Google · Supported

Gemini CLI can deploy to your infrastructure.
It cannot drop your production database.

Both of those are by design, and they are the same design. Install eight Qovery skills with one command and Gemini CLI can deploy applications, provision databases and open preview environments on your own cloud account. What it cannot do is decided in the API underneath, not in a prompt asking it nicely.

Start free trial Talk with us

What it can do

Eight skills, one install.

The Qovery skills follow the Agent Skills open standard, so Gemini CLI picks the right one from what you ask. Each also has a slash command if you would rather be explicit.

qovery

/qovery

Entry point. Routes to the right skill and handles quick operations: list, status, stop, restart, logs, clone, scale, custom domains, deployment history.

qovery-onboard

/qovery-onboard

Guided setup. Recommends cloud provider, cluster type, environment structure, RBAC and cost defaults. Handles bring-your-own-Kubernetes and migrations from Heroku, Vercel, Netlify, Render and Railway.

qovery-deploy

/qovery-deploy

Deploys any application to Kubernetes. Analyses the codebase, writes a Dockerfile if one is missing, provisions databases, sets environment variables, then deploys via CLI and API or Terraform.

qovery-troubleshoot

/qovery-troubleshoot

Eight-layer diagnosis across deployment status, build and runtime logs, health checks, env vars, networking, resources and cluster. Matches 20+ error patterns and writes a runbook to .qovery/runbooks/.

qovery-optimize

/qovery-optimize

Analyses historical CPU and memory against allocation across seven optimisation dimensions, estimates external cloud costs, and produces a markdown report plus CSV export.

qovery-speedup

/qovery-speedup

Measures the deployment pipeline stage by stage, classifies each bottleneck as yours or Qovery infrastructure, and proposes Dockerfile and health-check fixes with before and after timings.

qovery-preview

/qovery-preview

Creates a preview environment from a pull request. Detects or builds a blueprint environment, clones it, switches branches, and configures auto-shutdown so it does not run all weekend.

qovery-terraform

/qovery-terraform

Reads an existing Qovery setup from the API and generates HCL for the qovery/qovery provider, imports resources into state, and validates against a test clone before you commit.

Connect it

Two interfaces. Pick both.

The skills deploy. The MCP Server operates what is already running. They are complementary, and most teams end up using both.

Agent Skills

Gemini CLI is listed as Supported in the Qovery skills compatibility table. The installer places all eight skills where compatible tools discover them, alongside their slash commands.

Then just ask: "Deploy my application with Qovery".

# Install all eight skills, globally
$ curl -fsSL https://skill.qovery.com/install.sh | bash

# Or scope them to the current project only
$ curl -fsSL https://skill.qovery.com/install.sh | bash -s -- --project

MCP Server

The skills deploy. The MCP Server operates what is already running. It is a standard remote MCP endpoint, so configure it the way you configure any MCP server in Gemini CLI.

Also published in the MCP registry as com.qovery. Write mode additionally requires write access enabled in the Qovery Console.

# Server URL, read-only by default
https://mcp.qovery.com/mcp

# Read/write, when you explicitly want it
https://mcp.qovery.com/mcp?read_write=true

# Or authenticate with a Qovery API token
https://mcp.qovery.com/mcp?token=YOUR_QOVERY_TOKEN

Read the full setup guide

What it cannot do

The boundary is not in the prompt.
It is in the API underneath.

If you came here from our homepage, Gemini CLI is the agent we show getting told no. That was not a dig at Google. It is the whole product in one frame: a capable agent, a request outside its scope, and a boundary that holds regardless of what the model decided it wanted.

Every one of them is checkable in the docs before you trust a word of this page.

Read-only by default

The Qovery MCP Server connects in read-only mode unless you say otherwise. Your agent can list environments, read service state, and tail logs. It cannot change anything.

Write access is two deliberate switches

Writes require read_write=true on the connection URL and a separate write-access setting enabled in the Qovery Console. Neither one is something a model can talk its way into.

Scoped by the RBAC you already run

An agent authenticates with its own API token and inherits the permissions of the role that token was issued under. Agents do not get a parallel access model, and they do not consume user seats.

Every action lands in the audit log

MCP tool calls and API operations are recorded in the Qovery Console audit trail against the token that made them, which is what turns "an agent did something" into an answerable question.

Keep reading

Guide

AI governance and cost

Gemini CLI and Qovery.

Does Qovery work with Gemini CLI?

Yes. Gemini CLI is listed as Supported in the Qovery agent skills compatibility table. The skills follow the Agent Skills open standard, so one install command covers Gemini CLI along with Claude Code, Cursor, OpenAI Codex, OpenCode, VS Code Copilot and 30+ other tools.

How do I connect Gemini CLI to Qovery?

Run curl -fsSL https://skill.qovery.com/install.sh | bash to install the eight Qovery agent skills, then ask Gemini CLI to deploy your application. To manage running infrastructure as well, add https://mcp.qovery.com/mcp as an MCP server in your Gemini CLI configuration.

Why does the Qovery homepage show Gemini CLI being blocked?

Because that is the product. The homepage shows an agent asking to drop a production database and the request being rejected as outside agent scope. Any agent would be rejected for that request. Gemini CLI is fully supported for the operations it is scoped to perform, and the boundary that stops the destructive request is the same boundary that makes the supported ones safe to run unattended.

Can I give Gemini CLI read-only access to my infrastructure?

That is the default. The Qovery MCP Server connects read-only unless you add read_write=true to the URL and separately enable write access in the Qovery Console. You can also issue a Qovery API token with view-only permissions, which guarantees no destructive action is possible regardless of the connection settings.

Get started

One command, and Gemini CLI
deploys to your own cloud.

Install the skills, point them at your AWS, GCP, Azure or Scaleway account, and let the agent work inside a boundary you set once. Read-only until you decide otherwise.