Can I limit what agents can do in Google BigQuery?

Yes, twice over. The connection itself has an access level (Read-only, Read + write), and on top of that you can allow, scope, or deny each individual agent from the Integrations page.

Can I connect more than one Google BigQuery account?

Yes. Connect additional accounts from the same card and mark one as primary; agents use the primary unless a mission names a specific account.

How do I disconnect Google BigQuery?

Open Integrations, choose the account under Google BigQuery, and revoke it. Agents lose access immediately; nothing keeps working in the background.

Analytics

🧮 Google BigQuery integration

Access levels: Read-only · Read + write · Verified July 15, 2026

Connect Google BigQuery once and every agent in your squad can work in it for you, with exactly as much access as you decide to give, and a receipt for every call it makes.

What your squad can do in Google BigQuery

Look things up, get bigquery model; get connection iam policy; get dataset, and more.
Do real work, create capacity commitment; create connection; create dataexchanges listings; create dataset, and more.
Run it on a schedule: any of the 57 available tools below can be part of a scheduled task or a mission.

How to connect

In your dashboard, open Integrations and find Google BigQuery.
Click Connect and pick an access level (we recommend Read-only): this is the ceiling for every agent.
Sign in to Google BigQuery in the window that opens and approve. You land back on the Integrations page with the account live.

You can change an account's access level any time under Manage. It applies instantly, no re-authorization. If the connection ever expires, the card shows Reconnect; one click re-authorizes the same account with the same settings.

Multiple accounts: connect as many as you need (say, yours and a client's). One is primary. Agents use it unless a mission says otherwise.

Access levels

The level you pick at connect time is enforced on our side for every agent call: an agent can never do more than the level allows, no matter what it's asked.

Level	What it allows
Read-only	Run queries and view data.	Recommended
Read + write	Query, insert, and manage data.

On top of the connection's level, every agent can be individually allowed, scoped down, or denied for this app from the Integrations page. Deny an agent and it doesn't even see the connection.

Every tool, in plain terms

The 57 tools agents use in Google BigQuery through Mission Control, and the lowest access level that includes each. Agents discover these themselves. You never have to name a tool; asking in plain language is enough. A few rows are marked "Not currently enabled": Google BigQuery offers them, but no access level includes them yet, so agents can't run them.

Tool	What it does	Access level
Cancel job `GOOGLEBIGQUERY_CANCEL_JOB`	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.	Not currently enabled
Create capacity commitment `GOOGLEBIGQUERY_CREATE_CAPACITY_COMMITMENT`	Create a new capacity commitment resource in BigQuery Reservation.	Read + write
Create connection `GOOGLEBIGQUERY_CREATE_CONNECTION`	Create a new BigQuery connection to external data sources using the BigQuery Connection API.	Read + write
Create dataexchanges listings `GOOGLEBIGQUERY_CREATE_DATAEXCHANGES_LISTINGS`	Create a new listing in a BigQuery Analytics Hub data exchange.	Read + write
Create dataset `GOOGLEBIGQUERY_CREATE_DATASET`	Create a new BigQuery dataset with explicit location, labels, and description using the BigQuery Datasets API.	Read + write
Create data exchange `GOOGLEBIGQUERY_CREATE_DATA_EXCHANGE`	Create a new Analytics Hub data exchange for sharing BigQuery datasets.	Read + write
Create listing `GOOGLEBIGQUERY_CREATE_LISTING`	Create a new listing in a data exchange using Analytics Hub API.	Read + write
Create locations datapolicies `GOOGLEBIGQUERY_CREATE_LOCATIONS_DATAPOLICIES`	Create a new data policy under a project with specified location using the v2beta1 BigQuery Data Policy API.	Read + write
Create query template `GOOGLEBIGQUERY_CREATE_QUERY_TEMPLATE`	Create a new query template in a BigQuery Analytics Hub Data Clean Room (DCR) data exchange.	Read + write
Create reservation `GOOGLEBIGQUERY_CREATE_RESERVATION`	Create a new BigQuery reservation resource to guarantee compute capacity (slots) for query and pipeline jobs.	Read + write
Create reservation assignment `GOOGLEBIGQUERY_CREATE_RESERVATION_ASSIGNMENT`	Create a BigQuery reservation assignment that allows a project, folder, or organization to submit jobs using slots from a specified reservation.	Read + write
Create routine `GOOGLEBIGQUERY_CREATE_ROUTINE`	Create a new user-defined routine (function or procedure) in a BigQuery dataset.	Read + write
Create table `GOOGLEBIGQUERY_CREATE_TABLE`	Create a new, empty table in a BigQuery dataset.	Read + write
Delete dataset `GOOGLEBIGQUERY_DELETE_DATASET`	Delete a BigQuery dataset specified by datasetId via the datasets.delete API.	Not currently enabled
Delete job metadata `GOOGLEBIGQUERY_DELETE_JOB_METADATA`	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.	Not currently enabled
Delete model `GOOGLEBIGQUERY_DELETE_MODEL`	Delete a BigQuery ML model from a dataset.	Not currently enabled
Delete routine `GOOGLEBIGQUERY_DELETE_ROUTINE`	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.	Not currently enabled
Delete table `GOOGLEBIGQUERY_DELETE_TABLE`	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.	Not currently enabled
Get bigquery model `GOOGLEBIGQUERY_GET_BIGQUERY_MODEL`	Retrieve a specific BigQuery ML model resource by model ID.	All levels
Get connection iam policy `GOOGLEBIGQUERY_GET_CONNECTION_IAM_POLICY`	Get the IAM access control policy for a BigQuery connection resource.	All levels
Get dataset `GOOGLEBIGQUERY_GET_DATASET`	Retrieve BigQuery dataset metadata including location via the datasets.get API.	All levels
Get job `GOOGLEBIGQUERY_GET_JOB`	Retrieve information about a specific BigQuery job.	All levels
Get query results `GOOGLEBIGQUERY_GET_QUERY_RESULTS`	Get the results of a BigQuery query job via RPC.	All levels
Get routine `GOOGLEBIGQUERY_GET_ROUTINE`	Retrieve a BigQuery routine (user-defined function or stored procedure) by its ID.	All levels
Get routine iam policy `GOOGLEBIGQUERY_GET_ROUTINE_IAM_POLICY`	Retrieve the IAM access control policy for a BigQuery routine resource.	All levels
Get service account `GOOGLEBIGQUERY_GET_SERVICE_ACCOUNT`	Get the service account for a project used for interactions with Google Cloud KMS.	All levels
Get table iam policy `GOOGLEBIGQUERY_GET_TABLE_IAM_POLICY`	Retrieve the IAM access control policy for a BigQuery table resource.	All levels
Get table schema `GOOGLEBIGQUERY_GET_TABLE_SCHEMA`	Fetch a BigQuery table's schema and metadata without querying row data.	All levels
Insert all `GOOGLEBIGQUERY_INSERT_ALL`	Stream data into BigQuery one record at a time without running a load job.	Read + write
Insert job `GOOGLEBIGQUERY_INSERT_JOB`	Start a new asynchronous BigQuery job (query, load, extract, or copy).	Read + write
Insert job with upload `GOOGLEBIGQUERY_INSERT_JOB_WITH_UPLOAD`	Start a new BigQuery load job with file upload.	Read + write
List analytics hub listings `GOOGLEBIGQUERY_LIST_ANALYTICS_HUB_LISTINGS`	List all listings in a given Analytics Hub data exchange.	All levels
List big query connections `GOOGLEBIGQUERY_LIST_BIG_QUERY_CONNECTIONS`	List BigQuery connections in a given project and location.	All levels
List capacity commitments `GOOGLEBIGQUERY_LIST_CAPACITY_COMMITMENTS`	List all capacity commitments for the admin project.	All levels
List dataexchanges listings `GOOGLEBIGQUERY_LIST_DATAEXCHANGES_LISTINGS`	List all listings in a given Analytics Hub data exchange using the v1beta1 API.	All levels
List datasets `GOOGLEBIGQUERY_LIST_DATASETS`	List datasets in a specific BigQuery project, including dataset locations.	All levels
List jobs `GOOGLEBIGQUERY_LIST_JOBS`	List all jobs that you started in a BigQuery project.	All levels
List locations `GOOGLEBIGQUERY_LIST_LOCATIONS`	List information about supported locations for BigQuery Data Transfer Service.	All levels
List locations connections `GOOGLEBIGQUERY_LIST_LOCATIONS_CONNECTIONS`	List BigQuery connections in a given project and location using the v1beta1 API.	All levels
List locations datapolicies `GOOGLEBIGQUERY_LIST_LOCATIONS_DATAPOLICIES`	List all data policies in a specified parent project and location using the v2beta1 API.	All levels
List models `GOOGLEBIGQUERY_LIST_MODELS`	List all BigQuery ML models in a specified dataset.	All levels
List organization data exchanges `GOOGLEBIGQUERY_LIST_ORGANIZATION_DATA_EXCHANGES`	List all data exchanges from projects in a given organization and location using Analytics Hub API.	All levels
List projects `GOOGLEBIGQUERY_LIST_PROJECTS`	List BigQuery projects to which the user has been granted any project role.	All levels
List query templates `GOOGLEBIGQUERY_LIST_QUERY_TEMPLATES`	List all query templates in a given Analytics Hub data exchange.	All levels
List reservations `GOOGLEBIGQUERY_LIST_RESERVATIONS`	List all BigQuery reservations for a project in a specified location.	All levels
List reservation assignments `GOOGLEBIGQUERY_LIST_RESERVATION_ASSIGNMENTS`	List BigQuery reservation assignments. Only explicitly created assignments will be returned (no expansion or merge happens). Use wildcard "-" in parent path to list assignments across all reservations in a location.	All levels
List reservation groups `GOOGLEBIGQUERY_LIST_RESERVATION_GROUPS`	List all BigQuery reservation groups for a project in a specified location.	All levels
List routines `GOOGLEBIGQUERY_LIST_ROUTINES`	List all routines (user-defined functions and stored procedures) in a BigQuery dataset.	All levels
List row access policies `GOOGLEBIGQUERY_LIST_ROW_ACCESS_POLICIES`	List all row access policies on a specified BigQuery table.	All levels
List tables `GOOGLEBIGQUERY_LIST_TABLES`	List tables in a BigQuery dataset via the REST API.	All levels
List table data `GOOGLEBIGQUERY_LIST_TABLE_DATA`	List the content of a BigQuery table in rows via the REST API.	All levels
Patch dataset `GOOGLEBIGQUERY_PATCH_DATASET`	Update an existing BigQuery dataset using RFC5789 PATCH semantics.	Read + write
Patch model `GOOGLEBIGQUERY_PATCH_MODEL`	Update specific fields in an existing BigQuery ML model using PATCH semantics.	Read + write
Patch table `GOOGLEBIGQUERY_PATCH_TABLE`	Update specific fields in an existing BigQuery table using RFC5789 PATCH semantics.	Read + write
Query `GOOGLEBIGQUERY_QUERY`	Query Tool runs a SQL query in BigQuery using the REST API.	All levels
Search all assignments `GOOGLEBIGQUERY_SEARCH_ALL_ASSIGNMENTS`	Search all BigQuery reservation assignments for a specified resource in a particular region.	All levels
Set routine iam policy `GOOGLEBIGQUERY_SET_ROUTINE_IAM_POLICY`	Set the IAM access control policy for a BigQuery routine resource.	Read + write
Test routine iam permissions `GOOGLEBIGQUERY_TEST_ROUTINE_IAM_PERMISSIONS`	Test which IAM permissions the caller has on a BigQuery routine.	All levels
Undelete dataset `GOOGLEBIGQUERY_UNDELETE_DATASET`	Undelete a BigQuery dataset within the time travel window.	Read + write
Update connection `GOOGLEBIGQUERY_UPDATE_CONNECTION`	Update a specified BigQuery connection using the BigQuery Connection API.	Read + write
Update dataset `GOOGLEBIGQUERY_UPDATE_DATASET`	Update information in an existing BigQuery dataset using the PUT method.	Read + write
Update routine `GOOGLEBIGQUERY_UPDATE_ROUTINE`	Update an existing BigQuery routine (function or stored procedure).	Read + write
Update table `GOOGLEBIGQUERY_UPDATE_TABLE`	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, descrip…	Read + write

What agents can't do in Google BigQuery (yet)

Anything not in the table above. The tools mirror what Google BigQuery makes available to connected apps. If Google BigQuery doesn't expose an operation, agents can't perform it either.
If something you need is missing, there's usually a path: add the service's API key under Settings → Custom integrations and your agents can call it directly. See custom integrations & secrets. You can also ask your lead agent to open a ticket describing what it needs.

Using it in missions

Just ask in plain language: “check Google BigQuery for …”, “create … in Google BigQuery”, “every Monday, … ”, and the agent finds the right tool, runs it, and reports back with a receipt in your Runs ledger. Anything outward-facing (sending, posting, publishing) that a mission didn't clearly authorize comes back to you as a ticket first.

Troubleshooting

Agent says	What's happening	Fix
"Google BigQuery isn't connected"	No active connection (or this agent is denied)	Connect on the Integrations page; check the agent's per-app policy
"The connection has expired"	Google BigQuery ended the authorization (they all do periodically)	Click Reconnect on the account, same settings, one click
"I'm not allowed to do that"	The action is above the account's access level, or the agent is scoped down	Raise the level under Manage, or adjust that agent's policy
It did something unexpected	The ask was ambiguous (e.g. matched an existing item)	Be explicit, "create a NEW …", and give agents a working folder where relevant