JARVIS MCP Server

JARVIS MCP Server

Enables macOS control, web scraping, news fetching, and workspace automation through an MCP server.

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JARVIS — Advanced AI Virtual Assistant

<img width="2926" height="1672" alt="image" src="https://github.com/user-attachments/assets/7b39c08f-5014-403c-a2a1-bc61a91a0d51" />

JARVIS is a futuristic, highly capable virtual assistant built with Electron and Python. It features a stunning "Stark Industries" HUD interface and leverages a multi-LLM architecture to provide real-time intelligence, system control, and automation.

🚀 System Architecture

1. Frontend (Electron HUD)

  • Visuals: A premium, glassmorphism-inspired "Iron Man" HUD with real-time audio visualizers (Arc Reactor), system stat monitors, and cinematic animations.
  • Speech Stack:
    • STT (Speech-to-Text): Supports Vosk (Local/Offline), Groq Whisper, and Sarvam.
    • TTS (Text-to-Speech): Integrated with Sarvam (Bulbul v3), Groq Orpheus, and native Web Speech API.
  • Interaction: Features a "Clap to Wake" cinematic sequence and always-on voice listening.

2. Backend (Python MCP Server)

  • Model Context Protocol (MCP): A dedicated Python server (mcp_server.py) provides JARVIS with "hands" to interact with the OS.
  • Capabilities:
    • macOS Control: Application launching, volume control, screen locking, screenshots, and system info.
    • Web Intelligence: Web scraping for summarization, news fetching via RSS, and advanced Chrome control via AppleScript.
    • Workspace Automation: One-command setup for 'Coding', 'Research', 'Relax', and 'Web Dev' modes.

3. Intelligence Layer

  • Groq (Llama 3.3/3.1): Used for sub-500ms intent detection and tool routing.
  • Gemini 3 Flash: The primary conversational brain, providing high-intelligence responses with minimal latency.
  • OpenRouter (Gemma 4): Fallback engine and advanced reasoning specialist.

🛠️ Setup & Installation

Prerequisites

  • macOS (Optimized for Mac; some features may not work on Windows).
  • Node.js (v18+)
  • Python 3.10+

1. Clone & Install Dependencies

# Install JS dependencies
npm install

# Install Python dependencies
pip install fastmcp psutil feedparser requests beautifulsoup4

2. Environment Configuration

Create a .env file in the root directory and add your API keys:

GROQ_API_KEY=gsk_...
GEMINI_API_KEY=AIza...
OPENROUTER_API_KEY=sk-or-...
SARVAM_API_KEY=your_sarvam_key

3. Run the App

npm start

Note: On first run, it will download the Vosk model (~40MB) if not present in the models/ folder.


📦 Exporting & Distribution

To package the application into a standalone macOS .app or .dmg file:

npm run build

The build output will be located in the dist/ folder.


🔧 Core Features

  • "Hey JARVIS": Start speaking anytime to interact.
  • "Clap to Wake": A loud clap wakes JARVIS up with a cinematic intro sequence.
  • Workspace Modes: Say "Setup coding workspace" to automatically open Terminal, VS Code, and relevant browser tabs.
  • System Telemetry: Real-time monitoring of CPU, RAM, and Network on the HUD.
  • Memory System: JARVIS remembers facts you tell it about yourself (name, profession, etc.) across sessions.

👨‍💻 Created By

Akshat Singh — Tech Creator & Developer. Designed to bring the future to the present.

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