Skip to content

README.md

Latest commit

 

History

History
117 lines (82 loc) · 4.46 KB

README.md

File metadata and controls

117 lines (82 loc) · 4.46 KB

Matrix MCP v2.0

Note

Official Promotional Homepage: https://lim-asdk.github.io/Matrix_MCP_V2/
Technical Documentation (README): This guide focuses on installation, configuration, and architecture.

English | 한국어

Status License Python MCP

Professional MCP Operation Workspace.
A specialized environment for connecting, testing, and managing Model Context Protocol (MCP) servers and AI profiles across Web and Desktop environments.

📖 Project Overview

Matrix MCP is a specialized workspace focused on the operational aspects of the Model Context Protocol. Unlike standard chat clients, it provides a structured environment for managing the full lifecycle of MCP connections and AI tool-calling workflows.

Key Capabilities

  • Native MCP Support: Direct integration with stdio and SSE transport layers for real-time tool execution.
  • Provider Agnostic: Seamlessly bridge any OpenAI-compatible API (Grok, OpenAI, DeepSeek, Google Gemini) to your MCP tools.
  • Hybrid Runtime: Optimized for both Web-first browser interaction and Windows Desktop native stability (WebView2).
  • Operator Inspector: Real-time monitoring of raw tool requests, responses, and AI reasoning chains for debugging and optimization.

🚀 Quick Start

1. Installation

Ensure you have Python 3.10+ installed on your system.

# Clone the repository
git clone https://github.com/lim-asdk/Matrix_MCP_V2.git
cd Matrix_MCP_V2

# Create a virtual environment
python -m venv .venv

Activate Environment:

  • Windows (PowerShell/CMD): .venv\Scripts\activate
  • macOS/Linux: source .venv/bin/activate
# Install dependencies
pip install -r requirements.txt

2. Configuration

Copy the template environment file and provide your AI API credentials.

# Copy template
copy .env.example .env

# Edit .env and provide your settings:
# OPENAI_API_KEY=your_key_here
# OPENAI_BASE_URL=https://api.x.ai/v1 (or preferred provider)

3. Execution

Run the workspace in your preferred mode.

  • Web Mode (Primary): python run_web_server.py
  • Desktop Mode (Windows Native): python run_desktop_app.py

⚙️ Run Modes

Mode Entry Point Target Platform Description
Web-First run_web_server.py Universal / Browser Recommended. Runs as a local server accessible via any modern browser. Supports the latest web features.
Desktop run_desktop_app.py Windows Native Wrapper utilizing WebView2. Provides a dedicated window experience and desktop lifecycle management.

🏛️ Architecture Overview (L1-L5)

The project follows a layered modular architecture optimized for separation of concerns and protocol flexibility.

Layer Responsibility Description
L5 (Presentation) UI/UX Frontend logic and assets located in lim_arsenal/engine/L5_Presentation.
L4 (Bridge) API Gateway Protocol transformation and communication bridge (bridge_api.py).
L3 (Protocol) MCP Logic Core Model Context Protocol handling and server management.
L2 (Engine) Core Logic Backend services and system management modules.
L1 (Infrastructure) Runtime/OS Python environment, file system persistence, and OS-level interactions.

🔗 Official Test Node

Validate your setup with our public SSE test endpoint:

🏗️ Directory Structure

  • lim_arsenal/engine/: Core backend and frontend assets.
  • installer_output/: Build artifacts and setup executables.
  • config/: Application and user configuration files.
  • docs/: Technical documentation and planning resources.

🏛️ Project Identity

Matrix MCP is a project by Lim Arsenal (lim-asdk).
Licensed under PolyForm Noncommercial License 1.0.

© 2026 Lim Arsenal. All rights reserved.