MCP.so
ログイン

AI Assistant MCP

@aldindugolli

リポジトリ

AI Assistant MCP について

Jarvis like AI, with web surfing capabilities and MCP server

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

基本情報

カテゴリ

AI とエージェント

ランタイム

powershell

トランスポート

stdio

公開者

aldindugolli

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.

FAQ from AI Assistant MCP

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.

コメント

「AI とエージェント」の他のコンテンツ

Gemini MCP Server

aliargun

MCP server implementation for Google's Gemini API

259

Intervals.icu MCP Server

mvilanova

Model Context Protocol (MCP) server for connecting Claude and ChatGPT with the Intervals.icu API.

311

Open Multi-Agent Canvas

CopilotKit

The open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation and add MCP servers for deep research

507

LinkedIn MCP Server

stickerdaniel

Open-source MCP server for LinkedIn. Give Claude and any MCP-compatible AI agent access to profiles, companies, jobs, and messages.

2.7K

1Panel

1Panel-dev

🔥 1Panel is a modern, open-source VPS control panel — and the only one with native AI agent support. Run Ollama models, deploy OpenClaw agents, and manage your entire server stack from one clean web interface.

36.1K