# Connect Google BigQuery to Checkly

When **New Job Completed** fires in [Google BigQuery](https://apiant.ai/connections/google-bigquery), your agent runs **Add alert channel** in [Checkly](https://apiant.ai/connections/checkly). Describe the whole flow and it is built, tested on every scenario and kept running.

Google BigQuery **4** triggers Google BigQuery **10** actions Checkly **22** actions

What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.

## What do you want Google BigQuery and Checkly to do together?

Give your AI client this address.

`https://mcp.apiant.ai`

Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.

### Set it up in your client

### Claude Code

Run this in the directory you want to work in.

`claude mcp add --transport http -s project apiant-ai https://mcp.apiant.ai`

Start Claude Code there, approve the server, and sign in in the browser page it opens.

[Claude Code guide (opens in a new tab)](https://apiant.ai/docs/mcp/claude-code)

### Claude, web and desktop

Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.

[Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp)

### Cursor

Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.

[Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp)

### Zed

Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.

[Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp)

### Codex and the ChatGPT desktop app

Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.

[Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp)

### Any other MCP client

Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.

[Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp)

Example flows

## What Google BigQuery can start in Checkly

- When **New Job Completed** in Google BigQuery then **Add alert channel** in Checkly
- When **New Row** in Google BigQuery then **Update alert channel** in Checkly

Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.

Everything your agent can do with Google BigQuery and Checkly

## Triggers and actions 4 triggers · 32 actions

- Trigger

**New Job Completed**

Triggers when a BigQuery job in the project finishes, whether it succeeded or failed.

- Trigger

**New Row**

Triggers when a new row is added to a table. New rows are detected by a column you name that increases for newer rows, such as a creation time or a sequential ID.

- Trigger

**Query Job Completed (With Row Data)**

Triggers when a SELECT query job in the project finishes successfully, and includes its result rows.

- Trigger

**Updated Row**

Triggers when a row in a table is added or changed, detected by a last-updated timestamp column you name.

- Action

**Create Row**

Creates a new row of data in a table. Note: Does not create a job.

- Action

**Create Rows**

Creates new rows of data in a table (accepts line items). Note: Does not create a job.

- Action

**Delete Rows**

Deletes every row in a table whose match column equals the value you give.

- Action

**Find One Row**

Finds the first row in a table whose column equals the value you give.

- Action

**Get Rows for Job Completed**

Returns the result rows of a finished query job.

- Action

**Import Data**

Imports a JSON, CSV, Avro or Parquet file from Cloud Storage into a table. Waits up to about 40 seconds for the import to finish; larger imports keep running in BigQuery and return state RUNNING.

- Action

**List Datasets**

Returns the datasets in a Google Cloud project.

- Action

**List Tables**

Returns the tables in a BigQuery dataset.

- Action

**Run a Query**

Runs a SQL query against a table in BigQuery.

- Action

**Update Row(s)**

Updates every row in a table whose match column equals the value you give, setting the columns you choose.

- Action

**Add alert channel**

Create a new alert channel (email, Slack, SMS, webhook, etc).

- Action

**Add check**

Create a new check (API, browser, URL, TCP, etc.).

- Action

**Add check group**

Create a new check group.

- Action

**Add maintenance window**

Create a maintenance window to suppress alerts during scheduled downtime.

- Action

**Add variable**

Create a new environment variable used by checks/scripts.

- Action

**Delete alert channel**

Delete an alert channel by id.

- Action

**Delete check**

Delete a check by id.

- Action

**Delete check group**

Delete a check group by id.

- Action

**Delete maintenance window**

Delete a maintenance window by id.

- Action

**Delete variable**

Delete an environment variable by key.

- Action

**Get check**

Retrieve a check by id.

- Action

**Get check group**

Retrieve a check group by id.

- Action

**Get check status**

Retrieve the current status (up/down/degraded) of a check.

- Action

**List alert channels**

List all alert channels in the account.

- Action

**List check groups**

List all check groups in the account.

- Action

**List check results**

List check results for a given check.

- Action

**List maintenance windows**

List all maintenance windows in the account.

- Action

**List status pages**

List all status pages in the account.

- Action

**Trigger check run**

Trigger an on-demand check session and return the run results.

- Action

**Update alert channel**

Update an existing alert channel by id.

- Action

**Update check**

Update an existing check by id.

- Action

**Update check group**

Update an existing check group by id.

## Each app on its own

- [ **Google BigQuery** BigQuery is Google's serverless and highly scalable enterprise data warehouse, designed to make all your...](https://apiant.ai/connections/google-bigquery)
- [ **Checkly** Synthetic monitoring platform for uptime, API, and browser checks with alerting and status pages.](https://apiant.ai/connections/checkly)

Reviews

## What our customers say

## More from Google BigQuery

- [ **Google BigQuery to HTML to Image** HTML to Image is a Powerful Image Generation API to convert HTML/CSS to Image and to take screenshots of...](https://apiant.ai/connect/google-bigquery-to-html-to-image)
- [ **Google BigQuery to PaperClean** Clean document photos for printing, remove shadows, fix lighting](https://apiant.ai/connect/google-bigquery-to-paperclean)
- [ **Google BigQuery to Resend** Resend is the email API for developers. It's designed for you to build, test, and send transactional and...](https://apiant.ai/connect/google-bigquery-to-resend)
- [ **Google BigQuery to TypeSafe** TypeSafe's Jev model answers typed questions about a piece of content and tells you how certain it is.](https://apiant.ai/connect/google-bigquery-to-typesafe)
- [ **Google BigQuery to HubSpot** HubSpot is your all-in-one stop for all of your marketing software needs.](https://apiant.ai/connect/google-bigquery-to-hubspot)
- [ **Google BigQuery to Salesforce** Salesforce is a leading enterprise customer relationship management (CRM) platform.](https://apiant.ai/connect/google-bigquery-to-salesforce)

## More into Checkly

- [ **HubSpot to Checkly** HubSpot is your all-in-one stop for all of your marketing software needs.](https://apiant.ai/connect/hubspot-to-checkly)
- [ **Salesforce to Checkly** Salesforce is a leading enterprise customer relationship management (CRM) platform.](https://apiant.ai/connect/salesforce-to-checkly)
- [ **Slack to Checkly** Slack is a messaging platform for teams. Post messages, manage channels, users, reminders, and react to...](https://apiant.ai/connect/slack-to-checkly)
- [ **Google Sheets to Checkly** Google Sheets](https://apiant.ai/connect/google-sheets-to-checkly)
- [ **Gmail to Checkly** Gmail is Google’s email service, featuring spam protection, search functions, and seamless integration with...](https://apiant.ai/connect/gmail-to-checkly)
- [ **Google Calendar to Checkly** Google Calendar is a time management tool providing scheduling features, event reminders, and integration...](https://apiant.ai/connect/google-calendar-to-checkly)

Questions

## Google BigQuery and Checkly, answered

###

### What can start an automation from Google BigQuery?

Any of Google BigQuery's 4 triggers in the catalog, including New Job Completed, New Row, Query Job Completed (With Row Data) and Updated Row. Describe the moment in plain language and your agent picks the right one.

###

### What can your agent do in Checkly when something happens in Google BigQuery?

Any of Checkly's 22 actions, including Update alert channel, Update check, Update check group and Add alert channel. Your agent maps the data both ways and tests every scenario before it ships.

###

### Can it also run from Checkly to Google BigQuery?

Checkly has no triggers in the catalog today, so automations start in Google BigQuery. If you need the other direction, ask: your agent reads Checkly's API documentation and adds it.

###

### Do I have to build a connector for Google BigQuery or Checkly?

No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.

###

### What happens when something fails?

Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.

###

### Is there a free plan?

Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.
