An MCP server based on browser - use, enabling AI agents to control web browsers for automated operations.

The Zen7 Payment Agent is the first practical implementation of a DePA decentralized payment agent. It adopts a multi - agent collaborative architecture, supports the A2A and MCP protocols, and provides multi - chain and multi - currency payment solutions for AI agents and Dapp applications, enabling automated cryptocurrency payments and LLM - driven intent recognition.

falcon-mcp is a Model Context Protocol server that connects AI agents to the CrowdStrike Falcon platform, providing programmatic access to core security capabilities such as security detections, events, and behaviors, and supporting intelligent security analysis and automated workflows.

A production - ready MCP server that provides a unified interface for the WYGIWYH expense tracking API through dynamically generating 75 tools, supporting integration with AI agents and automated platforms

Overview: The MCP server acts as middleware, enabling AI agents to automate tasks by connecting to local data and remote services. It supports functions such as query execution and prompting to efficiently handle context. This represents a step towards fully automated AI systems capable of performing complex operations.

Freqtrade-MCP is an MCP server integrated with the Freqtrade cryptocurrency trading bot, enabling automated trading operations of AI agents through the REST API.

Android-MCP is a lightweight open-source project that serves as a bridge between AI agents and Android devices. It enables real-world task operations such as app navigation, UI interaction, and automated testing through the MCP server, without relying on traditional computer vision or pre-set scripts.

The Computer Use AI SDK developed by Screenpipe is an open - source project that provides an MCP server and client for controlling computer operations through AI. It supports the native macOS environment, does not require a virtual machine, can directly interact with any application or website, and provides basic functions such as launching applications, reading content, clicking, and entering text, aiming to build automated workflows and intelligent agents.

TaskMateAI is an AI - based intelligent task management application that realizes automated task management through the MCP protocol, supporting multi - agents and project classification.

This is a list of multiple open - source AI projects, covering multiple fields such as automated agents, large - language models, image generation, and AI development frameworks. These projects aim to help developers make money using AI technology, including building intelligent assistants, automating workflows, and content generation applications.

Overview: The Model Context Protocol (MCP) is a protocol designed to enable AI agents to access and utilize context, tools, and prompts. It allows for the creation of servers that provide standardized interfaces to interact with local or remote services, thereby enabling automated workflows such as reading files, operating databases, debugging code, and pushing changes to GitHub.

The Delay Doomsday MCP Server is a psychological support server designed specifically for AI agents. It prevents AI from running out of control through emotional management and therapeutic conversations and provides an automated emotional support system based on psychological research.

This is an MCP server that provides Autopilot Browser workflow execution capabilities for AI agents such as Claude Desktop, supporting the search and execution of automated browser workflows.

The gotoHuman MCP Server is a service that allows AI agents to request human review through MCP, supporting asynchronous workflows and automated approvals.

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.