WantedAlchemist/aws-mcp-server

AWS MCP Server 🌐

Welcome to the AWS MCP Server repository! This project provides a robust solution for integrating the Model Context Protocol (MCP) with AWS API. It aims to streamline cloud infrastructure management for Generative AI (GenAI) applications.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Contributing
• License
• Contact
• Releases

Introduction

In today's fast-paced tech landscape, managing cloud infrastructure efficiently is crucial. The AWS MCP Server offers a seamless way to integrate with AWS services, enabling developers to focus on building AI-driven applications without worrying about the underlying infrastructure.

This project supports various use cases, including but not limited to:

• AI agent deployment
• Automation of cloud resources
• DevOps practices for enterprise applications

Features

• AI Agent Support: Easily deploy AI agents that can interact with AWS services.
• Automation: Automate routine tasks to save time and reduce human error.
• Cloud Integration: Seamlessly connect with various AWS APIs.
• Infrastructure Management: Simplify the management of cloud resources.
• Enterprise Ready: Built with enterprise needs in mind, ensuring scalability and reliability.

Installation

To get started with the AWS MCP Server, follow these steps:

1. Clone the repository:

   git clone https://github.com/WantedAlchemist/aws-mcp-server.git
   cd aws-mcp-server
   

2. Install dependencies:

   Use your preferred package manager to install the required libraries.

   npm install
   

3. Configuration:

   Configure your AWS credentials. You can do this by creating a config.json file in the root directory with the following structure:

   {
     "aws_access_key_id": "YOUR_ACCESS_KEY",
     "aws_secret_access_key": "YOUR_SECRET_KEY",
     "region": "YOUR_REGION"
   }
   

4. Run the server:

   Execute the following command to start the server:

   node server.js
   

Usage

After setting up the server, you can start using it for your applications. The server exposes several endpoints for interacting with AWS services.

Example API Call

To demonstrate the functionality, here’s a simple example of how to make an API call to deploy an AI agent:

curl -X POST http://localhost:3000/deploy-agent -H "Content-Type: application/json" -d '{
  "agent_name": "MyAI",
  "parameters": {
    "model": "GPT-3",
    "version": "latest"
  }
}'

This call will initiate the deployment of an AI agent named "MyAI" using the specified model.

Contributing

We welcome contributions to improve the AWS MCP Server. Here’s how you can help:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them with clear messages.
4. Push to your branch and submit a pull request.

Please ensure that your code adheres to the existing style and includes tests where applicable.

License

This project is licensed under the MIT License. See the file for more details.

Contact

For questions or suggestions, feel free to reach out:

• Email: contact@wantedalchemist.com
• Twitter: @WantedAlchemist

Releases

You can find the latest releases and download the necessary files from the Releases section. Make sure to download and execute the relevant files to stay up to date with the latest features and fixes.

Conclusion

The AWS MCP Server is designed to simplify the complexities of cloud infrastructure management for Generative AI applications. With its user-friendly API and robust features, it provides a solid foundation for developers looking to leverage AWS services effectively.

We hope you find this project useful. Happy coding!