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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").