Qubase MCP

A powerful, cross-platform AI Chat Client implementing the Model Context Protocol (MCP) for seamless AI interactions.

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Overview

Qubase MCP is a sophisticated chat interface that revolutionizes AI interactions on desktop and mobile devices. Built with Flutter and implementing the Model Context Protocol, it provides a unified interface for multiple Large Language Models (LLMs) while ensuring secure, efficient, and context-aware conversations.

Features

Core Capabilities

Feature	Description
Universal Compatibility	Works seamlessly across all major platforms
Model Flexibility	Connect to any supported LLM without changing workflow
Context Awareness	Leverages MCP for maintaining conversation context
Enterprise Ready	Built with security and scalability in mind

Platform Support

Platform	Status
Desktop (macOS, Windows, Linux)	Available
Mobile (iOS, Android)	Available
Web	Coming Soon

Supported AI Models

• OpenAI (GPT-3.5, GPT-4)
• Anthropic Claude
• OLLama (Local Models)
• DeepSeek
• Custom Model Support

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Local LLM Setup

Android Setup

1. Install Termux

   • Download Termux ARM64 V8 from Termux GitHub
   • Install and open Termux
   • Run termux-setup-storage to grant storage permissions
   • Run termux-change-repo to select package mirror
   • Update with pkg upgrade

2. Required Packages

   # Install Tur repository
   pkg install tur-repo
   
   # Install Ollama and Zellij
   pkg install ollama
   pkg install zellij

3. Android Configuration

   • Enable Developer Options: Settings > About device > Tap "Build number" 7 times
   • In Developer options, enable "Disable child process restrictions"

4. Model Operations

   # Start Ollama server
   ollama serve
   
   # In a new terminal, run models:
   ollama run deepseek-r1.5b  # For DeepSeek
   ollama run llama3.2        # For Llama3

5. Control Commands

   Action	Command
   Stop output	CTRL + C
   Exit model	CTRL + D
   Clear screen	CTRL + L
   Stop server	ps aux | grep ollama then kill [PID]

Desktop Setup

Coming soon...

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System Requirements

Hardware Requirements

Component	Minimum	Recommended
RAM	4GB	8GB
Storage	2GB free	4GB free
Processor	Intel/AMD x64 or ARM64	Modern multi-core

Software Requirements

Component	Version
Windows	10 or later
macOS	10.15 or later
Ubuntu	20.04 or later
Flutter SDK	3.0 or later
Git	Latest stable

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Installation Guide

Prerequisites

1. Flutter Setup

   git clone https://github.com/flutter/flutter.git
   export PATH="$PATH:`pwd`/flutter/bin"
   flutter doctor

2. System Dependencies

   # Linux
   sudo apt-get update
   sudo apt-get install libsqlite3-0 libsqlite3-dev
   
   # macOS
   brew install sqlite3
   
   # Windows
   # SQLite included in Flutter Windows setup

3. Development Tools

   # Using uv (Recommended)
   brew install uv
   
   # Alternative: npm
   brew install node

Application Setup

1. Installation

   git clone https://github.com/qubasehq/Qmcp.git
   cd Qmcp
   flutter pub get

2. Launch

   # Desktop platforms
   flutter run -d <platform>  # macos, windows, linux
   
   # Mobile development
   flutter run -d <device-id>

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Configuration

Initial Setup

1. API Configuration

   • Launch Qubase MCP
   • Navigate to Settings > API Configuration
   • Enter LLM API credentials
   • Configure custom endpoints (if needed)

2. MCP Server Setup

   • Access Settings > MCP Server
   • Choose installation method
   • Configure server settings
   • Select default AI model

File Locations

Purpose	Path
Configuration	~/Library/Application Support/qubase_mcp/mcp_server.json
Logs	~/Library/Application Support/run.daodao.qubase_mcp/logs
Application Data	~/Library/Application Support/qubase_mcp

Reset Application

# Clear all data (use with caution)
rm -rf ~/Library/Application\ Support/run.daodao.qubase_mcp
rm -rf ~/Library/Application\ Support/qubase_mcp

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Troubleshooting

Issue	Solution
Connection Issues	Verify API keys and network connectivity
Performance Problems	Check system resources and clear cache
Model Errors	Validate model configurations and quotas

For additional support, visit our Issues page.

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Development Roadmap

Upcoming Features

Feature	Description
MCP Server Marketplace	Easy discovery and deployment of community servers
Enhanced Integration	Automated server setup and cloud sync support
RAG Implementation	Document processing and knowledge base integration
UI/UX Improvements	Custom themes, keyboard shortcuts, mobile optimization

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Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to your branch
5. Open a Pull Request

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Acknowledgments

• Model Context Protocol (MCP) Team
• MCP CLI Contributors
• Flutter Community
• Open Source AI Community

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License

Licensed under Apache License 2.0 - see the LICENSE file for details.