts

  • Use Google BigQuery to check recent changes and summarize them in the issue.
  • When a customer writes in, pull their data from Google BigQuery before replying.
  • Audit our open items in Google BigQuery and notify the channel of anything stale.

Useful links

  • Google BigQuery website
  • Melso Agent Apps docs

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