Integration
Connect Google BigQuery and Mateo
When New Job Completed fires in Google BigQuery, your agent runs Add Contact to List in Mateo, or Contact Created in Mateo to Create Row in Google BigQuery. 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 Google BigQuery and Mateo 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)Grok
Open grok.com/connectors, choose New Connector, then Custom, and paste the address. Grok signs you in in your browser.
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 Google BigQuery and Mateo can do together
From Google BigQuery to Mateo
When New Job Completed in Google BigQuery
then Add Contact to List in Mateo
When New Row in Google BigQuery
then Create Contact Details in Mateo
From Mateo to Google BigQuery
When Contact Created in Mateo
then Create Row in Google BigQuery
When Contact Details Updated in Mateo
then Create Rows in Google BigQuery
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 Mateo
Triggers and actions 10 triggers · 40 actions
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.
Trigger
Contact CreatedTriggers when a new contact is created in hellomateo.
Trigger
Contact Details UpdatedTriggers when a contact is created or its details are updated.
Trigger
Inbound MessageTriggers when a new inbound message arrives from a contact.
Trigger
New AppointmentTriggers when a new appointment is created.
Trigger
New ConversationTriggers when a new conversation starts.
Trigger
New DealTriggers when a new deal is created.
Action
Add Contact to ListAdds a contact to a contact list.
Action
Add Conversation CommentAdds an internal comment to a conversation.
Action
Assign ConversationAssigns a conversation to an employee or agent.
Action
Close ConversationCloses a conversation.
Action
Create AppointmentCreates an appointment for a contact.
Action
Create Contact DetailsCreates a new contact with name, address and external IDs.
Action
Create Contact ListCreates a contact list.
Action
Create DealCreates a deal for a contact.
Action
Delete ContactDeletes a contact.
Action
Delete DealDeletes a deal.
Action
Find ChannelReturns the messaging channels (WhatsApp, SMS, email and others) in the account.
Action
Find ContactFinds one contact by exactly one locator: email, phone number, external ID or social ID.
Action
Find Contact DetailsReturns a contact by its hellomateo ID.
Action
Find Custom FieldReturns the custom fields defined in the account.
Action
Find MessageReturns a message by its ID.
Action
Find TemplateReturns the message templates in the account.
Action
Format a Phone NumberFormats a phone number to E.164.
Action
Get AppointmentReturns an appointment by ID.
Action
Get ConversationReturns a conversation by ID.
Action
Get DealReturns a deal by ID.
Action
List Contact ListsReturns the contact lists in the account.
Action
List ContactsReturns contacts, optionally filtered by external ID or last update time.
Action
List EmployeesReturns the employees in the organisation.
Action
Open ConversationReopens a closed conversation.
Action
Remove Contact from ListRemoves a contact from a contact list.
Action
Send Template MessageSends a template message to a contact on a hellomateo channel.
Action
Send Text MessageSends a free-text message to a contact on a hellomateo channel.
Action
Start JourneyStarts a journey for a contact, matching or creating the contact by external ID.
Action
Update Contact DetailsUpdates an existing contact's name, address and other details.
Action
Update DealUpdates a deal's name, status, value or assignee.
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
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Questions
Google BigQuery and Mateo, 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 Mateo when something happens in Google BigQuery?
Any of Mateo's 30 actions, including Create Appointment, Create Contact Details, Create Contact List and Create Deal. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Mateo to Google BigQuery?
Yes. When something happens in Mateo, your agent can act in Google BigQuery too. This page covers both directions: Mateo's triggers and Google BigQuery's actions are listed here as well.
Do I have to build a connector for Google BigQuery or Mateo?
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 Google BigQuery and Mateo 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.