AI Assistant MCP
@aldindugolli
AI Assistant MCP について
Jarvis like AI, with web surfing capabilities and MCP server
基本情報
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.
「AI とエージェント」の他のコンテンツ
Gemini MCP Server
aliargunMCP server implementation for Google's Gemini API
Model Context Protocol Server for Home Assistant
tevonsbA MCP server for Home Assistant
Hass-MCP
voskaControl and query Home Assistant from Claude and other LLMs — a Model Context Protocol (MCP) server.
Mcp Agent
lastmile-aiBuild effective agents using Model Context Protocol and simple workflow patterns
欢迎来到 智言平台
Shy2593666979AgentChat 是一个基于 LLM 的智能体交流平台，内置默认 Agent 并支持用户自定义 Agent。通过多轮对话和任务协作，Agent 可以理解并协助完成复杂任务。项目集成 LangChain、Function Call、MCP 协议、RAG、Memory、HITL、Skill、Milvus 和 ElasticSearch 等技术，实现高效的知识检索与工具调用，使用 FastAPI 构建高性能后端服务。
コメント