ChatMCP - Cross-Platform AI Chat Client Implementing MCP Protocol
Overview
ChatMCP is an AI chat client implementing the Model Context Protocol (MCP), created by developer daodao97. This project aims to provide a unified cross-platform AI conversation interface, supporting various AI models and MCP servers, allowing users to interact with different data sources and AI services through a single application.
Core Features and Characteristics
🌐 Cross-Platform Support
- Desktop: Supports macOS, Windows, and Linux systems
- Mobile: Provides iOS and Android applications
- Unified Experience: Maintains a consistent user interface and functionality across all platforms
🤖 Multi-AI Model Integration
- OpenAI Models: Supports GPT series models
- Claude Models: Integrates Anthropic's Claude AI
- Ollama Models: Supports locally deployed open-source models
- DeepSeek Models: Integrates DeepSeek AI services
- Flexible Configuration: Supports custom API keys and endpoints
🔌 MCP Protocol Support
- MCP Server Marketplace: Built-in MCP server marketplace, providing a rich selection of data sources
- Automatic Installation: One-click installation and configuration of MCP servers
- SSE Transmission: Supports Server-Sent Events (SSE) MCP transmission protocol
- Automatic Selection: Intelligently selects the appropriate MCP server to handle requests
💬 Intelligent Conversation Features
- Chat History: Complete conversation history saving and management
- Contextual Understanding: Rich context processing based on the MCP protocol
- Multi-Data Source Interaction: Dialogue with different types of data through MCP servers
🎨 User Experience Optimization
- Theme Switching: Supports dark/light themes
- Modern UI: Elegant user interface design
- Responsive Layout: Adapts to different screen sizes and devices
Platform Download and Installation
| Platform |
Download Method |
Remarks |
| macOS |
Release |
Download the installation package directly |
| Windows |
Release |
Download the installation package directly |
| Linux |
Release |
Requires installation of dependency libraries |
| iOS |
TestFlight |
Test version |
| Android |
Release |
Download the APK directly |
Linux System Dependencies
sudo apt-get install libsqlite3-0 libsqlite3-dev
Quick Start
1. Environment Preparation
Ensure that one of the following tools is installed on your system:
# Install uvx
brew install uv
# Or install npx
brew install node
2. Configuration Steps
- Configure LLM API: Configure your LLM API key and endpoint in the settings page
- Install MCP Server: Install the required MCP server from the MCP server page
- Start Conversation: Engage in intelligent conversations with the MCP server
3. Data Storage Location
- macOS:
~/Library/Application Support/ChatMcp
- Windows:
%APPDATA%\ChatMcp
- Linux:
~/.local/share/ChatMcp
- Mobile: Application document directory
4. Reset Application
To reset application data, use the following commands:
# macOS
rm -rf ~/Library/Application\ Support/ChatMcp
# Windows
rd /s /q "%APPDATA%\ChatMcp"
# Linux
rm -rf ~/.local/share/ChatMcp
Development Guide
Local Development
# Get dependencies
flutter pub get
# Run macOS version
flutter run -d macos
Test Database
The project provides a test database file. You can download test.db to test the SQLite MCP server functionality.
MCP Server Configuration
The MCP server configuration file is located at:
~/Library/Application Support/ChatMcp/mcp_server.json
Technical Features
Implemented Features
- ✅ Conversation with MCP Server: Complete MCP protocol implementation
- ✅ MCP Server Marketplace: Rich server ecosystem
- ✅ Automatic Installation of MCP Server: Simplified deployment process
- ✅ SSE MCP Transmission Support: Real-time communication capabilities
- ✅ Automatic Selection of MCP Server: Intelligent routing functionality
- ✅ Chat History Recording: Complete conversation management
- ✅ Multi-AI Model Support: OpenAI, Claude, Ollama, DeepSeek
- ✅ Theme Switching: Dark/Light mode
Planned Features
- 🔄 RAG Functionality: Retrieval Augmented Generation
- 🔄 Better UI Design: Continuous optimization of user experience
Application Scenarios
Data Analysis and Query
- Database Interaction: Natural language queries with various databases through MCP servers
- File Analysis: Analyzing and processing file data in various formats
- API Integration: Intelligent interaction with third-party API services
Development Assistance
- Code Understanding: Analyzing and explaining codebases
- Documentation Query: Intelligent search and understanding of technical documentation
- System Monitoring: Monitoring system status through MCP servers
Business Applications
- Customer Service: Building intelligent customer service systems
- Knowledge Management: Intelligent query of enterprise knowledge bases
- Workflow Automation: Automating various business processes
Technical Architecture
Core Technologies
- Flutter Framework: Cross-platform UI development
- MCP Protocol: Model Context Protocol implementation
- SQLite Database: Local data storage
- SSE Protocol: Real-time communication support
Extensibility Design
- Plugin Architecture: Extending functionality through MCP servers
- Multi-Model Support: Flexible AI model integration
- Cross-Platform Compatibility: Unified codebase supporting multiple platforms
Summary
ChatMCP represents a new direction in the development of AI chat clients. By implementing the MCP protocol, it not only provides a unified AI conversation interface but, more importantly, builds an extensible AI ecosystem. Its cross-platform support and multi-AI model integration enable it to meet the needs of different users, while the MCP server marketplace provides users with a rich selection of data sources and functional extensions.