--- title: "Connect Google BigQuery and PandaDoc - APIANT.ai" description: "When \"New Job Completed\" fires in Google BigQuery, your agent runs \"Create contact\" in PandaDoc." canonical: "https://apiant.ai/connect/google-bigquery-to-pandadoc" --- # Connect Google BigQuery and PandaDoc When **New Job Completed** fires in [Google BigQuery](https://apiant.ai/connections/google-bigquery), your agent runs **Create contact** in [PandaDoc](https://apiant.ai/connections/pandadoc), or **Document completed** in PandaDoc to **Get Rows for Job Completed** 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 PandaDoc **3** triggers PandaDoc **19** 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 PandaDoc to do together? Give your AI client this address. `https://mcp.apiant.ai` One 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.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 PandaDoc can do together ### From Google BigQuery to PandaDoc - When **New Job Completed** in Google BigQuery then **Create contact** in PandaDoc - When **New Row** in Google BigQuery then **Update contact** in PandaDoc ### From PandaDoc to Google BigQuery - When **Document completed** in PandaDoc then **Get Rows for Job Completed** in Google BigQuery - When **Document updated** in PandaDoc then **Create Row** 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 PandaDoc ## Triggers and actions 7 triggers · 29 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 **Document completed** Polling trigger. Fires when a document reaches completed status. Dedup by document id. - Trigger **Document completed (instant)** Instant trigger: fires when a PandaDoc document reaches the completed state. Self-registering — APIANT creates the PandaDoc webhook when you turn the automation on and removes it when you turn it off, so there is nothing to paste. Only document_state_changed events with status document.completed are passed through; each fires once with the document id, name, status, created/modified/completed timestamps and the full document object. - Trigger **Document updated** Polling trigger. Fires when a document is created or changes status. Dedup by document id + date_modified. - Action **Change document status** Manually changes a document's status (e.g. to mark paid or voided). Only certain transitions are allowed. - Action **Create contact** Creates a new contact. - Action **Create document from template** Creates a new document from a template, with recipients, tokens, fields, and pricing tables. - Action **Create document link** Generates a shareable session link for a recipient to view/sign a document. - Action **Delete contact** Deletes a contact by ID. - Action **Delete document** Deletes a document by ID. - Action **Download document PDF** Returns the document as a PDF file. Use watermark options as needed. - Action **Find document by name** Finds a document by name and emits its ID. An error occurs if none or more than one is found. - Action **Get document details** Retrieves detailed data for a single document by ID, including recipients, tokens, fields, and metadata. - Action **Get document entered data** Emits arrays of field and token names and values for the specified document. - Action **Get document status** Returns the current status of a document by ID. - Action **Get template details** Retrieves details for a template by ID, including roles, fields, tokens, and pricing tables. - Action **List contacts** Lists contacts in the workspace. - Action **List documents** Lists documents, optionally filtered by status, template, folder, or search query. - Action **List folders** Lists document folders. - Action **List members** Lists workspace members (users). - Action **List templates** Lists available document templates. - Action **Send document** Moves a draft document to sent status, optionally emailing recipients with a subject and message. Set silent to suppress notifications. - Action **Update contact** Updates an existing contact 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) - [ **PandaDoc** PandaDoc helps you build and deliver sales quotes and proposals and track presentations and close deals...](https://apiant.ai/connections/pandadoc) 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 PandaDoc - [ **HubSpot to PandaDoc** HubSpot is your all-in-one stop for all of your marketing software needs.](https://apiant.ai/connect/hubspot-to-pandadoc) - [ **Mailchimp to PandaDoc** Mailchimp marketing automation and email platform.](https://apiant.ai/connect/mailchimp-to-pandadoc) - [ **ActiveCampaign to PandaDoc** ActiveCampaign is a marketing automation, email marketing, and CRM platform.](https://apiant.ai/connect/activecampaign-to-pandadoc) - [ **JIRA to PandaDoc** Atlassian JIRA Cloud — issue tracking and project management.](https://apiant.ai/connect/jira-to-pandadoc) - [ **Intercom to PandaDoc** Intercom is a customer communications platform for support, engagement, and marketing.](https://apiant.ai/connect/intercom-to-pandadoc) - [ **JotForm to PandaDoc** JotForm is a web-based WYSIWYG form builder. Create forms, integrate them into your site, and collect...](https://apiant.ai/connect/jotform-to-pandadoc) Questions ## Google BigQuery and PandaDoc, 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 PandaDoc when something happens in Google BigQuery? Any of PandaDoc's 19 actions, including Create contact, Create document from template, Create document link and Send document. Your agent maps the data both ways and tests every scenario before it ships. ### ### Can it also run from PandaDoc to Google BigQuery? Yes. When something happens in PandaDoc, your agent can act in Google BigQuery too. This page covers both directions: PandaDoc's triggers and Google BigQuery's actions are listed here as well. ### ### Do I have to build a connector for Google BigQuery or PandaDoc? 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 PandaDoc 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.