Open source MCP servers for AWS

Cost Analysis MCP Server

MCP server for analyzing AWS service costs and generating cost reports

Features

Analyze and visualize AWS costs

• Get detailed breakdown of your AWS costs by service, region and tier
• Understand how costs are distributed across various services

Query cost data with natural language

• Ask questions about your AWS costs in plain English, no complex query languages required
• Get instant answers fetched from pricing webpage and AWS Pricing API, for questions related to AWS services

Generate cost reports and insights

• Generate comprehensive cost reports based on your IaC implementation
• Get cost optimization recommendations

Prerequisites

1. Install uv from Astral or the GitHub README
2. Install Python using uv python install 3.10
3. Set up AWS credentials with access to AWS services
   • You need an AWS account with appropriate permissions
   • Configure AWS credentials with aws configure or environment variables
   • Ensure your IAM role/user has permissions to access AWS Pricing API

Installation

Here are some ways you can work with MCP across AWS, and we'll be adding support to more products including Amazon Q Developer CLI soon: (e.g. for Amazon Q Developer CLI MCP, ~/.aws/amazonq/mcp.json):

{
  "mcpServers": {
    "awslabs.cost-analysis-mcp-server": {
      "command": "uvx",
      "args": ["awslabs.cost-analysis-mcp-server@latest"],
      "env": {
        "FASTMCP_LOG_LEVEL": "ERROR",
        "AWS_PROFILE": "your-aws-profile"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

AWS Authentication

The MCP server uses the AWS profile specified in the AWS_PROFILE environment variable. If not provided, it defaults to the "default" profile in your AWS configuration file.

"env": {
  "AWS_PROFILE": "your-aws-profile"
}

Make sure the AWS profile has permissions to access the AWS Pricing API. The MCP server creates a boto3 session using the specified profile to authenticate with AWS services. Your AWS IAM credentials remain on your local machine and are strictly used for accessing AWS services.