What can an AI teammate do with Google Cloud?

A Google Cloud AI teammate can list and inspect Compute Engine instances, enumerate Cloud Storage buckets, pull billing reports across projects, review Cloud Functions, and perform write operations like starting or stopping VMs and creating buckets. It can generate infrastructure health digests, surface cost anomalies, and flag IAM misconfigurations - all on a schedule or on demand. Write actions require your approval.

Which GCP projects and resources can my teammate access?

Your teammate accesses whatever is visible to the connected GCP service account. You can scope tasks to specific projects, regions, or resource labels in the task instructions to limit the blast radius.

Can my teammate start, stop, or create resources automatically?

Yes, but write actions like starting or stopping instances and creating buckets require your approval in safe and plan permission modes. You can configure auto-approval for trusted recurring workflows such as scheduled scale-downs.

How is a Google Cloud AI teammate different from GCP monitoring dashboards?

GCP dashboards display metrics but can't reason across them or take action. A Google Cloud AI teammate reads across compute, storage, IAM, and billing to write a plain-language summary of what needs attention and, with your approval, acts on it directly.

Developer tools

AI Teammate for Google Cloud

An AI teammate that monitors, manages, and optimizes your Google Cloud infrastructure.

Your AI teammate for Google Cloud monitors and manages your GCP infrastructure across Compute Engine, Cloud Storage, IAM, and billing. Think of it as an always-on cloud operations assistant: it checks instance health, reviews storage usage, audits IAM policies, and surfaces cost anomalies in plain language. Write actions always require your approval.

GCP gives you powerful primitives but no opinionated view of what's actually happening across your infrastructure. A Google Cloud AI teammate reads across compute, storage, and billing to answer the operational questions your team would otherwise have to dig up manually.

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What your AI teammate can do with Google Cloud

Read-only actions run automatically. Write actions require your approval.

Read-only actions

list compute instances

Browse all VM instances across projects and zones with their current status

get instance details

Read the full configuration, metadata, and status of a specific Compute Engine instance

list storage buckets

Enumerate Cloud Storage buckets with their locations and storage classes

get billing report

Fetch cost and usage data across services, projects, and time ranges

list cloud functions

Browse deployed Cloud Functions with their runtime, region, and trigger configuration

Write actions (require approval)

start or stop instance

Start or stop a Compute Engine VM instance

create storage bucket

Provision a new Cloud Storage bucket with specified location and storage class

Example workflows with Google Cloud

Real tasks you can run on a schedule or on demand.

task

generate a daily GCP cost digest broken down by project and post it to Slack

task

check all compute instances for stopped or unhealthy VMs and alert on-call

task

audit IAM policies across projects and surface overly permissive roles for review

task

monitor Cloud Functions for deployment failures and summarize error trends weekly

How to connect Google Cloud

Create a free m8tes account.

Connect Google Cloud

Click Connect and complete the OAuth flow or enter your API key.

Create a task

Give your AI teammate a task that uses Google Cloud. It handles the rest.

Google Cloud AI teammate: FAQ

Common questions about using an AI teammate with Google Cloud.

Build an AI teammate for Google Cloud

Connect Google Cloud to an autonomous AI teammate that reads data, runs tasks on schedule, and delivers structured output.

AI teammates — all integrations
Build a teammate that uses Google Cloud alongside your other tools.

Related integrations

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Slack

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