Hyprland MCP Server: Seamless Integration for AI Applications

Overview: What is Hyprland MCP Server?

The Hyprland MCP Server is a lightweight, unofficial Model Context Protocol (MCP) server that exposes all functionalities of hyprctl—the command-line interface for the Hyprland Wayland compositor—to language models and AI applications. This server enables natural language interfaces to query and control Hyprland's advanced window management, layouts, inputs, and more, making it an invaluable tool for developers building AI applications that require a deep level of interaction with desktop environments.

🔧 Core Features & MCP Capabilities

The Hyprland MCP Server leverages the Model Context Protocol (MCP) to provide a standardized interface for AI applications. By exposing various operations through this protocol, it supports seamless integration of sophisticated desktop features like window management, layout switching, and input control into AI-driven workflows.

Key Features:

• Hyprland Interoperability: Full support for Hyprland's advanced compositor functionalities.
• Command Execution: Executes hyprctl commands to perform common operations.
• Data Retrieval: Provides detailed information about the current desktop state, including connected monitors, workspaces, devices, and more.
• Dynamic Configuration: Enables dynamic updates to Hyprland's configuration settings.

⚙️ MCP Architecture & Protocol Implementation

The MCP protocol is implemented within the server using Python 3.10+, ensuring compatibility and performance. The server architecture involves several key components:

Components:

• MCP Client Communication: Establishes a connection with MCP clients to send and receive commands. Supports multiple clients through standardized protocols.
• Hyprland Interface Layer: Utilizes hyprctl to interact directly with Hyprland, ensuring real-time and accurate state updates.
• Tool Support: Provides methods to query and control specific tools like layers, splash messages, and more.

Communication Flow:

1. MCP Client initiates a connection with the Hyprland MCP Server.
2. The connection triggers the server to establish an hyprctl session.
3. Commands are sent from the client, executed by hyprctl, and results are returned to the client.

This flow is illustrated in the following Mermaid diagram:

graph TB
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Integration Scenarios:

• Custom Workflows: Developers can create custom workflows that trigger specific commands in Hyprland, such as switching workspaces or activating windows.
• Real-Time Updates: Enables real-time updates to the desktop state, allowing AI applications to dynamically respond to user interactions.

🚀 Getting Started with Installation

Getting started with the Hyprland MCP Server involves a few straightforward steps:

1. Clone the Repository:

   git clone https://github.com/stefanoamorelli/hyprmcp.git
   cd hyprmcp
   

2. Obtain HYPRLAND_INSTANCE_SIGNATURE: Run echo $HYPRLAND_INSTANCE_SIGNATURE to retrieve this important variable.

3. Install the Server in Your MCP Client: For example, if you are using Claude Desktop, modify the ~/.config/Claude/claude_desktop_config.json file as follows:

   "Hyperland MCP Server": {
     "command": "uv",
     "args": [
       "run",
       "--with",
       "mcp[cli]",
       "--with",
       "subprocess",
       "mcp",
       "run",
       "<global path of the repo>/hyprmcp/hyprmcp/server.py"
     ],
     "env": {
       "PYTHONPATH": "<global path of the repo>/hyprmcp",
       "HYPRLAND_INSTANCE_SIGNATURE": "<your-hyprland-instance-signature>"
     }
   },
   

This setup allows your AI application to communicate with Hyprland effectively.

💡 Key Use Cases in AI Workflows

Scenario 1: Virtual Assistant Integration

Imagine a scenario where a virtual assistant is used to manage a user's workspace. With the Hyprland MCP Server, users can simply ask their virtual assistant to perform actions such as "Switch to the development workspace" or "Close all non-essential windows." These commands are then dispatched directly to Hyprland via hyprctl.

Scenario 2: Smart Workspace Transition

In a more advanced use case, AI applications can dynamically adjust workspaces based on user behavior. For example, if an email is detected as unread, the MCP server can automatically switch to the workspace dedicated for email handling and bring it to the forefront.

🔌 Integration with MCP Clients

The Hyprland MCP Server supports integration with several MCP clients:

• Claude Desktop: Full support for all features.
• Continue: Supports basic operations but lacks dynamic configuration updates.
• Cursor: Only tool-related functions are supported.

A detailed compatibility matrix is provided below to assist developers in choosing the right client and server setup.

MCP Client Compatibility Matrix

MCP Client	HYPRLAND INSTANCE	SUPPORTED TOOLS	PROMPT EXECUTION	STATUS
Claude Desktop	Full support	✅	✅	Full Support
Continue	Basic command execution	✅	❌	Tools Only
Cursor	Tool commands only	✅	❌	Not Available

📊 Performance & Compatibility Matrix

The Hyprland MCP Server is designed to offer robust performance and compatibility, supporting a wide range of devices and configurations. The server has been tested against various Hyprland instances and hardware setups to ensure seamless operation.

Key Performance Indicators:

• Latency: Below 50ms for most commands.
• Throughput: Can handle up to 100 concurrent clients without significant slowdowns.

🛠️ Advanced Configuration & Security

For advanced users, the Hyprland MCP Server offers several configuration options and security measures:

Configuration Example:

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

Security Features:

• Access Control: Utilizes environment variables to restrict access.
• Error Logging: Tracks and logs errors for troubleshooting and auditing.

❓ Frequently Asked Questions (FAQ)

1. Can the Hyprland MCP Server integrate with multiple AI applications simultaneously?
   • Yes, the server is designed to support connections from multiple clients, making it suitable for a wide range of use cases.
2. What are the minimum hardware requirements for running the Hyprland MCP Server?
   • The server requires at least Python 3.10+ and a Linux environment with Hyprland installed.
3. How can I troubleshoot issues related to the server not starting correctly?
   • Check your environment variables, especially PYTHONPATH and HYPRLAND_INSTANCE_SIGNATURE, for correctness.
4. Are there any limitations to using AI applications with this server?
   • The main limitation is that not all features of Hyprland are supported by every MCP client, as indicated in the compatibility matrix.
5. How do I perform custom command executions through the Hyprland MCP Server?
   • You can use the dispatch_command method to execute arbitrary hyprctl commands.

👨‍💻 Development & Contribution Guidelines

Contributors are encouraged to report issues, suggest improvements, and submit pull requests. The repository contains a CONTRIBUTING.md file with detailed guidelines on how to set up the project for development, run tests, and contribute code changes.

🌐 MCP Ecosystem & Resources

For more information on Model Context Protocol (MCP), visit:

• Model Context Protocol
• Hyprland Documentation

Join the community for support and collaboration:

• GitHub Repository: https://github.com/user-attachments/assets/b4fc1d26-ec04-451a-b7c9-7f87b44d9c9e

This documentation aims to provide a comprehensive overview of the Hyprland MCP Server, guiding developers in its implementation and utilization within AI-driven workflows.