# AWS integration

A service based on the Model Context Protocol (MCP) that provides AI assistants with the ability to access and analyze AWS CloudWatch logs, supporting functions such as log search, summary generation, and error pattern recognition.

The AWS CodePipeline MCP Server is a model context protocol service integrated with Windsurf and Cascade, providing a standardized management interface for AWS CodePipeline.

This project implements a server based on the Model Context Protocol (MCP) for deploying web applications to AWS serverless infrastructure, supporting automatic deployment of front - end, back - end, and full - stack applications.

A knowledge base search MCP server project based on AWS Bedrock and Cloudflare Workers, supporting AI assistants to search for document content through the protocol.

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.

An S3 storage service based on the MCP protocol, providing efficient file streaming processing and security management functions.

This project provides a series of example modules using the AWS Model Context Protocol (MCP), covering multiple languages and technology stacks, including TypeScript, Python, Spring AI, etc., demonstrating the application of MCP in scenarios such as client-server communication, ECS deployment, and RAG integration.

A server for deploying and managing AWS Lambda functions through the MCP interface, providing functions for function deployment, list viewing, and guided deployment.