# Connect Google BigQuery and SQL Server When **New Job Completed** fires in [Google BigQuery](https://apiant.ai/connections/google-bigquery), your agent runs **Add Row** in [SQL Server](https://apiant.ai/connections/sql-server), or **New or Updated Row** in SQL Server to **Create Row** in Google BigQuery. Describe the whole flow and it is built, tested on every scenario and kept running. Google BigQuery **4** triggers Google BigQuery **10** actions SQL Server **4** triggers SQL Server **7** 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 SQL Server 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 and SQL Server can do together ### From Google BigQuery to SQL Server - When **New Job Completed** in Google BigQuery then **Add Row** in SQL Server - When **New Row** in Google BigQuery then **Update Row** in SQL Server ### From SQL Server to Google BigQuery - When **New or Updated Row** in SQL Server then **Create Row** in Google BigQuery - When **New Row** in SQL Server 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 SQL Server ## Triggers and actions 8 triggers · 17 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. - Trigger **New or Updated Row** Triggers when a new row is added or modified. - Trigger **New or Updated Row (Custom Query)** Fires for each new or changed row returned by a SELECT statement you write against the connected SQL Server database. - Trigger **New Row** Triggers when you add a new row. - Trigger **New Table** Fires when a new table appears in the connected SQL Server database. - Action **Add Row** Add one row to a table on the connected SQL Server database. - Action **Delete Row** Delete the rows in a table whose chosen column equals a value. - Action **Find Row** Find the first row in a table whose chosen column matches a value. - Action **Find Rows via Custom Query** Runs a SELECT statement you write against the connected SQL Server database and returns every row it matches. - Action **Find Row via Custom Query** Runs a SELECT statement you write against the connected SQL Server database and returns the first row it matches. - Action **Run Custom Statement** Runs a statement you write against the connected SQL Server database that changes data rather than returning rows, and reports how many rows it changed. - Action **Update Row** Change column values on every row of a table whose chosen column matches a value. ## 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) - [ **SQL Server** Connect directly to a Microsoft SQL Server database and run SQL statements from your automations.](https://apiant.ai/connections/sql-server) 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 SQL Server - [ **HubSpot to SQL Server** HubSpot is your all-in-one stop for all of your marketing software needs.](https://apiant.ai/connect/hubspot-to-sql-server) - [ **Slack to SQL Server** Slack is a messaging platform for teams. Post messages, manage channels, users, reminders, and react to...](https://apiant.ai/connect/slack-to-sql-server) - [ **Mailchimp to SQL Server** Mailchimp marketing automation and email platform.](https://apiant.ai/connect/mailchimp-to-sql-server) - [ **Shopify to SQL Server** Shopify is a commerce platform for online stores and retail point-of-sale.](https://apiant.ai/connect/shopify-to-sql-server) - [ **QuickBooks Online to SQL Server** QuickBooks Online accounting — manage customers, invoices, bills, payments, vendors, expenses, and more via...](https://apiant.ai/connect/quickbooks-online-to-sql-server) - [ **Pipedrive to SQL Server** Pipedrive is a sales CRM and pipeline management tool.](https://apiant.ai/connect/pipedrive-to-sql-server) Questions ## Google BigQuery and SQL Server, 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 SQL Server when something happens in Google BigQuery? Any of SQL Server's 7 actions, including Update Row, Add Row, Find Row and Find Rows via Custom Query. Your agent maps the data both ways and tests every scenario before it ships. ### ### Can it also run from SQL Server to Google BigQuery? Yes. When something happens in SQL Server, your agent can act in Google BigQuery too. This page covers both directions: SQL Server's triggers and Google BigQuery's actions are listed here as well. ### ### Do I have to build a connector for Google BigQuery or SQL Server? 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.