The AWS MCP Servers are a set of dedicated servers based on the Model Context Protocol, offering various AWS-related functions, including document retrieval, knowledge base query, CDK best practices, cost analysis, image generation, etc., aiming to enhance the integration of AI applications with AWS services through a standardized protocol.

This project is a toolset for managing and configuring multiple Model Context Protocol (MCP) servers, mainly serving AI assistants such as Claude Desktop. It provides functions such as file system access, SQLite database queries, web automation, and GitHub integration, and includes installation scripts, configuration templates, and security practice guides.

The MCP Context Provider is a static MCP server that provides a persistent tool context for AI models, preventing context loss between chat sessions. It automatically loads and injects tool - specific rules, syntax preferences, and best practices to ensure consistency across sessions.

An intelligent MCP server that acts as a guardian of development knowledge, providing AI assistants with access to the latest documentation and best practices.

This project guides developers on how to integrate the MCP service with GitHub Copilot to extend the capabilities of the AI-assisted development workflow. Through less than an hour of learning, users will set up the GitHub MCP server, implement Copilot proxy mode integration, and complete the full process practice from issue research to code submission.

The official e18e MCP server provides modern, high - performance best - practice suggestions for AI agents, including checking package installation commands, analyzing source code imports, and providing migration guides.

An MCP server designed for AI simulated interview scenarios, providing interactive voice interview practice functions

The SFCC Development MCP Server is an MCP protocol service that provides comprehensive support for Salesforce B2C Commerce Cloud development, including document query, log analysis, best practice guides, and system object definition functions, and supports AI assistant integration.

This project is a practice project for the MIT Hack decentralized AI summit, demonstrating how to quickly set up a Claude MCP protocol service on Windows. It includes two examples: a weather application and an SQLite database, which respectively demonstrate government API data acquisition and bakery inventory management functions.

An MCP server that provides best practices for AI agent access development, security guidelines, and coding standards. It supports multiple programming languages and frameworks, includes over 284 standards, and features a plug-in architecture and fast memory storage.

Practices MCP Server is a protocol server designed specifically for AI assistants, which helps development teams achieve standardized development practice management, including Git branch management, version control, PR preparation, and tool integration.

This is a TypeScript/Node.js template project for building MCP servers, providing a standardized structure, best practices, and example implementations. It includes functions such as tool development, resource management, and error handling, and supports AI-assisted development.

A personal learning project that builds a small AI agent by integrating the X API with the MCP server to explore backend integration and AI workflows, with an emphasis on security and ethical practices.

This project is a tutorial for developing an MCP server that retrieves Pokémon information through the PokéAPI. It aims to cultivate the ability of problem decomposition and logical reconstruction through programming practice, including 6 steps from basic concepts to actual deployment.

This project is used to practice relevant technologies such as Langgraph, Langchain, and AI automation, and includes the implementation of an MCP server and client.