About AWS Storage MCP Server
AWS Storage MCP Server connects Amazon Q CLI with AWS storage services for users who want to query and manage storage resources in natural language. It covers services including S3, EBS, EFS, FSx, and AWS Backup.
Key features
- 01Query storage resources in natural language
- 02Perform AWS storage operations
- 03Manage multiple services through one interface
- 04Support S3, EBS, EFS, and FSx
- 05Run operations with local AWS credentials
Use cases
- 01List Amazon S3 buckets
- 02Retrieve information about AWS storage resources
- 03Manage storage services using natural language
MCP support
The MCP server provides Amazon Q CLI with tools for querying and operating AWS storage resources. Operations run with locally configured AWS credentials and their permissions.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEAWS Storage MCP Server
A Model Context Protocol (MCP) server that enables natural language interactions with AWS storage services through Amazon Q CLI.
Disclaimer
This project is provided "as is" without warranty of any kind, express or implied. The authors and contributors are not responsible for any damages or liabilities that may arise from using this software.
- Not an Official AWS Product: This is a community project and is not officially supported by Amazon Web Services.
- Use at Your Own Risk: Review all operations before executing them, especially those that modify or delete resources.
- Cost Implications: Using AWS services may incur costs to your AWS account. You are responsible for monitoring and managing these costs.
- Security Considerations: This tool requires AWS credentials to function. Always follow security best practices when handling credentials.
- No Liability: The authors and contributors cannot be held liable for any data loss, unexpected charges, or other damages resulting from the use of this software.
What is MCP?
The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). MCP enables communication between LLMs like Amazon Q and locally running MCP servers that provide additional tools and capabilities.
Why Use MCP?
- Natural Language Interface: Interact with AWS services using plain English instead of complex CLI commands
- Simplified Workflows: Perform complex operations with simple queries like "list my S3 buckets"
- Contextual Understanding: MCP servers provide domain-specific knowledge to LLMs
- Extended Capabilities: Add new functionalities to your LLM without retraining the model
- Local Execution: Operations execute on your local machine with your credentials
What This Project Does
This AWS Storage MCP server connects Amazon Q to your AWS storage services, allowing you to:
- Query AWS storage resources using natural language
- Perform operations on AWS storage services without remembering complex commands
- Get information about your storage resources in a conversational manner
- Manage multiple storage services from a single interface
Architecture Diagram

Supported AWS Storage Services
- Amazon S3: Object storage for any type of data
- Amazon EBS: Block storage for EC2 instances
- Amazon EFS: Scalable file storage for EC2 instances
- Amazon FSx: Fully managed file storage built on Windows Server
- AWS Storage Gateway: Hybrid cloud storage that connects on-premises environments with cloud storage
- Amazon S3 Glacier: Low-cost archive storage
- AWS Snow Family: Physical devices for data migration and edge computing
- AWS Backup: Centralized backup service
- Amazon S3 Object Lambda: Process S3 data during retrieval
- Amazon S3 Glacier Deep Archive: Lowest-cost archive storage class
Prerequisites
- Docker and Docker Compose
- AWS CLI configured with valid credentials
- Amazon Q CLI installed
Quick Start
- For detailed installation instructions, please refer to the Installation Guide.
- For detailed usage examples, please refer to the Usage Guide.
- For practical examples and demonstrations, see the Examples Guide.
Troubleshooting
If you encounter issues:
-
Check Docker Container Status
docker ps | grep aws-storage -
View Container Logs
docker logs aws-storage-mcp-aws-storage-mcp-1 -
Test the API Directly
curl -s -X POST -H "Content-Type: application/json" -d '{"tool_name": "list_aws_profiles", "parameters": {}}' http://localhost:8080/invoke -
Verify AWS Credentials Make sure your AWS credentials are valid and have the necessary permissions.
-
Restart the Container
docker compose restart
Project Structure
aws-storage-mcp/
├── README.md # This documentation
├── requirements.txt # Python dependencies
├── mcp-manifest.json # MCP server manifest
├── docker-compose.yml # Docker configuration
├── docker-compose.override.yml # Volume mapping for AWS credentials
├── Dockerfile # Docker build instructions
├── setup.sh # Environment setup script
├── start-docker.sh # Server startup script
└── src/ # Source code
├── server.py # MCP server implementation
└── services/ # AWS service modules
├── __init__.py
├── base.py # Base service class
├── s3.py # S3 operations
├── ebs.py # EBS operations
├── efs.py # EFS operations
└── ... # Other service modules
Documentation
- Installation Guide - Detailed installation instructions
- Usage Guide - Examples and usage instructions
- Contributing Guide - How to contribute to this project
- Code of Conduct - Community guidelines
Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to submit pull requests, report issues, and suggest enhancements.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Security Notes
- This MCP server runs with your AWS credentials
- All operations are executed with your permissions
- Review the code before running in production environments
- Consider using IAM roles with least privilege principles
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.