AWS MCP is a service based on the Model Context Protocol that allows querying and managing AWS resources through natural language, similar to an alternative to Amazon Q.

This project is a server based on the Model Context Protocol (MCP), specifically designed to interact with the Amazon Redshift database. It securely connects through the AWS Data API, provides functions such as database structure query, data retrieval, and performance analysis, and supports integration with AI tools such as Claude and Cursor.

AWS MCP is an AI tool for managing AWS resources through natural language, replacing Amazon Q and providing higher flexibility and security.

The MCP server for Amazon VPC Lattice provides tools and documentation support for accessing and managing AWS VPC Lattice resources, including functions such as resource listing, prompt templates, and CLI operations.

This project demonstrates a serverless MCP (Model Context Protocol) tool implementation based on AWS Lambda, including a Python server - side and a TypeScript client, supporting streaming HTTP communication. The server - side simplifies the MCP tool development process, has built - in session state management, and demonstrates integration with Amazon Bedrock.

This project demonstrates how to configure the Amazon Q CLI to integrate with the FastMCP MySQL Server and interact with AWS RDS MySQL databases via natural language commands.

The Amazon Nova Reel 1.1 MCP server for video generation supports asynchronous video generation, multiple transmission methods, and AWS integration.

An Amazon CloudWatch log management server based on the MCP protocol, providing a standardized interface for AI assistants to operate the CloudWatch logging service through the AWS SDK.

A guide to setting up MCP servers for AWS database services, supporting integration of multiple database types with Amazon Bedrock models