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Connect Render to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn your AI agent into a DevOps control center.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 10 capabilities

We ship only the actions that matter.

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 10 available through Render.

  1. 01

    Create service

    Creates a new Render service by specifying the type, name, owner, and repository.

  2. 02

    Get deploy

    Retrieves specific details regarding a single deployment.

  3. 03

    Trigger deploy

    Starts a manual deployment for a designated service.

  4. 04

    List deploys

    Shows a list of recent deployments for a specific service.

Capability set02 / 03

05-07

3 capabilities in this set.

Part of 10 available through Render.

  1. 05

    Delete service

    Permanently removes a Render service from your account.

  2. 06

    Get service

    Fetches the current details of a specific Render service.

  3. 07

    List services

    Returns a list of all web apps, databases, and cron jobs in your Render account.

Capability set03 / 03

08-10

3 capabilities in this set.

Part of 10 available through Render.

  1. 08

    Resume service

    Wakes up a service that was previously suspended.

  2. 09

    Suspend service

    Pauses a service to stop its execution and halt billing.

  3. 10

    Update service branch

    Changes the GitHub branch that a service tracks.

Real work

What teams actually run

01

Automated Hotfixes

Tell your agent to trigger a new deployment after you push a critical fix to GitHub.

02

Cost Optimization

Ask your agent to find and suspend non-production services during off-hours.

03

Rapid Prototyping

Provision a new staging environment by simply providing a repository link to your agent.

04

Deployment Auditing

Query your agent to check the success or failure of recent service builds.

Automate a task

Put Render to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Render works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Render to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

892ms average. Fast in production.

Render is checked daily against the live service.

Daily averagePeak 1106ms
Oct 3Today
Fastest day
752ms
Slowest day
1106ms
14-day trend
Slowing+13%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 10 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Render, so you can see the experience inside your AI.

It does not authenticate your account with Render. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Render Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_pEeUg16StLOA5pkBaryT7Mq2sSYvbxeIRlBjicca/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Render capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "render-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_pEeUg16StLOA5pkBaryT7Mq2sSYvbxeIRlBjicca/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Render in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Render owners hand off.

This MCP is built for technical users who want to manage cloud resources without switching between their code editor and a web dashboard.

  • 01

    DevOps Engineers

    They use the agent to manage routing, execute deployments, and scale resources.

  • 02

    Backend Developers

    They spin up private services or background workers using repo links.

  • 03

    Startups

    They use the agent to identify and suspend unused instances to keep costs low.

FAQ

Questions Render owners ask.

  • 01

    How do I connect this MCP to my Render account?

    You need to generate a personal API Key in your Render Account Settings and add it to the MCP configuration in Vinkius.

  • 02

    Can I use this to save money on my Render bill?

    Yes. You can instruct your agent to use the suspend_service capability to stop compute and billing for unused services.

  • 03

    Will this replace the Render dashboard?

    It acts as a command interface for your agent. While it handles most deployment and scaling tasks, the dashboard remains available for full visual management.

  • 04

    Is deleting a service permanent?

    Yes. The delete_service capability performs an irreversible action that removes the service from your account.

  • 05

    Which AI clients can use this Render MCP?

    Any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code, can use this connector.

  • 06

    Can the AI clear the cache when triggering a deploy?

    Yes, absolutely. The capability 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."

  • 07

    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).

  • 08

    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.

Explore

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