Integration
Connect actiTIME and Google BigQuery
When New Customer fires in actiTIME, your agent runs Create Row in Google BigQuery, or New Job Completed in Google BigQuery to Create Customer in actiTIME. 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 actiTIME 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 actiTIME and Google BigQuery can do together
From actiTIME to Google BigQuery
When New Customer in actiTIME
then Create Row in Google BigQuery
From Google BigQuery to actiTIME
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 actiTIME and Google BigQuery
Triggers and actions 11 triggers · 23 actions
- New Customer
Triggers when a new customer is created.
- New Project
Triggers when a new project is created.
- New Task
Triggers when a new task is created.
- New User
Triggers when a new user is created.
- Updated Leave Time
Triggers when the user's leave time is changed.
- Updated Task
Triggers when an existing task is changed.
- Updated Time-Track
Triggers when the user's working time is changed.
- Create Customer
Creates a new customer.
- Create Project
Creates a new project.
- Create Task
Creates a new task.
- Create User
creates a user account (firstName, lastName, email, username, password required; optional middleName, active, hired, releaseDate, departmentId, timeZoneGroupId).
- Find Customer
Finds the customer by name.
- Find Task
Finds the task by name.
- Get Time-Track
Returns one time-track record (taskId, time, comment)
- List Leave Time
Lists leave-time records (userId, date, leaveTypeId, leaveTime)
- Modify Leave Time
Modifies the leave time record by replacing the existing value with a specified one.
- Modify Leave Time (Increase Time)
Modifies the leave time record by increasing the existing value by a specified value.
- Modify Time-Track
Modifies the time-track record by replacing the existing value with a specified one (along with the time-track record comment).
- Modify Time-Track (Increase Time)
Modifies the time-track record by increasing the existing value by a specified value.
- Update Task
updates a task's name, description, status/workflowStatusId, projectId, typeOfWorkId, deadline or estimatedTime.
- New Job Completed
Triggers when a BigQuery job in the project finishes, whether it succeeded or failed.
- 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.
- Query Job Completed (With Row Data)
Triggers when a SELECT query job in the project finishes successfully, and includes its result rows.
- Updated Row
Triggers when a row in a table is added or changed, detected by a last-updated timestamp column you name.
- Create Row
Creates a new row of data in a table. Note: Does not create a job.
- Create Rows
Creates new rows of data in a table (accepts line items). Note: Does not create a job.
- Delete Rows
Deletes every row in a table whose match column equals the value you give.
- Find One Row
Finds the first row in a table whose column equals the value you give.
- Get Rows for Job Completed
Returns the result rows of a finished query job.
- 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.
- List Datasets
Returns the datasets in a Google Cloud project.
- List Tables
Returns the tables in a BigQuery dataset.
- Run a Query
Runs a SQL query against a table in BigQuery.
- 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
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Questions
actiTIME and Google BigQuery, answered
What can start an automation from actiTIME?
Any of actiTIME's 7 triggers in the catalog, including New Customer, New Project, New Task 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 actiTIME?
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 actiTIME?
Yes. When something happens in Google BigQuery, your agent can act in actiTIME too. This page covers both directions: Google BigQuery's triggers and actiTIME's actions are listed here as well.
Do I have to build a connector for actiTIME 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 actiTIME 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.