alexei-led/aws-mcp-server

Overview

A lightweight Python service that lets AI assistants run AWS CLI commands inside a safe containerized environment via the Model Context Protocol (MCP). It connects MCP-aware tools like Claude and Cursor to AWS CLI for cloud infrastructure management.

Best for

Best for
Developers who want to control AWS infrastructure from AI assistants like Claude or Cursor

Use cases

• Manage AWS resources from an AI chat interface
• Automate routine cloud operations with natural language prompts
• Inspect and debug AWS infrastructure without leaving the editor

How to use

Tools exposed

• aws_cli_help
• aws_cli_pipeline
• AWS_PROFILE
• AWS_REGION
• AWS_CONFIG_FILE
• AWS_SHARED_CREDENTIALS_FILE
• AWS_MCP_TIMEOUT
• AWS_MCP_MAX_OUTPUT
• AWS_MCP_TRANSPORT
• AWS_MCP_SANDBOX
• AWS_MCP_SANDBOX_CREDENTIALS

Tested with

Claude Desktop, Claude Code

Example client config

{\n  "mcpServers": {\n    "aws": {\n      "command": "uvx",\n      "args": ["aws-mcp"]\n    }\n  }\n}

Notes

A lightweight Python service that lets AI assistants run AWS CLI commands inside a safe containerized environment via the Model Context Protocol (MCP). It connects MCP-aware tools like Claude and Cursor to AWS CLI for cloud infrastructure management.

182 stars on GitHub. Last updated 2026-02-27. Licensed MIT.

Use cases

• Manage AWS resources from an AI chat interface
• Automate routine cloud operations with natural language prompts
• Inspect and debug AWS infrastructure without leaving the editor

Pros

• Runs AWS CLI commands in an isolated container for safety
• Works with multiple MCP-compatible AI assistants
• Lightweight and easy to set up

Cons

• Requires MCP-aware tools, limiting direct use
• Containerized execution may add latency for simple commands
• Depends on AWS CLI configuration and credentials

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.