Integration
Connect Feathery and Google BigQuery
When Data Received fires in Feathery, your agent runs Import Data in Google BigQuery, or New Job Completed in Google BigQuery to Create or Fetch User in Feathery. 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 Feathery 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 Feathery and Google BigQuery can do together
From Feathery to Google BigQuery
When Data Received in Feathery
then Import Data in Google BigQuery
When Form Completion in Feathery
then Create Row in Google BigQuery
From Google BigQuery to Feathery
When New Job Completed in Google BigQuery
then Create or Fetch User in Feathery
When New Row in Google BigQuery
then Get User Field Data in Feathery
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 Feathery and Google BigQuery
Triggers and actions 6 triggers · 21 actions
Trigger
Data ReceivedTriggers when an end user submits or updates data on a Feathery form.
Trigger
Form CompletionTriggers when an end user completes a Feathery form.
Action
Create Hidden FieldCreates a hidden field in your Feathery account.
Action
Create or Fetch UserCreates a Feathery end user with the given ID, or returns the existing user, including its SDK key.
Action
Create or Update SubmissionSets field values for a Feathery user and initializes submissions on the given forms.
Action
Delete UserDeletes a Feathery end user and their submissions.
Action
Get User Field DataReturns every field value a Feathery user submitted across forms.
Action
Get User Form SessionReturns a Feathery user's form session: every form they are working on and their progress.
Action
List Document TemplatesReturns document templates uploaded by your Feathery team, optionally filtered by name or tags.
Action
List FormsReturns your Feathery forms, optionally filtered by tags or active status.
Action
List Form SubmissionsReturns submissions for a Feathery form, optionally filtered by user, completion and update time.
Action
List Hidden FieldsReturns all hidden fields in your Feathery account.
Action
List UsersReturns your Feathery end users, optionally filtered by creation time or a field value.
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
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Questions
Feathery and Google BigQuery, answered
What can start an automation from Feathery?
Any of Feathery's 2 triggers in the catalog, including Data Received and Form Completion. 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 Feathery?
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 Feathery?
Yes. When something happens in Google BigQuery, your agent can act in Feathery too. This page covers both directions: Google BigQuery's triggers and Feathery's actions are listed here as well.
Do I have to build a connector for Feathery 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 Feathery 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.