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MCP Server

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baryhuang

The only general AI agent that does NOT requires extra API key, giving you full control on your local and remote MacOs from Claude Desktop App

Publisherbaryhuang
Repositorymcp-remote-macos-use
LanguagePython
Forks
56
Stars
490
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    MCP Server 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

    490 stars and 56 forks from the linked repository.

MCP Server - Remote MacOs Use

The first open-source MCP server that enables AI to fully control remote macOS systems.

A direct alternative to OpenAI Operator, optimized specifically for autonomous AI agents with complete desktop capabilities, requiring no additional software installation.

Docker Pulls License: MIT

Showcases

  • Research Twitter and Post Twitter(https://www.youtube.com/watch?v=--QHz2jcvcs)

  • Use CapCut to create short highlight video(https://www.youtube.com/watch?v=RKAqiNoU8ec)

  • AI Recruiter: Automated candidate information collection, qualifying applications and sending screening sessions using Mail App

  • AI Marketing Intern: LinkedIn engagement - automated following, liking, and commenting with relevant users

  • AI Marketing Intern: Twitter engagement - automated following, liking, and commenting with relevant users

To-Do List (Prioritized)

  1. Performance Optimization - Match speed of Ubuntu desktop alternatives
  2. Apple Scripts Generation - Reduce execution time while maintaining flexibility
  3. VNC Cursor Visibility - Improve debugging and demo experience

We welcome contributions!

Features

  • No Extra API Costs: Free screen processing with your existing Claude Pro plan
  • Minimal Setup: Just enable Screen Sharing on the target Mac – no additional software needed
  • Universal Compatibility: Works with all macOS versions, current and future

Why We Built This

Native macOS Experience Without Compromise

The macOS native ecosystem remains unmatched in user experience today and will continue to be the gold standard for years to come. This is where human capabilities truly thrive, and now your AI can operate in this environment with the same fluency.

Open Architecture By Design

  • Universal LLM Compatibility: Work with any MCP Client of your choice
  • Model Flexibility: Seamlessly integrate with OpenAI, Anthropic, or any other LLM provider
  • Future-Proof Integration: Designed to evolve with the MCP ecosystem

Effortless Deployment

  • Zero Setup on Target Machines: No background applications or agents needed on macOS
  • Screen Sharing is All You Need: Control any Mac with Screen Sharing enabled
  • Eliminate Backend Complexity: Unlike other solutions that require running Python applications or background services

Streamlined Bootstrap Process

  • Leverage Claude Desktop's Polished UI: No need for developer-style Python interfaces
  • Intuitive User Experience: Interact with your AI-controlled Mac through a familiar, user-friendly interface
  • Instant Productivity: Start working immediately without configuration hassles

Architecture

Installation

json
{
  "mcpServers": {
    "remote-macos-use": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "-e",
        "MACOS_USERNAME=your_macos_username",
        "-e",
        "MACOS_PASSWORD=your_macos_password",
        "-e",
        "MACOS_HOST=your_macos_hostname_or_ip",
        "--rm",
        "buryhuang/mcp-remote-macos-use:latest"
      ]
    }
  }
}

WebRTC Support via LiveKit

This server now includes WebRTC support through LiveKit integration, enabling:

  • Low-latency real-time screen sharing
  • Improved performance and responsiveness
  • Better network efficiency compared to traditional VNC
  • Automatic quality adaptation based on network conditions

To use WebRTC features, you'll need to:

  1. Set up a LiveKit server or use LiveKit Cloud
  2. Configure the LiveKit environment variables as shown in the configuration example above

Developer Instruction

Clone the repo

bash
# Clone the repository
git clone https://github.com/yourusername/mcp-remote-macos-use.git
cd mcp-remote-macos-use

Building the Docker Image

bash
# Build the Docker image
docker build -t mcp-remote-macos-use .

Cross-Platform Publishing

To publish the Docker image for multiple platforms, you can use the docker buildx command. Follow these steps:

  1. Create a new builder instance (if you haven't already):

    bash
    docker buildx create --use
  2. Build and push the image for multiple platforms:

    bash
    docker buildx build --platform linux/amd64,linux/arm64 -t buryhuang/mcp-remote-macos-use:latest --push .
  3. Verify the image is available for the specified platforms:

    bash
    docker buildx imagetools inspect buryhuang/mcp-remote-macos-use:latest

Usage

The server provides Remote MacOs functionality through MCP tools.

Tools Specifications

The server provides the following tools for remote macOS control:

remote_macos_get_screen

Connect to a remote macOS machine and get a screenshot of the remote desktop. Uses environment variables for connection details.

remote_macos_send_keys

Send keyboard input to a remote macOS machine. Uses environment variables for connection details.

remote_macos_mouse_move

Move the mouse cursor to specified coordinates on a remote macOS machine, with automatic coordinate scaling. Uses environment variables for connection details.

remote_macos_mouse_click

Perform a mouse click at specified coordinates on a remote macOS machine, with automatic coordinate scaling. Uses environment variables for connection details.

remote_macos_mouse_double_click

Perform a mouse double-click at specified coordinates on a remote macOS machine, with automatic coordinate scaling. Uses environment variables for connection details.

remote_macos_mouse_scroll

Perform a mouse scroll at specified coordinates on a remote macOS machine, with automatic coordinate scaling. Uses environment variables for connection details.

remote_macos_open_application

Opens/activates an application and returns its PID for further interactions.

remote_macos_mouse_drag_n_drop

Perform a mouse drag operation from start point and drop to end point on a remote macOS machine, with automatic coordinate scaling.

All tools use the environment variables configured during setup instead of requiring connection parameters.

Limitations

  • Authentication Support:
    • Only Apple Authentication (protocol 30) is supported

Security Note

https://support.apple.com/guide/remote-desktop/encrypt-network-data-apdfe8e386b/mac https://cafbit.com/post/apple_remote_desktop_quirks/

We only support protocol 30, which uses the Diffie-Hellman key agreement protocol with a 512-bit prime. This protocol is used by macOS 11 to macOS 12 when communicating with OS X 10.11 or earlier clients.

Here's the information converted to a markdown table:

macOS version running Remote DesktopmacOS client versionAuthenticationControl and ObserveCopy items or install packageAll other tasksProtocol Version
macOS 13macOS 132048-bit RSA host keys2048-bit RSA host keys2048-bit RSA host keys to authenticate, then 128-bit AES2048-bit RSA host keys36
macOS 13macOS 10.12Secure Remote Password (SRP) protocol for local only. Diffie-Hellman (DH) if bound to LDAP or macOS server is version 10.11 or earlierSRP or DH,128-bit AESSRP or DH to authenticate, then 128-bit AES2048-bit RSA host keys35
macOS 11 to macOS 12macOS 10.12 to macOS 13Secure Remote Password (SRP) protocol for local only, Diffie-Hellman if bound to LDAPSRP or DH 1024-bit, 128-bit AES2048-bit RSA host keys macOS 13 to macOS 10.132048-bit RSA host keys macOS 10.13 or later33
macOS 11 to macOS 12OS X 10.11 or earlierDH 1024-bitDH 1024-bit, 128-bit AESDiffie-Hellman Key agreement protocol with a 512-bit primeDiffie-Hellman Key agreement protocol with a 512-bit prime30

Always use secure, authenticated connections when accessing remote remote MacOs machines. This tool should only be used with servers you trust and have permission to access.

License

See the LICENSE file for details.

Installation

TypingMind
{
  "mcpServers": {
    "mcp-remote-macos-use": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "-e",
        "MACOS_USERNAME={{config.MACOS_USERNAME}}",
        "-e",
        "MACOS_PASSWORD={{config.MACOS_PASSWORD}}",
        "-e",
        "MACOS_HOST={{config.MACOS_HOST}}",
        "--rm",
        "buryhuang/mcp-remote-macos-use:latest"
      ],
      "env": {
        "MACOS_USERNAME": "<MACOS_USERNAME>",
        "MACOS_PASSWORD": "<MACOS_PASSWORD>",
        "MACOS_HOST": "<MACOS_HOST>"
      }
    }
  }
}

Use MCP Server MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once MCP Server 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 MCP Server 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 MCP Server 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": {
    "mcp-remote-macos-use": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the MCP Server 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 MCP Server 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 MCP Server to help me with this task?
MCP Server
Sure. I read it.
Here is what I found using MCP Server.

Frequently asked questions

What is the MCP Server MCP server used for?

MCP Server 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 MCP Server MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use MCP Server 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 MCP Server 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 MCP Server connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect MCP Server MCP to TypingMind?

MCP Server 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 MCP Server MCP provide in TypingMind?

MCP Server 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 MCP Server MCP?

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

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