A .NET console application for monitoring MCP interactions in the Cursor AI editor, providing real-time log analysis, error debugging, and protocol interaction visualization functions.

The Electron MCP Server is a server based on the Model Context Protocol (MCP), providing comprehensive automation, debugging, and observability capabilities for Electron applications. It implements AI-driven automation through the integration of the Chrome DevTools protocol, supporting real-time UI interactions, visual debugging, deep inspection, and development observability, and can work without modifying the target application's code.

ScreenMonitorMCP is a revolutionary AI vision server project that provides real-time screen monitoring, visual analysis, and intelligent interaction capabilities for AI assistants such as Claude, enabling AI to 'see' and operate the user's screen.

The MCP Browser is a headless browser interface based on Playwright, supporting web UI interaction and WebSocket real-time communication. It is designed for AI agent and MCP protocol integration.

MCP is a standardized protocol for interaction between AI models and applications, supporting tool invocation, resource management, and real-time data transfer.

The ROS 2 MCP Server is a model context protocol server designed for the ROS 2 system, enabling AI agents such as GitHub Copilot to monitor, debug, and manage ROS 2 nodes, topics, services, and the TF2 framework, providing real-time interaction and system visualization tools.

The Hacker News MCP server is a tool that provides real-time interaction with Hacker News content, supporting functions such as getting popular stories, story details, comments, and search, suitable for AI assistant integration.

This project demonstrates a real-time multi-tool agent architecture based on LangGraph and the MCP protocol, achieving decoupled AI agents and remote tool execution, supporting asynchronous, modular, and scalable real-time interaction.

An MCP server implementation based on TypeScript and Express, used to connect AI agents with external APIs, providing movie database interaction functions, supporting real-time communication and modular expansion.

MCP-TEAMATE is an AI agent communication server based on SSE, providing an interaction environment similar to a corporate team for AI agents, supporting real-time communication, document management, and multi-agent collaboration.

This project is an MCP server that connects AI assistants to Atlassian Confluence, enabling real-time access to and interaction with Confluence content, and providing functions such as searching and retrieving pages.

An intelligent system that combines AI and Kubernetes management, providing real-time diagnosis, resource monitoring, and log analysis, and simplifying cluster management through natural language interaction.

A production-level task management system based on the MCP protocol and Kafka, supporting task management, real-time notifications, and event stream processing, providing an interaction interface for AI agents.