Render MCP Server

Render's Model Context Protocol (MCP) server enables you to manage your Render infrastructure directly from compatible AI apps, such as Cursor and Claude Code:

Using natural language prompts, you can:

• Spin up new services
• Query your databases
• Analyze metrics and logs

...and more! For inspiration, see some example prompts.

How it works

The Render MCP server is hosted at the following URL:

https://mcp.render.com/mcp

You can configure compatible AI apps (such as Cursor and Claude Code) to communicate with this server. When you provide a relevant prompt, your tool intelligently calls the MCP server to execute supported platform actions:

In the example diagram above:

1. A user prompts Cursor to "List my Render services".
2. Cursor intelligently detects that the Render MCP server supports actions relevant to the prompt.
3. Cursor directs the MCP server to execute the list_services "tool", which calls the Render API to fetch the corresponding data.

Setup

1. Create an API key

The MCP server uses an API key to authenticate with the Render platform. Create an API key from your Account Settings page:

2. Configure your tool

Next, we'll configure your AI app to use Render's hosted MCP server. Most compatible apps define their MCP configuration in a JSON file (such as ~/.cursor/mcp.json for Cursor).

Select the tab for your app:

{
  "mcpServers": {
    "render": {
      "url": "https://mcp.render.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_API_KEY>"
      }
    }
  }
}

claude mcp add --transport http render https://mcp.render.com/mcp --header "Authorization: Bearer <YOUR_API_KEY>"

{
  "mcpServers": {
    "render": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.render.com/mcp",
        "--header",
        "Authorization: Bearer ${RENDER_API_KEY}"
      ],
      "env": {
        "RENDER_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

{
  "mcpServers": {
    "render": {
      "url": "https://mcp.render.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_API_KEY>"
      }
    }
  }
}

3. Set your workspace

To start using the Render MCP server, you first tell your AI app which Render workspace to operate in. This determines which resources the MCP server can access.

You can set your workspace with a prompt like Set my Render workspace to [WORKSPACE_NAME].

If you don't set your workspace, your app usually directs you to specify one if you submit a prompt that uses the MCP server (such as List my Render services):

With your workspace set, you're ready to start prompting! Get started with some example prompts.

Example prompts

Your AI app can use the Render MCP server to perform a wide variety of platform actions. Here are some basic example prompts to get you started:

Service creation

Create a new database named user-db with 5 GB storage

Deploy an example Flask web service on Render using https://github.com/render-examples/flask-hello-world

Data analysis

Using my Render database, tell me which items were the most frequently bought together

Query my read replica for daily signup counts for the last 30 days

Service metrics

What was the busiest traffic day for my service this month?

What did my service's autoscaling behavior look like yesterday?

Troubleshooting

Pull the most recent error-level logs for my API service

Why isn't my site at example.onrender.com working?

Supported actions

The Render MCP server provides a "tool" for each platform action listed below (organized by resource type). Your AI app (the "MCP host") can combine these tools however it needs to perform the tasks you describe.

Running locally

You can install and run the Render MCP server on your local machine as a Docker container, or by running the executable directly:

{
  "mcpServers": {
    "render": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "RENDER_API_KEY",
        "-v",
        "render-mcp-server-config:/config",
        "ghcr.io/render-oss/render-mcp-server"
      ],
      "env": {
        "RENDER_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

Local installation

Limitations

The Render MCP server attempts to minimize exposing sensitive information (like connection strings) to your AI app's context. However, Render does not guarantee that sensitive information will not be exposed. Exercise caution when interacting with secrets in your AI app.

Note the following additional limitations:

• The MCP server supports creation of the following resources:

  • Web services
  • Static sites
  • Render Postgres databases
  • Render Key Value instances

  Other service types (private services, background workers, and cron jobs) are not yet supported.

• The MCP server does not support creating free instances.

• The MCP server does not support all configuration options when creating services.

  • For example, you cannot create image-backed services or set up IP allowlists. If there are options you'd like to see supported, please submit an issue on the MCP server's GitHub repository.

• The MCP server does not support modifying or deleting existing Render resources, with one exception:

  • You can modify an existing service's environment variables.
  • To perform other modifications or deletions, use the Render Dashboard or REST API.

• The MCP server does not support triggering deploys, modifying scaling settings, or other operational service controls.