AWS CLI MCP Server

@ClockworkCubed

Basic information

About AWS CLI MCP Server

MCP server that acts as a thin wrapper around the local AWS CLI command

AWS CLI MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "aws-cli-mcp": {
      "command": "python",
      "args": [
        "aws_mcp.py"
      ]
    }
  }
}

AWS CLI MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is AWS CLI MCP Server?

AWS CLI MCP Server is a Model Context Protocol (MCP) server that acts as a thin wrapper around the local AWS CLI installation, providing AI assistants with secure, controlled access to AWS services through the familiar AWS CLI interface. It is designed for users who want AI systems to manage AWS resources while leveraging existing AWS CLI configurations and credentials.

How to use AWS CLI MCP Server?

Install Python 3.10+ and the AWS CLI, then clone the repository, run pip install -e . to install dependencies, and start the server with python aws_mcp.py. The server runs in stdio mode and exposes a single tool, execute_aws_command_tool, which accepts an args array (e.g., ["sts", "get-caller-identity"]) and returns the command’s stdout, stderr, and exit code. Connect any MCP-compatible client (e.g., Claude Desktop) to the server via stdio transport.

Key features of AWS CLI MCP Server

Thin wrapper that proxies commands directly to local AWS CLI
Security by respecting existing AWS CLI credentials and permissions
Compatibility with all AWS CLI commands and services
Uses existing AWS CLI profiles and configurations
Clean error handling and structured JSON output
No additional authentication beyond existing AWS CLI setup

Use cases of AWS CLI MCP Server

AI assistants managing AWS resources through natural language
Automating routine AWS CLI tasks (e.g., listing instances, checking status)
Enabling read-only AWS operations with guardrails from IAM policies
Deploying or modifying infrastructure via the AWS CLI in a controlled manner
Troubleshooting AWS services by executing CLI commands interactively

Frequently asked questions

What dependencies are required?

Python 3.10+ and a locally installed, configured AWS CLI with valid credentials (via `aws configure`, IAM roles, or environment variables).

What transport does the server use?

The server runs in stdio mode and communicates via the Model Context Protocol over standard input/output.

Does the server work with all AWS CLI commands?

Yes, it proxies any valid AWS CLI command and returns the output, so all services and commands supported by the local AWS CLI are accessible.

How are credentials and security handled?

The server uses the existing AWS CLI credentials and configuration—no additional authentication is needed. All AWS security mechanisms (IAM policies, MFA, etc.) remain in effect.

What is the name and format of the tool exposed?

The only tool is `execute_aws_command_tool`, which accepts a JSON array of arguments under the `args` key (e.g., `{"args": ["s3", "ls"]}`).

Comments

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