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niyogi

An unofficial MCP server for Render to help developers ship code faster via Cline, Cursor, and Windsurf

Publisherniyogi
Repositoryrender-mcp
LanguageTypeScript
Forks
9
Stars
15
Available tools
0
Transport typestdio
Categories
LicenseMIT
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  • Connect tools to AI workflows

    Render exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    15 stars and 9 forks from the linked repository.

Render MCP Server

Deploy to Render.com directly through AI assistants.

This MCP (Model Context Protocol) server allows AI assistants like Claude to interact with the Render API, enabling deployment and management of services on Render.com.

Features

  • List all services in your Render account
  • Get details of a specific service
  • Deploy services
  • Create new services
  • Delete services
  • Get deployment history
  • Manage environment variables
  • Manage custom domains

Installation

bash
npm install -g @niyogi/render-mcp

Configuration

  1. Get your Render API key from Render Dashboard
  2. Configure the MCP server with your key:
bash
node bin/render-mcp.js configure --api-key=YOUR_API_KEY

Alternatively, you can run node bin/render-mcp.js configure without the --api-key flag to be prompted for your API key.

Usage

Starting the Server

bash
node bin/render-mcp.js start

Checking Configuration

bash
node bin/render-mcp.js config

Running Diagnostics

bash
node bin/render-mcp.js doctor

Note: If you've installed the package globally, you can also use the shorter commands:

bash
render-mcp start
render-mcp config
render-mcp doctor

Using with Different AI Assistants

Using with Cline

  1. Add the following to your Cline MCP settings file:

    json
    {
      "mcpServers": {
        "render": {
          "command": "node",
          "args": ["/path/to/render-mcp/bin/render-mcp.js", "start"],
          "env": {
            "RENDER_API_KEY": "your-render-api-key"
          },
          "disabled": false,
          "autoApprove": []
        }
      }
    }
  2. Restart Cline for the changes to take effect

  3. You can now interact with Render through Claude:

    Claude, please deploy my web service to Render

Using with Windsurf/Cursor

  1. Install the render-mcp package:

    bash
    npm install -g @niyogi/render-mcp
  2. Configure your API key:

    bash
    node bin/render-mcp.js configure --api-key=YOUR_API_KEY
  3. Start the MCP server in a separate terminal:

    bash
    node bin/render-mcp.js start
  4. In Windsurf/Cursor settings, add the Render MCP server:

    • Server Name: render
    • Server Type: stdio
    • Command: node
    • Arguments: ["/path/to/render-mcp/bin/render-mcp.js", "start"]
  5. You can now use the Render commands in your AI assistant

Using with Claude API Integrations

For custom applications using Claude's API directly:

  1. Ensure the render-mcp server is running:

    bash
    node bin/render-mcp.js start
  2. In your application, when sending messages to Claude via the API, include the MCP server connections in your request:

    json
    {
      "mcpConnections": [
        {
          "name": "render",
          "transport": {
            "type": "stdio",
            "command": "node",
            "args": ["/path/to/render-mcp/bin/render-mcp.js", "start"]
          }
        }
      ]
    }
  3. Claude will now be able to interact with your Render MCP server

Example Prompts

Here are some example prompts you can use with Claude once the MCP server is connected:

  • "List all my services on Render"
  • "Deploy my web service with ID srv-123456"
  • "Create a new static site on Render from my GitHub repo"
  • "Show me the deployment history for my service"
  • "Add an environment variable to my service"
  • "Add a custom domain to my service"

Development

Building from Source

bash
git clone https://github.com/niyogi/render-mcp.git
cd render-mcp
npm install
npm run build

Running Tests

bash
npm test

License

MIT

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "render": {
      "command": "npx",
      "args": [
        "-y",
        "@niyogi/render-mcp"
      ],
      "env": {
        "RENDER_API_KEY": "your-render-api-key"
      }
    }
  }
}

Use Render MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Render is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Render as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Render MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "render": {
      "command": "npx",
      "args": [
        "-y",
        "@niyogi/render-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Render MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Render MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Render to help me with this task?
Render
Sure. I read it.
Here is what I found using Render.

Frequently asked questions

What is the Render MCP server used for?

Render is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Render MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Render with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Render MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Render connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Render MCP to TypingMind?

Render runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Render MCP provide in TypingMind?

Render exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Render MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Render requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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