CFM Tips - Cost Optimization MCP Server

A comprehensive Model Context Protocol (MCP) server for AWS cost analysis and optimization recommendations, designed to work seamlessly with Amazon Q CLI and other MCP-compatible clients.

✅ Features

Core AWS Services Integration

• Cost Explorer - Retrieve cost data and usage metrics

• Cost Optimization Hub - Get AWS cost optimization recommendations

• Compute Optimizer - Right-sizing recommendations for compute resources

• Trusted Advisor - Cost optimization checks and recommendations

• Performance Insights - RDS performance metrics and analysis

Cost Optimization Playbooks

• 🔧 EC2 Right Sizing - Identify underutilized EC2 instances

• 💾 EBS Optimization - Find unused and underutilized volumes

• 🗄️ RDS Optimization - Identify idle and underutilized databases

• ⚡ Lambda Optimization - Find overprovisioned and unused functions

• � *CloudTrail Optimization - Analyze and optimize CloudTrail configurations

• 📊 Comprehensive Analysis - Multi-service cost analysis

Advanced Features

• Real CloudWatch Metrics - Uses actual AWS metrics for analysis

• Multiple Output Formats - JSON and Markdown report generation

• Cost Calculations - Estimated savings and cost breakdowns

• Actionable Recommendations - Priority-based optimization suggestions

📁 Project Structure

🔐 Security and Permissions - Least Privileges

The MCP tools require specific AWS permissions to function.

• Create a read-only IAM role - Restricts LLM agents from modifying AWS resources. This prevents unintended create, update, or delete actions.

• Enable CloudTrail - Tracks API activity across your AWS account for security monitoring.

• Follow least-privilege principles - Grant only essential read permissions (Describe*, List*, Get*) for required services.

The below creates an IAM policy with for list, read and describe actions only:

🛠️ Installation

Prerequisites

• Python 3.11 or higher

• AWS CLI configured with appropriate credentials

• Amazon Q CLI (for MCP integration) - https://docs.aws.amazon.com/amazonq/latest/qdeveloper-ug/command-line-installing.html

Setup Steps

1. Clone the Repository

   git clone https://github.com/aws-samples/sample-cfm-tips-mcp.git cd sample-cfm-tips-mcp

2. Install Dependencies

   pip install -r requirements.txt

3. Configure AWS Credentials

   aws configure # Or set environment variables: # export AWS_ACCESS_KEY_ID=your_access_key # export AWS_SECRET_ACCESS_KEY=your_secret_key # export AWS_DEFAULT_REGION=us-east-1

4. Apply IAM Permissions

   • Create an IAM policy with the permissions listed above

   • Attach the policy to your IAM user or role

5. Install the MCP Configurations

   python3 setup.py

6. Usage Option 1: Using the Q CLI Chat

   q chat Show me cost optimization recommendations

7. Usage Option 2: Integrate with Amazon Q Developer Plugin or Kiro

   • Open Amazon Q Developer Plugin on your IDE

   • Click on Chat -> 🛠️ Configure MCP Servers -> ➕ Add new MCP

   • Use the following configuration

   - Scope: Global - Name: cfm-tips - Transport: stdio - Command: python3 - Arguments: <replace-with-path-to-folder>/mcp_server_with_runbooks.py - Timeout: 60

🔧 Available Tools

Cost Analysis Tools

• get_cost_explorer_data - Retrieve AWS cost and usage data

• list_coh_enrollment - Check Cost Optimization Hub enrollment

• get_coh_recommendations - Get cost optimization recommendations

• get_coh_summaries - Get recommendation summaries

• get_compute_optimizer_recommendations - Get compute optimization recommendations

EC2 Optimization

• ec2_rightsizing - Analyze EC2 instances for right-sizing opportunities

• ec2_report - Generate detailed EC2 optimization reports

EBS Optimization

• ebs_optimization - Analyze EBS volumes for optimization

• ebs_unused - Identify unused EBS volumes

• ebs_report - Generate EBS optimization reports

RDS Optimization

• rds_optimization - Analyze RDS instances for optimization

• rds_idle - Identify idle RDS instances

• rds_report - Generate RDS optimization reports

Lambda Optimization

• lambda_optimization - Analyze Lambda functions for optimization

• lambda_unused - Identify unused Lambda functions

• lambda_report - Generate Lambda optimization reports

Comprehensive Analysis

• comprehensive_analysis - Multi-service cost analysis

Additional Tools

• get_trusted_advisor_checks - Get Trusted Advisor recommendations

• get_performance_insights_metrics - Get RDS Performance Insights data

📊 Example Usage

Basic Cost Analysis

Resource Optimization

Report Generation

Multi-Service Analysis

🔍 Troubleshooting

Common Issues

1. Cost Optimization Hub Not Working

   python3 diagnose_cost_optimization_hub_v2.py

2. No Metrics Found

   • Ensure resources have been running for at least 14 days

   • Verify CloudWatch metrics are enabled

   • Check that you're analyzing the correct region

3. Permission Errors

   • Verify IAM permissions are correctly applied

   • Check AWS credentials configuration

   • Ensure Cost Optimization Hub is enabled in AWS Console

4. Import Errors

   # Check Python path and dependencies python3 -c "import boto3, mcp; print('Dependencies OK')"

Getting Help

• Check the RUNBOOKS_GUIDE.md for detailed usage instructions

• Run the diagnostic script: python3 diagnose_cost_optimization_hub_v2.py

• Run integration tests: python3 test_runbooks.py

🧩 Add-on MCPs

Add-on AWS Pricing MCP Server MCP server for accessing real-time AWS pricing information and providing cost analysis capabilities https://github.com/awslabs/mcp/tree/main/src/aws-pricing-mcp-server

🎯 Key Benefits

• Immediate Cost Savings - Identify unused resources for deletion

• Right-Sizing Opportunities - Optimize overprovisioned resources

• Real Metrics Analysis - Uses actual CloudWatch data

• Actionable Reports - Clear recommendations with cost estimates

• Comprehensive Coverage - Analyze EC2, EBS, RDS, Lambda, and more

• Easy Integration - Works seamlessly with Amazon Q CLI

📈 Expected Results

The CFM Tips cost optimization server can help you:

• Identify cost savings on average

• Find unused resources costing hundreds of dollars monthly

• Right-size overprovisioned instances for optimal performance/cost ratio

• Optimize storage costs through volume type recommendations

• Eliminate idle resources that provide no business value

🤝 Contributing

We welcome contributions! Please see our contributing guidelines:

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Add tests for new functionality

5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.