# AI Agent

The PostgreSQL MCP Server is an implementation based on the Model Context Protocol (MCP), which allows AI agents to interact with PostgreSQL databases through standardized interfaces.

An MCP system implementation based on C++, including host, client, and server components, supporting interaction with LLM through the command line and calling various tool services.

The MCP Gateway is an advanced AI infrastructure middleware solution that acts as a proxy gateway for model context protocol (MCP) servers, providing unified interfaces, sensitive information filtering, and lifecycle management functions.

Redis MCP Server is a natural language interface service designed for Redis, supporting AI agents to query and manage Redis data through natural language, integrating the MCP protocol, and providing multiple data structures and search functions.

A production-level MCP server for the Kubernetes cluster API, providing a secure and standardized cluster management interface for AI agents

Email MCP is a simple Model Context Protocol server that adds email capabilities to AI agents, supports POP3 and SMTP protocols, and provides functions for sending, receiving, and managing emails.

MCP - AWS is an AI - based application that manages AWS EC2 instances through OpenAI agents and the MCP server, supporting natural language commands to create and terminate instances.

A lightweight MCP server based on Python that interacts with local ComfyUI via WebSocket to enable programmatic image generation by AI agents.

An AI agent and task management server based on the CrewAI framework, providing functions such as agent creation, task assignment, and workflow execution.

BenBox is an AI agent system based on the SSE-based MCP protocol, including a mobile Angular application, supporting image recognition and cloud deployment.

The Superset MCP Integration project enables AI agents to interact with Apache Superset, connecting and controlling Superset instances programmatically.

An MCP server based on the crawl4ai library, providing web page crawling and intelligent content extraction functions, supporting AI agents to interact with web pages through natural language instructions.

The AnySite MCP Server is a multi - platform network data collection tool based on the model context protocol, supporting platforms such as LinkedIn, Instagram, Reddit, and Twitter. It provides real - time, structured network data access capabilities for AI agents.

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.

Skills MCP is a server that extends the Claude Skills format to any AI agent supporting the MCP protocol, enabling general AI agents to quickly become domain experts through modular skills.

DigitalFate is an enterprise-level LLM task orchestration framework that supports multi-level task processing, tool integration, and computer operations.

Filesys is a file system server based on the MCP protocol that allows LLM agents to conveniently read, write, and list local files via Python.

A browser automation service based on the MCP protocol, supporting natural language control of browser operations

This is a Python project based on the SSE implementation of the MCP protocol, including server and client components. It invokes LLM services through the OpenRouter.ai platform and provides book search functionality.

A universal file viewer MCP server that provides read access to any folder in the file system for MCP clients, facilitating AI agents to access multiple repositories or other files.

The MCP Toolkit is a modular server implementation for building high-precision vertical AI agents, providing support for 123 tools, significantly reducing the amount of code, and simplifying complex workflows.

Install MCP is a tool that simplifies the installation and management of MCP servers through an AI agent. It supports one - click installation, centralized configuration, and secure key management, and is compatible with multiple development environments.

GenPilot is a tool that simplifies the creation and management of single/multi - agent systems for generative AI. It supports the MCP protocol and provides terminal and web interfaces for rapid development and deployment.

The MCP Agent Server is a hub platform that connects AI clients with intelligent agents, supporting the creation of multi - specialized agents, combined agent workflows, and the integration of various AI tools and services.

The first open-source MCP server that enables full-featured AI control of a remote macOS system without the need to install additional software, providing complete desktop operation capabilities.

The project provides rankings and user reviews of MCP servers to help users distinguish between high - quality and poor - quality MCP AI agent services.

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

This project provides two implementations of the MCP server, connecting Claude Desktop with Azure search capabilities and supporting document and web content search through Azure AI agent service (recommended) or direct Azure AI Search integration.

The Graphiti MCP Server is a multi - project knowledge graph server extension based on the official getzep/graphiti. It supports multi - server single - database configuration, provides a developer - friendly CLI tool, and can build temporary knowledge graphs for each project for AI agents to query through the model context protocol.

The Ultimate MCP Server is a comprehensive native MCP system. As a complete AI agent operating system, it provides dozens of powerful functions through the Model Context Protocol (MCP), enabling advanced AI agents to access a rich ecosystem of tools, cognitive systems, and professional services.