AI Assistant MCP
About
Jarvis like AI, with web surfing capabilities and MCP server
Details
- Author
- aldindugolli
- Downloads
- 292
- Categories
- AI
Jump to
- Interactive AI chat with context-aware conversations and history management.
- Real-time system monitoring dashboard (CPU, memory, disk, network).
- Process tracking, management, and resource usage alerts.
- File system operations (list, read, write) and process control.
- Secure API key authentication for all endpoints.
- Modern, responsive web UI with real-time updates.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
AI Assistant MCPCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Set up by cloning the repository, creating a Python virtual environment, installing dependencies, and adding a SECRET_KEY to your .env file. Start the Ollama service with ollama serve, then run python run.py. Access the web interface at http://localhost:8000 to chat with the AI, monitor system resources, manage files and processes, and view alerts. Interact programmatically through the documented API endpoints.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"ai assistant mcp": {
"Arrodes-2.0": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}
}McpServers
{
"Arrodes-2.0": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}AI Assistant MCP
A powerful AI assistant with system monitoring and control capabilities, built with FastAPI and Ollama.
Features
AI Chat Interface
- Interactive chat with AI assistant - Context-aware conversations - Support for new chat sessions - Chat history managementSystem Monitoring
- Real-time system metrics dashboard - CPU, memory, disk, and network monitoring - Process tracking and management - Resource usage alerts - Interactive charts and visualizationsSystem Control
- File system operations - Process management - System health checks - Secure API accessWeb Interface
- Modern, responsive design - Real-time updates - Easy navigation between features - User-friendly controlsSetup Instructions
1. Clone the repository:
git clone https://github.com/yourusername/book-writer.git
cd book-writer
2. Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
3. Install dependencies:
pip install -r requirements.txt
4. Set up environment variables:
Create a .env file with:
SECRET_KEY=your_secret_key_here
5. Start the Ollama service:
ollama serve
6. Run the application:
python run.py
Usage
Web Interface
Access the web interface athttp://localhost:8000:
- Chat with the AI assistant
- Monitor system resources
- Manage files and processes
- View system alerts
API Endpoints
Chat
-POST /chat - Send messages to the AI assistant
- GET / - Access the chat interface
System Monitoring
-GET /monitoring - Access the monitoring dashboard
- GET /monitoring/metrics - Get current system metrics
- GET /monitoring/history - Get historical metrics data
- GET /monitoring/alerts - Get system alerts
System Control
-GET /system/files/list/{path} - List directory contents
- GET /system/files/read/{path} - Read file contents
- POST /system/files/write - Write to a file
- GET /system/processes - List running processes
- GET /system/processes/{pid} - Get process details
- DELETE /system/processes/{pid} - Terminate a process
Security
- API key authentication for all endpoints
- Secure file system operations
- Process management safety checks
- Environment variable configuration
Development
Project Structure
src/
├── main.py # FastAPI application
├── ollama_client.py # AI integration
├── monitoring.py # System monitoring
├── system_ops.py # System operations
├── security.py # Security utilities
├── config.py # Configuration
└── templates/ # HTML templates
├── index.html # Chat interface
└── monitoring.html # Monitoring dashboard
Contributing
1. Fork the repository 2. Create a feature branch 3. Commit your changes 4. Push to the branch 5. Create a Pull RequestLicense
MIT LicenseSign in to leave a review
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