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

How is authentication handled?

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

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.

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`.

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.

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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