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<h1 align="center">MCP Desk</h1>

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MCP Desk - Your Own MCP Client built with Electron, React, and TypeScript.
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Application Interface Gallery

Explore the visual design and functionality of MCP Desk through these screenshots:

Here are some screenshots showcasing the mcp-desk application:

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<details>
<summary>Table of Contents</summary>
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<li><a href="#application-interface-gallery">Application Interface Gallery</a></li>
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<a href="#about-the-project">About The Project</a>
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<li><a href="#key-features">Key Features</a></li>
<li><a href="#built-with">Built With</a></li>
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<a href="#getting-started">Getting Started</a>
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<li><a href="#prerequisites">Prerequisites</a></li>
<li><a href="#installation">Installation</a></li>
<li><a href="#development">Development</a></li>
<li><a href="#build">Build</a></li>
<li><a href="#download-pre-built-application">Download Pre-built Application</a></li>
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<li><a href="#usage">Usage</a></li>
<li><a href="#contributing">Contributing</a></li>
<li><a href="#contact">Contact</a></li>
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About The Project

mcp-desk is a desktop application designed to serve as a client for interacting with Multi-Capability Platform (MCP) servers. Built using modern web technologies within the Electron framework, it provides a user-friendly interface for managing MCP configurations and leveraging AI agent capabilities, including tool usage powered by models like those from OpenRouter via Langchain.

The application features a chat interface for interacting with AI agents, settings management for MCP server configurations, and the ability to import/export application settings.

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Key Features

- Electron Desktop Application: Cross-platform compatibility (Windows, macOS, Linux).
- React Frontend: Modern UI built with React and TypeScript.
- Shadcn UI & Tailwind CSS: Utilizes Shadcn UI components and Tailwind CSS (v3) for a consistent and utility-first styling approach.
- MCP Client: Connect to and interact with MCP servers using easy-mcp-use.
- AI Agent Chat: Integrated chat interface powered by Langchain and OpenRouter models.
- Tool Usage: Supports AI models capable of tool calling.
- Model Selection: Allows users to select different LLM models.
- Settings Management: Configure MCP server details and manage application settings.
- Import/Export: Backup and restore application settings (stored in localStorage) via JSON files.
- Markdown Support: Renders assistant messages in Markdown format within the chat UI.
- IPC Communication: Efficient communication between the main and renderer processes.

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Built With

Electron - Cross-platform desktop app framework
Electron Vite - Build toolchain for Electron
React - UI library
TypeScript - Strongly typed JavaScript
Tailwind CSS (v3) - Utility-first CSS framework
Shadcn UI - Re-usable UI components
Langchain - Framework for developing applications powered by language models
OpenRouter - AI models and API
easy-mcp-use - Library for interacting with MCP servers

Download Latest Release (v1.0.0)

Download the appropriate file for your system (.dmg for macOS, .exe for Windows) and install it as you would any other application.

Note for Linux Users: Currently, pre-built packages for Linux are not available in the release. Linux users should follow the <a href="#installation">Installation</a> and <a href="#build">Build</a> instructions to set up the project locally and then run pnpm build:linux to generate the Linux distribution file.

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Prerequisites (for Development)

Node.js (Check package.json engines or project requirements for specific version)
pnpm package manager

    npm install -g pnpm

    

Installation

1. Clone the repository (Update URL if needed)

    git clone https://github.com/debsouryadatta/mcp-desk.git

    cd mcp-desk

    

    pnpm install

    

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Development

To run the application in development mode with hot-reloading:

pnpm run dev

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Build

To build the application for distribution:

# For Windows
pnpm run build:win
For macOS
pnpm run build:mac
For Linux
pnpm run build:linux

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Usage

After launching the application (pnpm run dev or by running the built executable):

1. Configure MCP Server: Navigate to the settings section to input your MCP server configuration details.
2. Select LLM Model: Choose your preferred language model from the available options.
3. Interact via Chat: Use the chat interface to send requests to the configured AI agent.
4. Manage Settings: Use the import/export functionality in settings to back up or restore your configurations.

Refer to the application's UI for more detailed usage instructions.

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Contributing

Contributions are welcome! If you have suggestions for improving mcp-desk, please feel free to contribute.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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Contact

Debsourya Datta - X Profile @debsourya005 - Email debsouryadatta@gmail.com

Project Link: https://github.com/debsouryadatta/mcp-desk

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