Integration
Connect Beanstalk and Google BigQuery
When New Repository fires in Beanstalk, your agent runs Create Row in Google BigQuery, or New Job Completed in Google BigQuery to Get User in Beanstalk. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want Beanstalk and Google BigQuery to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. 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.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)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)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)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)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)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)Example flows
What Beanstalk and Google BigQuery can do together
From Beanstalk to Google BigQuery
When New Repository in Beanstalk
then Create Row in Google BigQuery
When New User in Beanstalk
then Create Rows in Google BigQuery
From Google BigQuery to Beanstalk
When New Job Completed in Google BigQuery
then Get User in Beanstalk
When New Row in Google BigQuery
then List Users in Beanstalk
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 Beanstalk and Google BigQuery
Triggers and actions 6 triggers · 17 actions
Trigger
New RepositoryPolls for newly created repositories.
Trigger
New UserPolls for newly added users.
Action
Add public keyAdd an SSH public key for Git authentication.
Action
Create RepositoryCreate a new repository in the Beanstalk account.
Action
Get RepositoryRetrieve a single repository by ID.
Action
Get UserRetrieve a single user by ID.
Action
List public keysList SSH public keys for users on the account.
Action
List RepositoriesList all repositories in the Beanstalk account.
Action
List UsersList all users in the Beanstalk account.
Trigger
New Job CompletedTriggers when a BigQuery job in the project finishes, whether it succeeded or failed.
Trigger
New RowTriggers 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 RowTriggers when a row in a table is added or changed, detected by a last-updated timestamp column you name.
Action
Create RowCreates a new row of data in a table. Note: Does not create a job.
Action
Create RowsCreates new rows of data in a table (accepts line items). Note: Does not create a job.
Action
Delete RowsDeletes every row in a table whose match column equals the value you give.
Action
Find One RowFinds the first row in a table whose column equals the value you give.
Action
Get Rows for Job CompletedReturns the result rows of a finished query job.
Action
Import DataImports 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 DatasetsReturns the datasets in a Google Cloud project.
Action
List TablesReturns the tables in a BigQuery dataset.
Action
Run a QueryRuns 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.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
What our customers say
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Questions
Beanstalk and Google BigQuery, answered
What can start an automation from Beanstalk?
Any of Beanstalk's 2 triggers in the catalog, including New Repository and New User. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Google BigQuery when something happens in Beanstalk?
Any of Google BigQuery's 10 actions, including Create Row, Create Rows, Get Rows for Job Completed and Update Row(s). Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Google BigQuery to Beanstalk?
Yes. When something happens in Google BigQuery, your agent can act in Beanstalk too. This page covers both directions: Google BigQuery's triggers and Beanstalk's actions are listed here as well.
Do I have to build a connector for Beanstalk or Google BigQuery?
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.
Can my AI client use Beanstalk and Google BigQuery without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
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.