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Enables AI agents to provision and terminate AWS EC2 instances using natural language commands.

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Описание

Enables AI agents to provision and terminate AWS EC2 instances using natural language commands.

README

Welcome to MCP-AWS, a simple yet powerful AI-driven application that leverages OpenAI Agents and MCP servers to manage AWS EC2 instances. This app allows you to provision and terminate EC2 instances using natural language commands in your terminal. 🖥️✨


🎥 Demo Video

Watch the demo video to see MCP-AWS in action! 🚀

Watch the Demo


🌟 Features

  1. Provision EC2 Instances: Just tell the AI agent to create an EC2 instance, and it will handle the rest, providing you with the instance ID. 🛠️
  2. Terminate EC2 Instances: Provide the instance ID, and the agent will terminate the instance for you. ❌
  3. MCP Server Integration: Explore how custom MCP servers can be created and integrated with OpenAI Agents SDK. 🧩

🛠️ Tools in the MCP Server

The MCP server is a custom server with two tools:

  1. initiate_aws_ec2_instance: Creates an AWS EC2 instance.
  2. terminate_aws_ec2_instance: Terminates an AWS EC2 instance by its ID.

🚀 Getting Started

Prerequisites

  1. Python 3.12+ (for local setup) or Docker (for containerized setup)
  2. AWS IAM Role: Create an IAM role with the necessary permissions to manage EC2 instances.
  3. Environment Variables: Prepare a .env file with the following variables:
    • AWS_ACCESS_KEY_ID
    • AWS_SECRET_ACCESS_KEY
    • AWS_DEFAULT_REGION
    • OPENAI_API_KEY
    • AMI_ID
    • INSTANCE_TYPE
    • KEY_NAME
    • SECURITY_GROUP_IDS
    • AWS_REGION

🏃‍♂️ Running the App

  1. Clone the repository:
    git clone https://github.com/anirban1592/mcp-server-aws.git
    cd mcp-aws
    
  2. Create .env file as shown in prerequisites

Option 1: Docker Setup (Recommended)

  1. Build the Docker image:
    docker image build -t my-mcp .
    
  2. Run the container:
    docker container run -it my-mcp
    

Option 2: Local Setup

  1. Create and activate virtual environment:

    pip install uv
    uv venv .venv
    # Windows
    .venv\Scripts\activate
    # Unix/MacOS
    source .venv/bin/activate
    
  2. Run the application:

    cd openai-agent/
    uv run agent.py
    

💬 Using the AI Agent

  1. To create an EC2 instance:

    Enter your command: Create an EC2 instance
    
  2. To terminate an EC2 instance:

    Enter your command: Terminate EC2 instance with ID <instance-id>
    

⚠️ Word of Caution

  • IAM Role and Credentials: Please create AWS IAM roles and credentials at your own risk. Ensure you follow AWS best practices for security.
  • Billing and Security: This app is a proof of concept (POC) and is intended for learning purposes only. We are not responsible for any billing issues or security incidents.

📚 Learnings

This project demonstrates:

  1. How to integrate MCP servers with OpenAI Agents SDK
  2. How to build a simple AI-driven application for AWS resource management

Enjoy exploring the power of AI and MCP servers! 🌟

from github.com/anirban1592/mcp-server-aws

Установка AWS

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/anirban1592/mcp-server-aws

FAQ

AWS MCP бесплатный?

Да, AWS MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для AWS?

Нет, AWS работает без API-ключей и переменных окружения.

AWS — hosted или self-hosted?

Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.

Как установить AWS в Claude Desktop, Claude Code или Cursor?

Открой AWS на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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