Aws Sage MCP Server

A production-grade [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server for AWS. Connect AI assistants to your AWS infrastructure

Local serverstdioPython

What is the Aws Sage MCP server?

A production-grade Model Context Protocol (MCP) server for AWS. Connect AI assistants to your AWS infrastructure and manage it through natural conversation. That is what the aws sage mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

Getting it running

Installation goes through your MCP client rather than a global install: point it at git on PyPI and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.

The tools it exposes

The server publishes 4 tools. What each one is for:

  • Prerequisites — The Prerequisites tool exposed by this server
  • Cursor — The Cursor tool exposed by this server
  • Windsurf — The Windsurf tool exposed by this server
  • Setup — The Setup tool exposed by this server

What it needs from you

Configuration is passed through the environment: AWS_PROFILE, AWS_DEFAULT_REGION, AWS_SAGE_LOCALSTACK_HOST. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.

  • Python 3.11+ - AWS credentials configured (~/.aws/credentials or ~/.aws/config) - Any MCP-compatible client (see Compatible Clients above)

Things to watch

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

How it compares

Plenty of cloud and infrastructure servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Aws Sage's toolset — Prerequisites, Cursor, Windsurf and 1 more — is a fair guide to whether it matches your workflow. It is maintained by arunsanna; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Available tools

ToolWhat it does
PrerequisitesThe Prerequisites tool exposed by this server.
CursorThe Cursor tool exposed by this server.
WindsurfThe Windsurf tool exposed by this server.
SetupThe Setup tool exposed by this server.

How to install the Aws Sage MCP server

{
  "mcpServers": {
    "aws-sage": {
      "command": "uvx",
      "args": ["git"],
      "env": {
        "AWS_PROFILE": "your-value",
        "AWS_DEFAULT_REGION": "your-value",
        "AWS_SAGE_LOCALSTACK_HOST": "your-value"
      }
    }
  }
}

Add to claude_desktop_config.json, then restart Claude Desktop.

Configuration

  • Python 3.11+ - AWS credentials configured (~/.aws/credentials or ~/.aws/config) - Any MCP-compatible client (see Compatible Clients above)
VariableDescriptionRequired
AWS_PROFILEConfiguration value read at startup.Optional
AWS_DEFAULT_REGIONConfiguration value read at startup.Optional
AWS_SAGE_LOCALSTACK_HOSTEndpoint or connection string the server talks to.Optional

Example prompts to try

  • Use Aws Sage to Prerequisites.
  • Use Aws Sage to Cursor.
  • Use Aws Sage to Windsurf.

Frequently asked questions

It connects Aws Sage to MCP-compatible AI assistants such as Claude and Cursor, exposing 4 tools (Prerequisites, Cursor, Windsurf, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Aws Sage directly.