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MCP Client Application

MCP Client Application

github.com/regibyteFrameworks & SDKs11Updated 84w ago
Repository

About MCP Client Application

A cross-platform desktop application for chat conversations with Claude, GPT, and other LLMs through MCP. Provides MCP server management, tool execution with user approval, conversation history, and secure credential storage.

Key features

  1. 01Multi-model LLM support
  2. 02MCP server registration and configuration
  3. 03Real-time streaming responses
  4. 04Tool execution with permission system
  5. 05Conversation history and secure vault

Use cases

  1. 01Chat conversations with AI assistants
  2. 02Executing automated tasks via MCP tools
  3. 03Managing multiple MCP server connections
  4. 04Learning MCP application development

MCP support

The application connects to MCP servers and integrates their tools into the chat interface, allowing users to execute tools through AI model requests with explicit user approval.

Details

From the project README

MCP Client Application

A desktop application for interacting with AI models via the Model Context Protocol (MCP), providing a powerful interface for chat conversations with tool execution capabilities.

What is MCP?

The Model Context Protocol (MCP) is a standardized communication protocol that enables AI models to request execution of tools and functions with user confirmation. This creates a secure and transparent environment for AI assistants to interact with your system while maintaining user control.

Features

  • 🤖 Multi-model support: Connect to Claude, GPT, and other LLMs through a unified interface
  • 🔧 Tool execution: Allow AI models to perform actions through a secure permission system
  • 🔄 Real-time streaming: Experience fluid conversations with streaming responses
  • 🔌 Server management: Register, configure and connect to MCP servers
  • 💾 Conversation history: Save and revisit your chat sessions
  • 🔐 Secure vault: Store sensitive information like API keys safely

Why Use MCP Client?

MCP Client demonstrates how to create applications that leverage the full potential of modern AI systems while maintaining appropriate security boundaries. It serves as both a practical tool and a learning resource for developers interested in building applications with AI capabilities.

Getting Started

Prerequisites
  • Node.js 18+
  • npm package manager
Installation
# Clone the repository
git clone [email protected]:RegiByte/mcp-client-app.git
cd mcp-client-app

# Install dependencies
npm install

# Start the development server
npm dev
Building for Production
# For Windows
npm build:win

# For macOS
npm build:mac

# For Linux
npm build:linux

Using the Application

Starting a Conversation
  1. Open the application
  2. Navigate to the conversations page
  3. Click on "New conversation"
  4. Start chatting!
Working with Tools

When an AI assistant needs to perform an action:

  1. You'll see a tool execution request in the chat
  2. Review the requested action and parameters
  3. Approve or deny the request
  4. See the results integrated back into the conversation

Architecture Overview

The MCP Client App is built with:

  • Electron: For cross-platform desktop capabilities
  • React: For the user interface
  • TypeScript: For type-safe code
  • Vercel AI SDK: For standardized AI model interactions
  • Model Context Protocol: For secure and standardized tool execution

The application uses a driver pattern to support multiple LLM providers while maintaining a consistent interface.

Learning Resources

Contributing

We welcome contributions to the MCP Client App! Please see our CONTRIBUTING.md for guidelines.

License

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

Acknowledgments

  • The Anthropic team for Claude and MCP
  • Vercel for the AI SDK
  • The Electron community for the application framework

Project maintained by @RegiByte. For support, open an issue on the repository.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.