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Qovery

Qovery MCP Server

Built by Vinkius GDPR ToolsFree for Subscribers

Bring effortless Kubernetes and cloud deployment management to your IDE. List environments, check application states, restart pods, and deploy exact Git commits via chat.

Vinkius supports streamable HTTP and SSE.

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Qovery
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

What is the Qovery MCP Server?

The Qovery MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Qovery via 10 tools. Bring effortless Kubernetes and cloud deployment management to your IDE. List environments, check application states, restart pods, and deploy exact Git commits via chat. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.

Built-in capabilities (10)

deploy_applicationget_applicationget_environmentget_organizationget_projectlist_applicationslist_environmentslist_organizationslist_projectsrestart_application

Tools for your AI Agents to operate Qovery

Ask your AI agent "List all Qovery projects and tell me how many there are." and get the answer without opening a single dashboard. With 10 tools connected to real Qovery data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.

Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.

Why teams choose Vinkius

One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.

Build your own MCP Server with our secure development framework →

Vinkius works with every AI agent you already use

…and any MCP-compatible client

CursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWSCursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWS

Qovery MCP Server capabilities

10 tools
deploy_application

Triggers an immediate deployment of a specific Git commit SHA

get_application

Retrieves details for a specific Qovery application

get_environment

Retrieves details for a specific Qovery environment

get_organization

Retrieves details for a specific Qovery organization

get_project

Retrieves details for a specific Qovery project

list_applications

Lists all applications running in a specific environment

list_environments

Lists all environments (Production, Staging, etc.) in a project

list_organizations

Lists all Qovery organizations associated with the token

list_projects

Lists all projects within a Qovery organization

restart_application

Performs a zero-downtime rolling restart of a Qovery application

What the Qovery MCP Server unlocks

Connect your Qovery infrastructure to any AI agent and bring DevOps execution directly into your coding environment.

What you can do

  • Map your Infrastructure — Traverse effortlessly through your Qovery Organizations, Projects, and Environments to build a complete mental map of your deployments
  • Monitor Applications — Inspect individual microservices, check active replica counts, verify auto-deploy settings, and get real-time status updates without switching contexts to the Qovery dashboard
  • Take Action via Chat — Trigger zero-downtime rolling restarts to cycle Kubernetes pods and refresh environment variables directly inside Claude or Cursor
  • Targeted Deployments — Issue a fast-track deploy of a specific Git commit SHA for hotfixes or localized feature testing, all handled friction-free by the LLM

How it works

1. Subscribe to this server
2. Supply your Qovery Organization API Token
3. Start managing your clusters and triggering deploys across your environments within seconds

Who is this for?

  • Platform Engineers — easily check staging environments and cluster configs while writing infrastructure-as-code paradigms
  • Full-stack Developers — push a fix to a branch, copy the commit SHA, and just tell your agent to deploy it instantly to the dev sandbox
  • Engineering Leads — check if the latest mission-critical app is properly scaled and healthy across multiple availability zones

Frequently asked questions about the Qovery MCP Server

01

How do I securely obtain my Qovery API Token?

Sign in to your Qovery Console. Navigate to your Organization Settings, then to the API Tokens section. Click Generate Token (or Add). Give it a brief name, select the desired roles, and click Create. Copy the static string immediately as it won't be shown again, and paste it to authenticate.

02

Can it restart specific microservices?

Yes. Once you identify the app_id using the list components tools, you can instruct your agent to restart_application. This triggers a rolling restart exactly as if you clicked 'Restart' on the console. Traffic is routed seamlessly while pods re-initialize.

03

What does deploy specific Git commit do?

Normally, Qovery auto-deploys a branch. With deploy_application you can force Qovery to pull a specific commit ID (SHA) and deploy it immediately to an environment. This is perfect for hotfixes, effectively circumventing prolonged CI loops while ensuring zero downtime.

04

Is this tool safe to run on production?

Yes, but with caveats. Standard queries (like listing environments and getting stats) are entirely read-only. However, tools like restart and deploy are mutating operations. Always make sure you instruct your agent precisely and maintain manual approval checkpoints before executing deployment functions.

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