Remote MacOs Use MCP Server

What does “Remote MacOs Use” MCP Server do?

The “Remote MacOs Use” MCP Server is an open-source Model Context Protocol (MCP) server designed to allow AI agents to gain full control over remote macOS systems. Acting as a bridge between AI assistants (such as Claude Desktop App) and the underlying macOS environment, this server enables tasks that traditionally require direct system access—such as file management, application control, and remote automation—without the need for extra API keys or additional software installation. It is positioned as a direct alternative to solutions like OpenAI Operator and is optimized for autonomous AI agents, making it possible to execute complex desktop operations securely and efficiently from anywhere. This enhances developer workflows by seamlessly integrating external macOS capabilities into AI-driven processes.

List of Prompts

No prompt templates were found in the available repository documentation or files.

List of Resources

No explicit MCP resources were documented in the repository or in accessible files.

List of Tools

No explicit list of tools (such as those in a server.py) was found in the repository structure or documentation.

Use Cases of this MCP Server

• Remote macOS Automation: Enables developers and AI agents to automate tasks on remote macOS machines without requiring physical access, improving productivity for distributed teams.
• Desktop Application Control: Allows AI assistants to launch, close, or interact with macOS applications remotely, useful for testing, demonstrations, or managing workflows.
• File Management: Facilitates secure file operations (such as copy, move, or delete) on remote systems, useful for backup, organization, or deployment tasks.
• Social Media Automation: Automates research and posting on platforms like Twitter directly from a macOS environment, as showcased in linked video demonstrations.
• Developer Environment Orchestration: Supports setting up, monitoring, or updating development environments on macOS remotely, streamlining DevOps and CI/CD processes.

How to set it up

Windsurf

1. Ensure you have Node.js and the latest version of Windsurf installed.

2. Locate the Windsurf configuration file (commonly windsurf.config.json).

3. Add the Remote MacOs Use MCP Server to the mcpServers section:

   {
     "mcpServers": {
       "remote-macos-use": {
         "command": "npx",
         "args": ["@remote-macos-use/mcp-server@latest"]
       }
     }
   }
   

4. Save the configuration file and restart Windsurf.

5. Verify in Windsurf UI that the MCP server is active.

Securing API Keys (example using environment variables):

{
  "mcpServers": {
    "remote-macos-use": {
      "command": "npx",
      "args": ["@remote-macos-use/mcp-server@latest"],
      "env": {
        "SOME_SECRET_KEY": "${{ secrets.SOME_SECRET_KEY }}"
      },
      "inputs": {
        "api_key": "${{ secrets.SOME_SECRET_KEY }}"
      }
    }
  }
}

Claude

1. Install Claude Desktop App and ensure Node.js is available.

2. Open Claude’s configuration panel or file.

3. Add the MCP server under the mcpServers or similar section:

   {
     "mcpServers": {
       "remote-macos-use": {
         "command": "npx",
         "args": ["@remote-macos-use/mcp-server@latest"]
       }
     }
   }
   

4. Save and restart Claude.

5. Confirm the server is connected via Claude’s interface.

Cursor

1. Ensure Cursor and Node.js are installed.

2. Find the Cursor configuration file (often cursor.config.json).

3. Add the MCP server configuration:

   {
     "mcpServers": {
       "remote-macos-use": {
         "command": "npx",
         "args": ["@remote-macos-use/mcp-server@latest"]
       }
     }
   }
   

4. Save and relaunch Cursor.

5. Check that the server appears in Cursor’s MCP server list.

Cline

1. Install Cline and ensure Node.js is set up.

2. Open or create the Cline configuration file.

3. Insert the MCP server configuration block:

   {
     "mcpServers": {
       "remote-macos-use": {
         "command": "npx",
         "args": ["@remote-macos-use/mcp-server@latest"]
       }
     }
   }
   

4. Save the file and restart Cline.

5. Visit the Cline dashboard to verify the MCP server connection.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "remote-macos-use": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “remote-macos-use” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the available documentation, “Remote MacOs Use” MCP provides a unique and practical solution for remote macOS control, but lacks some advanced MCP documentation elements (like prompt templates, tools, and resources) that would make integration even more robust. Its open approach and clear use cases are a plus, but more technical detail would be useful for developers.

MCP Score

Overall, I would rate this MCP server a 6/10. It is innovative and practical, with clear utility and a strong open-source foundation, but lacks comprehensive MCP documentation and technical detail for deeper integration.