Vinkius

Render MCP. Manage Your Entire Cloud Stack From Conversation.

Render MCP gives your agent direct control over your cloud infrastructure. Instead of opening the dashboard, you can use natural language prompts to list services, suspend compute resources to save costs, deploy hotfixes instantly from GitHub, or build brand-new backend services—all through conversation.

Render MCP is compatible with Claude Claude
Render MCP is compatible with ChatGPT ChatGPT
Render MCP is compatible with Cursor Cursor
Render MCP is compatible with Gemini Gemini
Render MCP is compatible with Windsurf Windsurf
Render MCP is compatible with VS Code VS Code
Render MCP is compatible with JetBrains JetBrains
Render MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Assess current service status

Lists all active web apps, databases, and cron jobs to show their current running state.

Control compute costs

Suspends or resumes services instantly, stopping billing cycles when the project isn't needed.

Build new infrastructure

Automatically provisions entirely new cloud services linked to a specific GitHub repository branch.

Force deployments and updates

Triggers an immediate, manual deployment for any service, even clearing the build cache if necessary.

Review deployment history

Retrieves a chronological log of past deployment attempts for deep auditing.

Remove resources

Permanently deletes specific services that are no longer required in the staging environment.

Waiting for input…

AI Agent
Render

What AI agents can do with Render MCP: 10 Tools for Service Management

These tools allow your AI client to execute every core operation needed to build, deploy, and manage services within the Render cloud environment.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Render MCP

Create Service

Creates a brand new Render service instance linked directly from a GitHub repository.

Delete Service

Permanently removes an existing, unwanted Render service; this action cannot be...

Get Deploy

Pulls specific details about a single recorded deployment run.

Get Service

Retrieves full, detailed status information for one particular Render service.

List Deploys

Generates a list of all recent deployment attempts made to a specific service.

List Services

Lists every single resource in the account, including web apps, databases, and cron jobs.

Resume Service

Restarts a service that was previously suspended, bringing it back online.

Suspend Service

Stops a running service to halt compute usage and prevent billing charges.

Trigger Deploy

Forces a manual rebuild and deployment of code for an existing service.

Update Service Branch

Changes which specific branch in GitHub is used as the source for a running service.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Render MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Render integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Render, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Render MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Render. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

VINKIUS CLOUD

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

The Manual Pain Points of Cloud Ops

Right now, managing a growing cloud architecture means living in dashboards. You open the Render UI, click 'Services,' scroll through status checks, and if you need to pause billing on staging, you have to find that specific project and manually toggle it off. If something breaks, you're clicking tabs—checking deploy history here, then checking logs there.

With this MCP, you skip the whole UI process. You just tell your AI client: "List all services and suspend anything marked 'staging' except for my database." Your agent handles the navigation, the status checks, and the billing controls in a single conversational step.

Control Deployments with trigger_deploy

Before this, forcing an update meant logging into the service settings, selecting 'Deploy', picking the correct branch, and hoping nothing was missed. It was a multi-step process that always felt clunky.

Now you simply prompt your AI client: "Force deploy the main app and clear the cache." The agent executes `trigger_deploy` perfectly every time, giving you immediate control over your code's release cycle.

What Render MCP does for your AI

Your AI client connects directly to Render's capabilities via this MCP. This changes how you manage your entire cloud stack; it turns standard chat into a powerful DevOps control center. You can ask your agent to inspect the status of every web endpoint, database, and cron job in your account.

Need to save money? Tell it to suspend compute on inactive projects, or wake them up when needed. If a hotfix lands on GitHub, you don't need to click buttons; just prompt your AI client to trigger a full deployment for the service. You can even tell your agent to create brand-new services pointing to specific repository branches or completely delete obsolete staging environments.

This level of infrastructure management is what makes Vinkius such a vital catalog, giving your agent deep operational control over complex systems.

Built · Hosted · Managed by Vinkius Render MCP - Cloud DevOps Control via AI Agent
Server ID 019d75fe-6e27-707c-923b-7ed43046f89c
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Render MCP

Can I use Render MCP to check which services are running? +

Yes. Running list_services shows all connected resources—web apps, databases, and cron jobs—so you always know what's active in your account.

How do I stop billing for a test environment using Render MCP? +

You use the suspend_service tool. You tell the agent to suspend the specific service name, which immediately halts compute usage and prevents related charges.

What if I need to deploy code from an old branch? +

First, you must run update_service_branch to point the service to that historical branch. Then, use trigger_deploy to start the build process from that new source.

Is delete_service permanent? Should I worry about it? +

Yes, this action is irreversible and permanently deletes the resource. Use it only when you are 100% certain you never need the service again.

Can the AI clear the cache when triggering a deploy? +

Yes, absolutely. The tool trigger_deploy incorporates an optional variable explicitly created for cache management. You can command the agent: "Redeploy the web app named Node-Backend and bypass rendering cache."

Which type of new services can the AI deploy using `create_service`? +

The MCP can provision and launch exactly three core resource forms utilizing GitHub repos: standard web services (web_service), private network-locked processes (private_service), and asynchronous task handlers (background_worker).

Warning: Is there a confirmation before using `delete_service`? +

Since natural language agents can occasionally misinterpret parameters, invoking the text request explicitly will route straight to the Render API resulting in instantaneous destruction. Please ensure absolute clarity when pointing the AI logic toward deletion operations.