A project that exposes AutoHotkey functionality through an MCP server, enabling model interfaces to control Windows automation tasks.

This project uses the MCP protocol and AI technology to build automated network security tools, covering multiple fields such as red - team attack simulation, SOC analysis, malware development, and threat hunting, to achieve the intelligence and automation of security tasks.

This project is an automation platform integrating AI, Ansible, and OpenShift. It enables interaction with Claude Desktop through the MCP server and supports automated task execution and management.

The combination of Gemini CLI and the MCP server built with Google Apps Script extends the automation capabilities of Google Workspace through a low - code platform, providing support for 41 tools covering services such as Gmail, Drive, Calendar, etc., and enabling multi - step execution of complex tasks.

The Ultimate MCP Server is an AI agent operating system based on the Model Context Protocol (MCP), providing dozens of powerful tool capabilities, including intelligent task delegation, document processing, browser automation, Excel operations, etc. It achieves cognitive enhancement and complex task orchestration of AI agents through standardized MCP tools.

The OWL x WhatsApp MCP Server project is an application that integrates WhatsApp messaging functionality with a multi - agent collaboration framework. It enables AI agents to access, search, and send messages to WhatsApp data through the Streamlit interface and supports real - time web searches.

A multi - agent browser automation framework based on AgentKit, which realizes intelligent web page navigation and task execution through division of labor and collaboration, including four core modules: task planning, navigation control, browser operation and result verification.

This project is a Model Context Protocol (MCP) server implemented for the Wrike project management platform, allowing interaction with the Wrike API through an MCP client (such as Anthropic's Claude desktop app), supporting queries and operations on data such as tasks, projects, spaces, and comments.

The AWX MCP Server is an industry-standard MCP server that connects the AWX/Ansible automation platform to AI tools, enabling AI assistants to manage job templates, start and monitor tasks, and manage inventories and projects using natural language, automating infrastructure workflows.

Mission Control MCP is a task automation and verification system designed specifically for Claude Code, providing autonomous task execution, result verification, and iterative optimization functions. It supports multiple verification strategies, has no external dependencies, and focuses on privacy and security.

A server that allows AI assistants to control Apple Shortcuts through the MCP protocol to trigger automation tasks

Codify MCP is an MCP server based on Apify Agent that can convert browser automation tasks into tools that AI assistants can call, supporting direct passing of tool definitions through JSON parameters without the need for configuration files.

An MCP server project for office automation, with functions including schedule management, weather query, email reminder, and task tracking.

The Narad MCP server integrates GitHub, email, and WhatsApp agents, enabling seamless communication and task automation through HTTP requests. It supports real-time and offline operations, providing a secure and efficient AI-driven workflow backend solution for managing multiple services.

Overview: The MCP Server aims to achieve full automation of AI agents. By providing a standardized protocol as an intermediate layer, it informs AI agents about currently available services, APIs, and data sources, enabling them to decide whether to call specific functions to perform tasks such as code modification, repository search on GitHub, problem search and creation, etc.

The project includes both MCP and REST APIs. The MCP interface serves clients such as Claude, and the REST interface is used for reports and automation tasks. Current functions include mailbox search and OCR processing. The next step is to implement PDF attachment processing and structured output.

Overview: MCP (Model Context Protocol) is a framework for AI automation through a standardized protocol, which includes key components such as hosts, clients, servers, local data sources, and remote services. The core lies in the server, which provides context, tools, and prompts for clients. MCP enables AI agents to automate tasks, such as code generation, debugging, and interaction with external services like GitHub repositories.

Overview: The README.md file provides an overview of the Model Context Protocol (MCP) Server, detailing its components and functions. It explains how MCP enables AI automation through a standardized protocol and connects hosts, clients, servers, local data sources, and remote services. The document also describes the evolution from basic AI chats to advanced AI agents capable of performing automated tasks.