Integration

Connect Google Tasks and BigML

When New Task Created fires in Google Tasks, your agent runs List Models in BigML, or New project in BigML to Create Task List in Google Tasks. 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 Tasks and BigML to do together?

Ask the assistant

You'll sign in before anything runs. What you typed comes with you.

Examples

Pick one to fill the box, then change anything: the steps, the wording, even the apps. Go as long as you like.

Connect your AI client

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)
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)

Google Tasks holds the checklist your team actually works from, while BigML holds the projects, datasets and models behind that work. Connecting them means a new BigML project can open its own list in Google Tasks with a task per dataset, and a task you touch in Google Tasks can pull the current status of the BigML resource it refers to.

Example flows

What Google Tasks and BigML can do together

From Google Tasks to BigML

From BigML to Google Tasks

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 Tasks and BigML

Triggers and actions 6 triggers ยท 20 actions

Each app on its own

Reviews

What our customers say

More from Google Tasks

More into BigML

Questions

Google Tasks and BigML, answered

Can a task in Google Tasks tell me whether a BigML model has finished training?

Yes, when a task is updated in Google Tasks the connection can call Get Resource Status in BigML using the resource id kept in the task, and read back the current state. The status comes back on each run, so you check by touching the task rather than opening BigML.

Does BigML have a trigger for new datasets or models?

BigML only triggers on a new project here, so that is the starting point for anything that runs automatically. Datasets, models and sources are reached with the List Datasets, List Models and List Sources actions after the project trigger fires or after a Google Tasks trigger.

What can start an automation from Google Tasks?

Any of Google Tasks's 5 triggers in the catalog, including New Task Created, New Task List Created, Task Details Changed and Task List Changed. Describe the moment in plain language and your agent picks the right one.

What can your agent do in BigML when something happens in Google Tasks?

Any of BigML's 4 actions, including List Models, Get Resource Status, List Datasets and List Sources. Your agent maps the data both ways and tests every scenario before it ships.

Can it also run from BigML to Google Tasks?

Yes. When something happens in BigML, your agent can act in Google Tasks too. This page covers both directions: BigML's triggers and Google Tasks's actions are listed here as well.

Do I have to build a connector for Google Tasks or BigML?

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 Tasks and BigML 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.