Google BigQuery

Google BigQuery MCP integration

Reads a table's schema and runs the SQL a question needs, creates datasets and streams in rows, cancels long-running jobs, and reports who has access.

Connect Google BigQuerySee all integrations

63actions available

Three actions you can hand over today

Every action runs live through MCP. Nothing to build, nothing to maintain.

  • Query

    Lyro runs a SQL query to pull the exact data you need from BigQuery in seconds. You get live results to answer customer questions without waiting for dashboard refreshes.

  • Cancel bigquery job

    Lyro stops a long-running BigQuery query that's consuming resources or no longer needed. The job terminates immediately and frees up slots for other work.

  • Insert bigquery job

    Lyro launches a new query, load, or pipeline job in BigQuery asynchronously without blocking. Results arrive when the job completes so you can check them later.

See all 63 actions

How businesses use Google BigQuery + Lyro

Each card is one request a support team gets, and the Google BigQuery actions Lyro runs to close it.

  • Answer the question with actual SQL

    Lyro fetches the table schema first so the query references real columns, runs the SQL, and returns the result rows, which keeps an ad-hoc data question from becoming a ticket for the analytics team.

    Get BigQuery Table SchemaQueryGet BigQuery Query Results

  • Land new data without a pipeline change

    Lyro creates the dataset in the right location, defines the table, and streams records into it one at a time, so a small feed can start collecting before anyone builds a load job for it.

    Create BigQuery DatasetCreate BigQuery TableInsert Data into BigQuery Table

  • Keep an eye on what is running

    Lyro lists the jobs started in a project, reports the configuration and status of the one someone is asking about, and cancels a query that is burning slots for no useful result.

    List BigQuery JobsGet BigQuery JobCancel BigQuery Job

  • Check who can see a table before sharing it

    Lyro reads the IAM policy on a table, lists the row access policies filtering what each caller sees, and tests which permissions the connected account itself holds on a routine.

    Get BigQuery Table IAM PolicyList BigQuery Row Access PoliciesTest BigQuery Routine IAM Permissions

How it works

Get started in 3 steps

Connect once, then just ask. There is no workflow builder to learn and nothing to maintain — Lyro reads the Google BigQuery actions it has and picks the ones a request needs.

  1. 01

    Connect Google BigQuery

    Authorize the Google BigQuery account your team already uses — one consent screen, no API keys, no mapping tables. Lyro can only do what you granted that account, and you can disconnect it at any time.

  2. 02

    Tell your agent what you need

    Describe the job the way you would hand it to a teammate. Lyro maps it to the Google BigQuery actions that close it and chains as many as the request needs.

  3. 03

    Watch it work

    The agent runs the actions inside the conversation the customer is already in, so nobody copies data between tabs and your team can take over at any point.

    Get started free
Google BigQuery · Lyro

Everything else about Google BigQuery

Setup, permissions, and the limits of what Lyro can do inside Google BigQuery.

  • Insert BigQuery Job starts a query, load, extract, or copy asynchronously, Get BigQuery Job reports its status, and Get BigQuery Query Results fetches the rows once it completes. Cancel BigQuery Job returns immediately and the real state still has to be polled, so Lyro reports a cancellation as in progress rather than done.

Every action available in Google BigQuery

All 63 actions your agent can call on Google BigQuery, straight from the live MCP connection.

  • Cancel bigquery job

    Cancel a running BigQuery job.

  • Create capacity commitment

    Create a new capacity commitment resource in BigQuery Reservation.

  • Create bigquery connection

    Create a new BigQuery connection to external data sources using the BigQuery Connection API.

  • Create analytics hub data exchange

    Create a new Analytics Hub data exchange for sharing BigQuery datasets.

  • Create analytics hub listing

    Create a new listing in a BigQuery Analytics Hub data exchange.

  • Create bigquery dataset

    Create a new BigQuery dataset with explicit location, labels, and description using the BigQuery Datasets API.

  • Create analytics hub listing

    Create a new listing in a data exchange using Analytics Hub API.

  • Create bigquery data policy (v2beta1)

    Create a new data policy under a project with specified location using the v2beta1 BigQuery Data Policy API.

  • Create analytics hub query template

    Create a new query template in a BigQuery Analytics Hub Data Clean Room (DCR) data exchange.

  • Create bigquery reservation

    Create a new BigQuery reservation resource to guarantee compute capacity (slots) for query and pipeline jobs.

  • Create bigquery reservation assignment

    Create a BigQuery reservation assignment that allows a project, folder, or organization to submit jobs using slots from a specified reservation.

  • Create bigquery routine

    Create a new user-defined routine (function or procedure) in a BigQuery dataset.

  • Create bigquery table

    Create a new, empty table in a BigQuery dataset.

  • Delete bigquery dataset

    Delete a BigQuery dataset specified by datasetId via the datasets.delete API.

  • Delete bigquery job metadata

    Delete the metadata of a BigQuery job.

  • Delete bigquery ml model

    Delete a BigQuery ML model from a dataset.

  • Delete bigquery routine

    Delete a BigQuery routine by its ID.

  • Delete bigquery table

    Delete a BigQuery table from a dataset.

  • Get bigquery ml model

    Retrieve a specific BigQuery ML model resource by model ID.

  • Get bigquery connection iam policy

    Get the IAM access control policy for a BigQuery connection resource.

  • Get bigquery dataset metadata

    Retrieve BigQuery dataset metadata including location via the datasets.get API.

  • Get bigquery job

    Retrieve information about a specific BigQuery job.

  • Get bigquery query results

    Get the results of a BigQuery query job via RPC.

  • Get bigquery routine

    Retrieve a BigQuery routine (user-defined function or stored procedure) by its ID.

  • Get bigquery routine iam policy

    Retrieve the IAM access control policy for a BigQuery routine resource.

  • Get bigquery service account

    Get the service account for a project used for interactions with Google Cloud KMS.

  • Get bigquery table iam policy

    Retrieve the IAM access control policy for a BigQuery table resource.

  • Get bigquery table schema

    Fetch a BigQuery table's schema and metadata without querying row data.

  • Insert data into bigquery table

    Stream data into BigQuery one record at a time without running a load job.

  • Insert bigquery job

    Start a new asynchronous BigQuery job (query, load, extract, or copy).

The tools Google BigQuery sits next to

Same connection, same setup. Pick the next one your team already uses.

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Ready to connect Google BigQuery?

Authorize the account and your agent has all 63 actions from the first conversation.

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