This project provides a MySQL implementation of the Model Context Protocol (MCP) server, designed to facilitate interaction between AI models and MySQL databases through a standardized interface. It supports listing available database tables, retrieving table schemas, executing read-only SQL queries, and handling safe transactions with automatic rollback. This server is particularly useful for integrating AI models with MySQL databases in a structured and secure manner.

The Word Tools MCP Server implements the Model Context Protocol (MCP) to provide AI-powered Word document manipulation capabilities. It supports features like document creation, rich text editing, table formatting, and metadata management. Designed for integration with AI tools like Cursor and VSCode, it allows developers to manipulate Word documents programmatically using natural language commands.

This MCP server provides a seamless interface for interacting with Lexware Office (formerly known as Lexoffice) through the Model Context Protocol. It allows users to manage invoices, contacts, and other business documents, with features like retrieving invoice details, filtering contacts, and listing posting categories. The server supports integration with Claude Desktop and can be deployed using Docker or NPX.

The MCP Shell Server acts as a bridge, enabling AI agents to execute shell commands securely. It supports various shells, including bash, zsh, fish, powershell, and cmd, and provides detailed error handling and logging. The server is compatible with MCP Inspector and can be installed via npm or built from source for development.

This MCP server provides a foundational framework for managing and controlling Three.js source code. It offers essential functions to facilitate integration and control within Three.js projects, making it easier to handle complex visualizations and 3D rendering tasks. The server is built to support developers in streamlining their workflows with Three.js.

This MCP server integrates with the RSS3 API to provide seamless querying of decentralized chains, social media platforms, and the RSS3 network. It enables users to retrieve data on staking, nodes, and AI intels, making it a powerful tool for developers and researchers. The server supports integration with tools like Claude Desktop, Cursor, and ChatWise for enhanced functionality.

The Grasshopper MCP Bridge facilitates seamless integration between Grasshopper and Claude Desktop by implementing the Model Context Protocol (MCP). It enables high-level intent recognition, automatic creation of complex component patterns, and provides a component knowledge base for understanding parameters and connection rules. This tool enhances the workflow for designers and developers using Grasshopper with Claude Desktop.

The Shodan MCP Server, developed by ADEO Cybersecurity Services, provides cybersecurity professionals with streamlined access to Shodan's reconnaissance capabilities and VirusTotal's threat intelligence through a Model Context Protocol interface. It enables efficient asset discovery, vulnerability assessment, and security monitoring with 11 consolidated analysis prompts, offering tools for network intelligence, DNS operations, and malware analysis.

This MCP (model context protocol) server facilitates seamless integration between large language models (LLMs) and databases by providing access and contextual knowledge through JDBC. It is built using Java, Spring Boot, and LangChain4J, offering a robust solution for enhancing LLM capabilities with database interactions.

This MCP server facilitates integration between Google Classroom and Claude AI, allowing users to retrieve course details, assignments, and announcements directly through the AI assistant. It supports OAuth 2.0 authentication, automatic token refresh, and provides tools for listing courses, fetching course details, and accessing assignments. Designed for use with MCP-compatible assistants, it simplifies managing Google Classroom data via AI interactions.

This MCP server provides access to real-time and historical air quality data from monitoring stations across Taiwan. It integrates with the Model Context Protocol (MCP) to deliver tools like aqi-health-guidance, aqi-query, and aqi-query-recent. Users can configure the server using PHP and a JSON configuration file to fetch and display air quality information efficiently.

SuperGateway is a tool designed to bridge stdio-based MCP (Model Context Protocol) servers with Server-Sent Events (SSE). It enables remote access to MCP servers by converting their stdio output into SSE streams. Key features include support for multiple clients, JSON format recognition, CORS, health check endpoints, and configurable log levels. This tool is particularly useful for integrating MCP servers with web-based applications that rely on real-time data updates.

The China Weather MCP Server is a Model Context Protocol (MCP) server designed to fetch real-time weather information for Chinese cities. It integrates with the AMap Weather API, offering features like asynchronous request handling and an easy-to-use MCP interface. This server enables AI assistants to access up-to-date weather conditions across China.

The Favicon Conversion MCP Server is a tool designed to convert SVG images into various favicon formats, including ICO and PNG, for use in web applications. It supports base64 encoded output for easy integration and seamless compatibility with LLM-powered applications. The server provides features like SVG to ICO and PNG conversion, making it a versatile solution for generating favicons efficiently.

This MCP server provides clients with the ability to access and retrieve Wikipedia pages seamlessly. It is designed to integrate with MCP-compatible systems, offering a straightforward solution for fetching Wikipedia content programmatically. The server is built using Python and leverages the MCP protocol for efficient communication.

Terminal MCP Server is a Model Context Protocol (MCP) server designed to allow AI models and applications to execute system commands on local machines or remote hosts via SSH. It features local and remote command execution, session persistence, environment variable customization, and multiple connection methods including stdio and Server-Sent Events (SSE). This server is particularly useful for integrating AI tools with system-level operations.

This repository contains detailed research and code examples for implementing Model Context Protocol (MCP) servers, specifically tailored for integration with Cursor AI and Claude Desktop. It includes step-by-step guides, technical requirements, and sample implementations in JavaScript and TypeScript. The resources aim to help developers create custom tools that enhance Cursor AI's capabilities for specific use cases.