A terminal-based MCP protocol scheduled task management tool that provides a visual interface to view and monitor crontab tasks

DINO-X MCP is a project that enables large language models to perform fine-grained object detection and image understanding through DINO-X and Grounding DINO 1.6 API. It can achieve precise object positioning, counting, attribute analysis, and scene understanding, and supports natural language-driven visual tasks and workflow integration.

mcp-micromanage is a tool for controlling and tracking the workflow of AI programming assistants. It ensures that development tasks are executed as planned through mandatory frequent feedback and a visualization dashboard.

The Screeny MCP Server is a privacy-first screenshot service designed specifically for macOS, allowing AI agents to securely capture screenshots of pre-approved application windows and providing a visual context for development and debugging tasks.

A lightweight MCP server that provides auditory and visual notification functions for Claude Desktop on macOS, including prompt sounds and desktop notifications when tasks start and end.

A Flutter - based HTN planning system that enables visual modeling and management of complex tasks through AI dialogue

This project implements a full-stack AI agent system inspired by the model context protocol, including a React front-end and a FastAPI back-end. The back-end serves as an AI coordinator, using Google Gemini to parse natural language instructions, safely call the file system, browser, or GitHub tools to perform tasks, and return the structured results to the front-end. The system focuses on software development scenarios, providing secure sandbox file operations, real-time web browsing, and repository inspection functions, and visualizing the tool call process.

A TypeScript-based persistent terminal MCP server that supports multi-session management, resume after disconnection, intelligent output compression, and Web visual management, specifically designed for AI assistants to execute long-time tasks

This project demonstrates an intelligent agent capable of performing complex mathematical operations, creating visual presentations, and sending email results via Google services. It integrates multiple MCP servers to collaborate and complete complex tasks.