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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Render with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Equip your AI to orchestrate cloud infrastructure, manage service deployments, and execute scaling operations natively on your Render platform.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

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

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 10 capabilities

The complete Render capability set.

These are the exact actions your AI can choose when you ask it to work with Render.

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 10 available through Render.

  1. 01

    Create service

    Specify type, name, owner, and repository. Creates a new Render service from a GitHub repository

  2. 02

    Get deploy

    Retrieves details for a specific deployment

  3. 03

    List services

    Lists all services (web apps, databases, cron jobs) in the Render account

  4. 04

    Trigger deploy

    Triggers a manual deployment for a service

Capability set02 / 03

05-07

3 capabilities in this set.

Part of 10 available through Render.

  1. 05

    List deploys

    Lists recent deployments for a service

  2. 06

    Delete service

    This action is irreversible. Permanently deletes a Render service

  3. 07

    Get service

    Retrieves details for a specific Render service

Capability set03 / 03

08-10

3 capabilities in this set.

Part of 10 available through Render.

  1. 08

    Resume service

    Resumes a previously suspended service

  2. 09

    Suspend service

    Suspends a service to stop execution and billing

  3. 10

    Update service branch

    Updates the tracked GitHub branch for a service

Observed, not estimated

880ms average. Fast in production.

Render is checked daily against the live service.

Daily averagePeak 1080ms
Aug 20Today
Fastest day
734ms
Slowest day
1080ms
14-day trend
Slowing+29%

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

FAQ

Questions Render owners ask.

  • 01

    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."

  • 02

    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).

  • 03

    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.

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