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AWS Support MCP Server

AWS Support MCP Server

A Model Context Protocol (MCP) server implementation for interacting with the AWS Support API. This server enables AI assistants to create and manage AWS support cases programmatically.

Features

  • Create and manage AWS support cases
  • Retrieve case information and full communication history
  • Add communications to existing cases (with attachment support)
  • Resolve support cases
  • Upload and download attachments with double-encoding protection
  • Discover valid service codes, category codes, severity levels, and languages before creating a case
  • Browse available case creation options per service

Available Tools

ToolDescription
create_support_caseCreate a new support case
describe_support_casesList/search existing cases
describe_communicationsGet full communication history for a case
add_communication_to_caseReply to a case (with optional attachments)
resolve_support_caseClose a case
describe_servicesList AWS services and category codes
describe_severity_levelsList severity levels
describe_create_case_optionsGet valid categories/severities for a service
describe_supported_languagesList supported languages
add_attachments_to_setUpload files for attachment to cases
describe_attachmentDownload an attachment by ID

Requirements

  • Python 3.7+
  • AWS credentials with Support API access
  • Business, Enterprise On-Ramp, or Enterprise Support plan

Prerequisites

  1. Install uv from Astral or the GitHub README
  2. Install Python using uv python install 3.10

Installation

KiroCursorVS Code
Add to KiroInstall MCP ServerInstall on VS Code

Configure the MCP server in your MCP client configuration (e.g., for Kiro, edit ~/.kiro/settings/mcp.json):


{
"mcpServers": {
"awslabs_support_mcp_server": {
"command": "uvx",
"args": [
"-m", "awslabs.aws-support-mcp-server@latest",
"--debug",
"--log-file",
"./logs/mcp_support_server.log"
],
"env": {
"AWS_PROFILE": "your-aws-profile"
}
}
}
}

Alternatively:



uv pip install -e .
uv run awslabs/aws_support_mcp_server/server.py
{
"mcpServers": {
"awslabs_support_mcp_server": {
"command": "path-to-python",
"args": [
"-m",
"awslabs.aws_support_mcp_server.server",
"--debug",
"--log-file",
"./logs/mcp_support_server.log"
],
"env": {
"AWS_PROFILE": "manual_enterprise"
}
}
}
}

Windows Installation

For Windows users, the MCP server configuration format is slightly different:

{
"mcpServers": {
"awslabs.aws-support-mcp-server": {
"disabled": false,
"timeout": 60,
"type": "stdio",
"command": "uv",
"args": [
"tool",
"run",
"--from",
"awslabs.aws-support-mcp-server@latest",
"awslabs.aws-support-mcp-server.exe"
],
"env": {
"FASTMCP_LOG_LEVEL": "ERROR",
"AWS_PROFILE": "your-aws-profile",
"AWS_REGION": "us-east-1"
}
}
}
}

Usage

Start the server:

python -m awslabs.aws_support_mcp_server.server [options]

Options:

  • --port PORT: Port to run the server on (default: 8888)
  • --debug: Enable debug logging
  • --log-file: Where to save the log file

Configuration

The server can be configured using environment variables:

  • AWS_REGION: AWS region (default: us-east-1)
  • AWS_PROFILE: AWS credentials profile name

Documentation

For detailed documentation on available tools and resources, see the API Documentation.

License

Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License").