# aws-mcp-server-devops-ai
## 基本信息
- Slug: `saifeezibrahim-aws-mcp-server-devops-ai`
- Source: modelscope
- Publisher: @saifeezibrahim/aws-mcp-server-devops-ai
- Categories: cloud-platforms / shell-access / developer-tools
- Hosted: No
- License: MIT License
- Source URL: https://www.modelscope.cn/mcp/servers/@saifeezibrahim/aws-mcp-server-devops-ai
## 简介
暂无描述。
## 安装提示

```bash
## Demo [Demo](https://private-user-images.githubusercontent.com/1898375/REDACTED.mp4?jwt=REDACTED.REDACTEDREDACTEDREDACTEDREDACTEDREDACTED.REDACTED) The video demonstrates using Claude Desktop with AWS MCP Server to create a new AWS EC2 instance with AWS SSM agent installed. ## Features - **Command Documentation** - Detailed help information for AWS CLI commands - **Command Execution** - Execute AWS CLI commands and return human-readable results - **Unix Pipe Support** - Filter and transform AWS CLI output using standard Unix pipes and utilities - **AWS Resources Context** - Access to AWS profiles, regions, account information, and environment details via MCP Resources - **Prompt Templates** - Pre-defined prompt templates for common AWS tasks following best practices - **Docker Integration** - Simple deployment through containerization with multi-architecture support (AMD64/x86_64 and ARM64) - **AWS Authentication** - Leverages existing AWS credentials on the host machine ## Requirements - Docker (default) or Python 3.13+ (and AWS CLI installed locally) - AWS credentials configured ## Getting Started **Note:** For security and reliability, running the server inside a Docker container is the **strongly recommended** method. Please review the [Security Considerations](#security-considerations) section for important considerations. ### Run Server Option 1: Using Docker (Recommended)
```

## MCP Server 详情

# AWS Model Context Protocol (MCP) Server

[![CI](https://github.com/alexei-led/aws-mcp-server/actions/workflows/ci.yml/badge.svg)](https://github.com/alexei-led/aws-mcp-server/actions/workflows/ci.yml)
[![Code Coverage](https://codecov.io/gh/alexei-led/aws-mcp-server/branch/main/graph/badge.svg?token=K8vdP3zyuy)](https://codecov.io/gh/alexei-led/aws-mcp-server)
[![Linter: Ruff](https://img.shields.io/badge/Linter-Ruff-brightgreen?style=flat-square)](https://github.com/alexei-led/aws-mcp-server)
[![Image Tags](https://ghcr-badge.egpl.dev/alexei-led/aws-mcp-server/tags?color=%2344cc11&ignore=latest&n=4&label=image+tags&trim=)](https://github.com/alexei-led/aws-mcp-server/pkgs/container/aws-mcp-server/versions)
[![Image Size](https://ghcr-badge.egpl.dev/alexei-led/aws-mcp-server/size?color=%2344cc11&tag=latest&label=image+size&trim=)](https://github.com/alexei-led/aws-mcp-server/pkgs/container/aws-mcp-server)

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP).

## Overview

The AWS MCP Server provides a bridge between MCP-aware AI assistants (like Claude Desktop, Cursor, Windsurf) and the AWS CLI. It enables these assistants to:

1. **Retrieve AWS CLI documentation** (`aws_cli_help`) - Get detailed help on AWS services and commands
2. **Execute AWS CLI commands** (`aws_cli_pipeline`) - Run commands with Unix pipes and receive formatted results optimized for AI consumption

```mermaid
flowchart LR
    AI[AI Assistant] <-->|MCP Protocol| Server[AWS MCP Server]
    Server <-->|Subprocess| AWS[AWS CLI]
    AWS <-->|API| Cloud[AWS Cloud]
```

## Demo

[Demo](https://private-user-images.githubusercontent.com/1898375/REDACTED.mp4?jwt=REDACTED.REDACTEDREDACTEDREDACTEDREDACTEDREDACTED.REDACTED)

The video demonstrates using Claude Desktop with AWS MCP Server to create a new AWS EC2 instance with AWS SSM agent installed.

## Features

- **Command Documentation** - Detailed help information for AWS CLI commands
- **Command Execution** - Execute AWS CLI commands and return human-readable results
- **Unix Pipe Support** - Filter and transform AWS CLI output using standard Unix pipes and utilities
- **AWS Resources Context** - Access to AWS profiles, regions, account information, and environment details via MCP Resources
- **Prompt Templates** - Pre-defined prompt templates for common AWS tasks following best practices
- **Docker Integration** - Simple deployment through containerization with multi-architecture support (AMD64/x86_64 and ARM64)
- **AWS Authentication** - Leverages existing AWS credentials on the host machine

## Requirements

- Docker (default) or Python 3.13+ (and AWS CLI installed locally)
- AWS credentials configured

## Getting Started

**Note:** For security and reliability, running the server inside a Docker container is the **strongly recommended** method. Please review the [Security Considerations](#security-considerations) section for important considerations.

### Run Server Option 1: Using Docker (Recommended)

```bash
# Clone repository
git clone https://github.com/alexei-led/aws-mcp-server.git
cd aws-mcp-server

# Build and run Docker container
docker compose -f deploy/docker/docker-compose.yml up -d
```

The Docker image supports both AMD64/x86_64 (Intel/AMD) and ARM64 (Apple Silicon M1-M4, AWS Graviton) architectures.

> **Note**: The official image from GitHub Packages is multi-architecture and will automatically use the appropriate version for your system.
>
> ```bash
> # Use the latest stable version
> docker pull ghcr.io/alexei-led/aws-mcp-server:latest
> 
> # Or pin to a specific version (recommended for production)
> docker pull ghcr.io/alexei-led/aws-mcp-server:1.0.0
> ```
>
> **Docker Image Tags**:
>
> - `latest`: Latest stable release
> - `x.y.z` (e.g., `1.0.0`): Specific version
> - `sha-<commit-sha>`: Development builds, tagged with Git commit SHA (e.g., `sha-gb697684`)

### Run Server Option 2: Using Python

**Use with Caution:** Running natively requires careful environment setup and carries higher security risks compared to the recommended Docker deployment. Ensure you understand the implications outlined in the [Security Considerations](#security-considerations) section.

```bash
# Clone repository
git clone https://github.com/alexei-led/aws-mcp-server.git
cd aws-mcp-server

# Set up virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e .

# Run the server
python -m aws_mcp_server
```

## Configuration

The AWS MCP Server can be configured using environment variables:

| Environment Variable      | Description                                  | Default   |
|--------------------------|REDACTED|-----------|
| `AWS_MCP_TIMEOUT`        | Command execution timeout in seconds         | 300       |
| `AWS_MCP_MAX_OUTPUT`     | Maximum output size in characters            | 100000    |
| `AWS_MCP_TRANSPORT`      | Transport protocol to use ("stdio" or "sse") | stdio     |
| `AWS_PROFILE`            | AWS profile to use                           | default   |
| `AWS_REGION`             | AWS region to use                            | us-east-1 |
| `AWS_MCP_SECURITY_MODE`  | Security mode ("strict" or "permissive")     | strict    |
| `AWS_MCP_SECURITY_CONFIG`| Path to custom security configuration file   | ""        |

**Important:** Securely manage the AWS credentials provided to the server, whether via mounted `~/.aws` files or environment variables. Ensure the credentials follow the principle of least privilege as detailed in the [Security Considerations](#security-considerations) section. When running via Docker, ensure these variables are passed correctly to the container environment (e.g., using `docker run -e VAR=value ...`).

## Security Considerations

Security is paramount when executing commands against your AWS environment. While AWS MCP Server provides functionality, **you are responsible** for…