MCP Project Orchestrator

# AWS MCP Implementation Summary ## Overview This document summarizes the AWS Model Context Protocol (MCP) capabilities that have been added to the MCP Project Orchestrator, based on the AWS MCP features discussed in the referenced Perplexity search. ## Implementation Date September 30, 2025 ## What Was Added ### 1. Core AWS MCP Module (`src/mcp_project_orchestrator/aws_mcp.py`) A comprehensive AWS integration module that provides: #### AWS Configuration (`AWSConfig` class) - Environment variable-based configuration - Support for multiple authentication methods: - Access key ID + Secret access key - AWS CLI profiles - IAM roles (for EC2/ECS/Lambda) - Temporary credentials (STS) - Configuration validation - Boto3 client configuration generation #### AWS MCP Integration (`AWSMCPIntegration` class) Provides programmatic access to AWS services: **S3 Operations:** - List buckets - List objects in buckets - Upload files to S3 **EC2 Operations:** - List instances - Get instance status **Lambda Operations:** - List functions - Invoke functions **CloudFormation Operations:** - List stacks **IAM Operations:** - List users - List roles **Best Practices:** - Service-specific best practices (S3, EC2, Lambda) - Security recommendations - Cost optimization guidelines - Performance optimization tips **Cost Estimation:** - S3 cost estimation - EC2 cost estimation - Lambda cost estimation - Service-specific breakdowns ### 2. MCP Tool Registration The `register_aws_mcp_tools()` function registers AWS capabilities as MCP tools: - `aws_list_s3_buckets` - List all S3 buckets - `aws_list_ec2_instances` - List EC2 instances - `aws_list_lambda_functions` - List Lambda functions - `aws_best_practices` - Get service-specific best practices - `aws_estimate_costs` - Estimate AWS costs based on usage ### 3. Environment Configuration (`.env.example`) Template for AWS environment variables: - `AWS_REGION` - AWS region - `AWS_ACCESS_KEY_ID` - Access key (optional) - `AWS_SECRET_ACCESS_KEY` - Secret key (optional) - `AWS_SESSION_TOKEN` - Session token for temporary credentials - `AWS_PROFILE` - AWS CLI profile name - `AWS_ENDPOINT_URL` - Custom endpoint (for LocalStack testing) - Feature flags for best practices, cost optimization, and security ### 4. Dependencies (`pyproject.toml`, `requirements.txt`) Added boto3 and botocore as dependencies: - Core dependencies include boto3 by default - Optional `[aws]` extra for explicit AWS support - Compatible with Python 3.9+ ### 5. Project Integration #### Updated `project_orchestration.py` - Imports AWS MCP module - Conditionally registers AWS tools when AWS_REGION is set - Graceful fallback if boto3 is not installed #### Updated `fastmcp.py` - Added dotenv support for loading environment variables - AWS configuration loaded automatically from .env ### 6. Configuration (`config/project_orchestration.json`) Added AWS-specific configuration: ```json { "enable": { "awsMcp": true }, "aws": { "enabled": true, "services": ["s3", "ec2", "lambda", "cloudformation", "iam"], "bestPractices": { "enabled": true, "enforcement": true }, "costOptimization": { "enabled": true, "alertThreshold": 100 }, "security": { "scanningEnabled": false, "enforceEncryption": true } } } ``` ### 7. Documentation #### `docs/AWS_MCP.md` (Comprehensive Guide) - Overview of AWS MCP capabilities - Environment variable configuration - Setup instructions (3 methods) - Usage examples for each MCP tool - Python API documentation - AWS best practices details - Cost estimation examples - Security considerations - Troubleshooting guide - Advanced usage (LocalStack, multi-region, cross-account) - Contributing guidelines #### `docs/AWS.md` (Updated) - Added AWS MCP integration section - Quick start guide - Links to detailed documentation #### `README.md` (Updated) - Added AWS MCP Integration feature section - Updated installation instructions - Added AWS-specific installation option ### 8. Testing (`tests/test_aws_mcp.py`) Comprehensive test suite: - Configuration validation tests - Boto3 configuration conversion tests - Best practices retrieval tests - Cost estimation tests - Mocked AWS service operations tests - S3, EC2, Lambda operation tests ### 9. Setup Script (`scripts/setup_aws_mcp.sh`) Automated setup script that: - Checks boto3 installation - Creates .env file from template - Validates AWS CLI configuration - Tests AWS MCP integration - Provides next steps and documentation links ### 10. Package Exports (`src/mcp_project_orchestrator/__init__.py`) - Exports AWS classes and functions - Graceful fallback if boto3 not installed - Clean API for consumers ## AWS MCP Capabilities ### Based on AWS Labs MCP Implementation The implementation aligns with AWS's official MCP servers approach: 1. **AWS Best Practices Enforcement** - Automatic suggestions for secure configurations - Well-Architected Framework principles - Service-specific recommendations 2. **Contextual Guidance** - Real-time AWS documentation access - Up-to-date service capabilities - Best practice patterns 3. **Cost Optimization** - Proactive cost estimation - Usage-based calculations - Service-specific breakdowns 4. **Security & Compliance** - IAM best practices - Encryption recommendations - Audit logging guidance ## Environment Variables ### Required - `AWS_REGION` - AWS region (e.g., us-east-1) ### Optional (Choose one authentication method) - Method A: Access Keys - `AWS_ACCESS_KEY_ID` - `AWS_SECRET_ACCESS_KEY` - Method B: AWS Profile - `AWS_PROFILE` - Method C: IAM Role (no variables needed, uses instance/container role) ### Optional Configuration - `AWS_SESSION_TOKEN` - For temporary credentials - `AWS_ENDPOINT_URL` - For LocalStack or custom endpoints - `AWS_ENFORCE_BEST_PRACTICES` - Enable/disable best practices - `AWS_COST_OPTIMIZATION` - Enable/disable cost optimization - `AWS_SECURITY_SCANNING` - Enable/disable security scanning ## Installation ### Basic Installation ```bash pip install -e . ``` ### With AWS Support ```bash pip install -e ".[aws]" ``` ### Quick Setup ```bash ./scripts/setup_aws_mcp.sh ``` ## Usage Examples ### List S3 Buckets ```python from mcp_project_orchestrator import AWSMCPIntegration, AWSConfig aws = AWSMCPIntegration(AWSConfig(region='us-east-1')) buckets = aws.list_s3_buckets() for bucket in buckets: print(bucket['Name']) ``` ### Get Best Practices ```python practices = aws.get_aws_best_practices('s3') print(practices['security']) # Security best practices print(practices['cost']) # Cost optimization tips print(practices['performance']) # Performance recommendations ``` ### Estimate Costs ```python costs = aws.estimate_costs('s3', { 'storage_gb': 100, 'requests': 10000, 'data_transfer_gb': 50 }) print(f"Estimated cost: ${costs['total_usd']} USD") ``` ## MCP Tools When the MCP server is running, AI assistants can use these tools: 1. **aws_list_s3_buckets** - List all S3 buckets 2. **aws_list_ec2_instances** - List EC2 instances in region 3. **aws_list_lambda_functions** - List Lambda functions 4. **aws_best_practices** - Get service-specific best practices 5. **aws_estimate_costs** - Estimate AWS costs ## Security Considerations 1. **Never commit credentials to version control** 2. **Use .env files** (added to .gitignore) 3. **Prefer IAM roles** over access keys 4. **Use temporary credentials** when possible 5. **Rotate credentials regularly** 6. **Apply least privilege** IAM policies ## Testing Run the test suite: ```bash pytest tests/test_aws_mcp.py -v ``` ## Files Created/Modified ### New Files - `src/mcp_project_orchestrator/aws_mcp.py` - Core AWS MCP module - `docs/AWS_MCP.md` - Comprehensive AWS MCP documentation - `tests/test_aws_mcp.py` - Test suite - `.env.example` - Environment variable template - `requirements.txt` - Python dependencies - `scripts/setup_aws_mcp.sh` - Setup automation script - `AWS_MCP_IMPLEMENTATION_SUMMARY.md` - This file ### Modified Files - `src/mcp_project_orchestrator/__init__.py` - Added AWS exports - `src/mcp_project_orchestrator/project_orchestration.py` - Integrated AWS tools - `src/mcp_project_orchestrator/fastmcp.py` - Added dotenv support - `config/project_orchestration.json` - Added AWS configuration - `docs/AWS.md` - Added AWS MCP section - `README.md` - Added AWS features and installation - `pyproject.toml` - Added boto3 dependencies ## Alignment with AWS MCP Standards This implementation follows the AWS MCP approach described in: - AWS Labs MCP servers (https://awslabs.github.io/mcp/) - Model Context Protocol specification - AWS Well-Architected Framework - AWS best practices documentation ## Future Enhancements Potential additions for future versions: 1. Additional AWS services (DynamoDB, RDS, SNS, SQS) 2. AWS CloudWatch metrics integration 3. AWS Cost Explorer API integration 4. AWS Config compliance checking 5. AWS Security Hub integration 6. Bedrock and SageMaker AI services 7. AWS CDK construct generation 8. Infrastructure as Code templates 9. Multi-account management 10. AWS Organizations support ## Contributing To add new AWS service integrations: 1. Add methods to `AWSMCPIntegration` class 2. Add corresponding MCP tools in `register_aws_mcp_tools()` 3. Add best practices to `get_aws_best_practices()` 4. Update documentation 5. Add tests ## References - [AWS MCP Documentation](https://awslabs.github.io/mcp/) - [Model Context Protocol](https://modelcontextprotocol.io/) - [AWS Well-Architected Framework](https://aws.amazon.com/architecture/well-architected/) - [Boto3 Documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html) - [Perplexity Search Reference](https://www.perplexity.ai/search/give-me-aws-environment-variab-lQbAxNL_TyumJdNLUhYrKQ#2) ## License This implementation is part of the MCP Project Orchestrator and is licensed under the MIT License. ## Support For issues, questions, or contributions: - See `docs/AWS_MCP.md` for detailed documentation - Run `./scripts/setup_aws_mcp.sh` for automated setup - Check `tests/test_aws_mcp.py` for usage examples