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AI Assistant MCP Server

@aldindugolli

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

aldindugolli

关于 AI Assistant MCP Server

Jarvis like AI, with web surfing capabilities and MCP server

#ai-assistant#system-monitoring#web-surfing

AI Assistant MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "Arrodes-2.0": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

AI Assistant MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is AI Assistant MCP?

AI Assistant MCP is a powerful AI assistant with system monitoring and control capabilities, built with FastAPI and Ollama. It provides an interactive chat interface alongside real-time system metrics, file operations, and process management, all accessible via a modern web interface and RESTful API.

How to use AI Assistant MCP?

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.

Key features of AI Assistant MCP

  • 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.

Use cases of AI Assistant MCP

  • Query system resource usage (CPU, memory, disk, network) via natural language.
  • Manage files and processes remotely through chat commands or API calls.
  • Automate system health checks and receive alerts on resource thresholds.
  • Build custom tools that combine AI assistance with direct system control.

常见问题

1

How is authentication handled?

All API endpoints require API key authentication. Configure the key in your `.env` file under `SECRET_KEY`.

2

What are the system requirements?

You need Python, Ollama (to run the AI model), and the dependencies listed in `requirements.txt`. Ollama must be running locally before starting the application.

3

How do I start the AI Assistant MCP server?

Clone the repo, install dependencies, set environment variables, start Ollama with `ollama serve`, and then run `python run.py`. The web interface is available at `http://localhost:8000`.

4

What API endpoints are available?

Chat: `POST /chat`. Monitoring: `GET /monitoring`, `/monitoring/metrics`, `/monitoring/history`, `/monitoring/alerts`. System control: endpoints for listing/reading/writing files and listing/getting/terminating processes.

5

Can I monitor system resources in real time?

Yes. The monitoring dashboard provides real-time metrics (CPU, memory, disk, network) with interactive charts and visualizations, plus resource usage alerts.

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