alexei-led/aws-mcp-server
by Various
A lightweight service that enables AI assistants to execute AWS CLI commands (in safe containerized environment) through the Model Context Protocol (MCP). Bridges Claude, Cursor, a
MCP
alexei-led/aws-mcp-server
Added 1 June 2026
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_helpaws_cli_pipeline
Tested with
Claude Code, Claude Desktop
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.
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
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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