Tauri MCP Server

A Model Context Protocol (MCP) server for testing and interacting with Tauri v2 applications. This tool enables AI assistants to better understand, debug, and interact with Tauri apps during development.

The MCP protocol provides a standardized way for AI assistants to interact with external tools and systems. This server implements the MCP specification to expose Tauri application testing and debugging capabilities.

MCP Compliance

This server is fully compliant with the Model Context Protocol specification. It implements:

• ✅ JSON-RPC 2.0 transport over stdio
• ✅ Initialize/shutdown handshake
• ✅ Tools capability with 12 specialized Tauri testing tools
• ✅ Proper error handling with descriptive messages
• ✅ Tool schemas using JSON Schema format
• ✅ Protocol version compatibility - Supports both "1.0" and date-based versions (e.g., "2024-11-05")

For more details about MCP:

• MCP Introduction
• Building MCP Servers
• Tool Definitions

Features

Core Tools

• Process Management

  • launch_app - Launch Tauri applications with arguments
  • stop_app - Gracefully stop running apps
  • get_app_logs - Capture stdout/stderr output
  • monitor_resources - Track CPU, memory, and disk usage

• Window Manipulation

  • take_screenshot - Capture app window screenshots
  • get_window_info - Get window dimensions, position, and state

• Input Simulation

  • send_keyboard_input - Simulate keyboard input
  • send_mouse_click - Simulate mouse clicks
  • Mouse movement, dragging, and scrolling support

• Debugging Tools

  • execute_js - Execute JavaScript in the webview
  • get_devtools_info - Get DevTools connection info
  • WebDriver integration for advanced testing
  • Console log capture

• IPC Interaction

  • list_ipc_handlers - List registered Tauri commands
  • call_ipc_command - Call Tauri IPC commands
  • Event emission and listening

Installation

Using DXT (Recommended for Claude Desktop)

The easiest way to install tauri-mcp for use with Claude Desktop is via DXT (Desktop Extension):

1. Download the latest tauri-mcp-node-*.dxt file from the releases page
2. Double-click the .dxt file to install (or drag it onto Claude Desktop)
3. The server will be automatically configured and ready to use

Note: Due to a known issue with Claude Desktop's DXT extraction, we provide a Node.js wrapper version (tauri-mcp-node-*.dxt) that works around this limitation.

Using Cargo

cargo install tauri-mcp

Important Note for Rust-based MCP Servers: Claude Desktop currently has compatibility issues with Rust-based MCP servers, causing immediate disconnections after initialization. This is a known issue affecting all non-Node.js MCP servers. The cargo installation is suitable for:

• Direct CLI usage
• Integration with other tools
• Development and testing

For use with Claude Desktop, please use the DXT package which includes a Node.js wrapper.

From Source

# Clone the repository
git clone https://github.com/dirvine/tauri-mcp.git
cd tauri-mcp

# Build and install
cargo install --path .

Usage

As a Standalone Server

# Start the MCP server
tauri-mcp serve

# With custom host and port
tauri-mcp serve --host 127.0.0.1 --port 3000

# With a specific Tauri app
tauri-mcp --app-path ./my-tauri-app

Configuration

Create a tauri-mcp.toml file for configuration:

auto_discover = true
session_management = true
event_streaming = false
performance_profiling = false
network_interception = false

Environment Variables

• TAURI_MCP_LOG_LEVEL - Set log level (trace, debug, info, warn, error)
• TAURI_MCP_CONFIG - Path to config file (default: tauri-mcp.toml)

MCP Integration

Claude Desktop Configuration

Option 1: Using DXT Package (Recommended)

Install the tauri-mcp-node-*.dxt package by double-clicking it. The server will be automatically configured.

Option 2: Manual Configuration

If you need to configure manually or use the development version, add to your Claude Desktop configuration:

{
  "mcpServers": {
    "tauri-mcp": {
      "command": "node",
      "args": ["/path/to/tauri-mcp/server/index.js"],
      "env": {
        "TAURI_MCP_LOG_LEVEL": "info"
      }
    }
  }
}

Note: Direct Rust binary configuration ("command": "tauri-mcp") will not work with Claude Desktop due to compatibility issues. Use the Node.js wrapper approach shown above.

Available MCP Tools

All tools are exposed through the MCP protocol and can be called by AI assistants:

// Launch a Tauri app
await use_mcp_tool("tauri-mcp", "launch_app", {
  app_path: "/path/to/tauri-app",
  args: ["--debug"]
});

// Take a screenshot
await use_mcp_tool("tauri-mcp", "take_screenshot", {
  process_id: "uuid-here",
  output_path: "./screenshot.png"
});

// Execute JavaScript
await use_mcp_tool("tauri-mcp", "execute_js", {
  process_id: "uuid-here",
  javascript_code: "window.location.href"
});

// Send keyboard input
await use_mcp_tool("tauri-mcp", "send_keyboard_input", {
  process_id: "uuid-here",
  keys: "cmd+a"
});

Platform Support

• macOS - Full support including window management
• Windows - Full support with native window APIs
• Linux - X11 support (Wayland in progress)

Development

Building

# Debug build
cargo build

# Release build
cargo build --release

# Run tests
cargo test

Building DXT Packages

The project includes build scripts for creating DXT (Desktop Extension) packages for different platforms.

Prerequisites

• Rust toolchain installed
• Node.js 18+ (for the Node.js wrapper)
• zip command available in PATH

Building on macOS/Linux

# Build the Node.js wrapper version (recommended)
./build-dxt-node.sh

# The DXT package will be created as tauri-mcp-node-*.dxt

Building on Windows

# Create a Windows build script or use WSL
# Ensure you have zip.exe available or use PowerShell's Compress-Archive

# Build release binary
cargo build --release

# Create package directory structure
mkdir dxt-package-node
mkdir dxt-package-node\server

# Copy files
copy target\release\tauri-mcp.exe dxt-package-node\
copy server\*.* dxt-package-node\server\
copy manifest-node.json dxt-package-node\manifest.json

# Install Node dependencies
cd dxt-package-node\server
npm install --production
cd ..\..

# Create DXT archive (using PowerShell)
Compress-Archive -Path dxt-package-node\* -DestinationPath tauri-mcp-node.zip
Rename-Item tauri-mcp-node.zip tauri-mcp-node-0.1.8.dxt

DXT Package Structure

The DXT package includes:

• manifest.json - Extension metadata and configuration
• tauri-mcp - The compiled Rust binary
• server/ - Node.js wrapper and dependencies
  • index.js - Node.js MCP server that spawns the Rust binary
  • package.json - Node.js dependencies
  • node_modules/ - MCP SDK and dependencies

Important Notes

1. Use --no-dir-entries flag: When creating the zip file, use the --no-dir-entries flag to avoid extraction issues:

   zip -r package.dxt . --no-dir-entries
   

2. Binary permissions: Ensure the Rust binary has executable permissions before packaging:

   chmod +x tauri-mcp
   

3. Cross-platform builds: For distributing to other platforms, you'll need to build the Rust binary on each target platform or use cross-compilation.

Project Structure

tauri-mcp/
├── src/
│   ├── main.rs          # Entry point
│   ├── server.rs        # MCP server implementation
│   ├── tools/           # Tool implementations
│   │   ├── process.rs   # Process management
│   │   ├── window.rs    # Window manipulation
│   │   ├── input.rs     # Input simulation
│   │   ├── debug.rs     # Debugging tools
│   │   └── ipc.rs       # IPC interaction
│   └── utils/           # Utility modules
├── examples/            # Example Tauri apps
└── tests/              # Integration tests

Examples

Testing a Tauri App

# Launch the server
tauri-mcp serve

# In your AI assistant:
# 1. Launch the app
# 2. Take a screenshot
# 3. Send some input
# 4. Check the logs
# 5. Stop the app

Automated Testing Script

import asyncio
from mcp import Client

async def test_tauri_app():
    client = Client("tauri-mcp")
    
    # Launch app
    result = await client.call_tool("launch_app", {
        "app_path": "./my-app",
        "args": ["--test-mode"]
    })
    process_id = result["process_id"]
    
    # Wait for app to start
    await asyncio.sleep(2)
    
    # Take screenshot
    await client.call_tool("take_screenshot", {
        "process_id": process_id,
        "output_path": "./test-screenshot.png"
    })
    
    # Send input
    await client.call_tool("send_keyboard_input", {
        "process_id": process_id,
        "keys": "Hello, Tauri!"
    })
    
    # Get logs
    logs = await client.call_tool("get_app_logs", {
        "process_id": process_id,
        "lines": 50
    })
    print("App logs:", logs)
    
    # Stop app
    await client.call_tool("stop_app", {
        "process_id": process_id
    })

asyncio.run(test_tauri_app())

Troubleshooting

Common Issues

1. Permission Denied on macOS

   • Grant accessibility permissions in System Preferences
   • Required for input simulation

2. Screenshot Fails

   • Ensure screen recording permissions are granted
   • Check if the app window is visible

3. WebDriver Connection Failed

   • Ensure the Tauri app has DevTools enabled
   • Check if ChromeDriver is installed for WebDriver support

Debug Mode

Enable debug logging:

TAURI_MCP_LOG_LEVEL=debug tauri-mcp serve

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Implements the Model Context Protocol specification
• Designed for Tauri v2 applications
• Input simulation powered by enigo
• Screenshot functionality via screenshots-rs