# AI agent

MemCP is an extensible memory MCP server designed for AI programming agents. It is extended based on Zep AI's Graphiti project, supports building, maintaining, and querying temporal knowledge graphs, and provides entity extraction, persistent storage, and support for multiple transport protocols.

Project exploring MCP servers and AI agents

This project showcases multiple Model Context Protocol (MCP) servers integrated with Microsoft Azure, which enable large language models (LLMs) to securely access Azure tools and data sources, including AI agent services and various database services.

An AI-driven browser automation server based on the MCP protocol, supporting natural language control of web page operations and in-depth web research.

iFlytek Workflow MCP Server is an AI workflow scheduling system based on the MCP protocol, supporting multiple node types and advanced orchestration modes, enabling intelligent business process automation.

Create an intelligent agent based on OpenAI to automatically generate Twitter post content.

Koppla is a natural language-based Active Directory management tool that enables querying and operating on user, group, and computer objects through an AI agent.

An AI agent based on Pydantic and Chainlit, supporting web browsing and multi-command protocol interaction

An MCP server based on the CrewAI framework, providing AI agent and task management functions, supporting the creation of agents, tasks, and workflows, and running automatically.

This project is an interaction server for the Open eClass platform based on the MCP protocol, supporting the SSO authentication system of the University of Athens. It provides functions such as course management and session maintenance, enabling AI agents to securely interact with the eClass platform.

The LINE Bot MCP Server is a server that implements the Model Context Protocol (MCP), used to connect an AI agent to a LINE official account and supports sending text and flexibly laid-out messages.

MCP BatchIt is a batching server for MCP tool calls. By aggregating multiple MCP tool calls into one request, it significantly reduces the communication overhead and token consumption of AI agents.

PG-MCP is a model context protocol server designed for PostgreSQL databases. It provides APIs for AI agents to connect to, query, and understand databases, and supports multiple database connections, rich metadata extraction, and query analysis functions.

The Azure MCP Server is a server that implements the MCP protocol, providing seamless connection between AI agents and Azure services (such as Storage and Cosmos DB), and supporting the conversion of natural language commands into Azure operations.

This is an MCP server implementation project based on SearXNG, providing privacy - protected search capabilities for AI agents. The project is deployed through Docker containerization, supports two transport protocols, SSE and Stdio, and can be easily integrated into MCP - compatible clients.

Discourse MCP is a Model Context Protocol server that exposes Discourse forum functions as tools to AI agents. It supports operations such as searching, reading posts, and creating posts, provides read-only and writable modes, and supports remote tool discovery and dynamic registration.

Cyclops MCP is a tool that allows AI agents to securely manage and deploy Kubernetes applications through the Model Context Protocol, providing template validation and application creation/update functions

A Django application that implements a Firebase Model Context Protocol (MCP) server, enabling AI agents to interact with Firebase services through a standardized protocol. It provides 14 Firebase tools covering authentication, database, and storage functions, supporting quick testing and full integration.

PraisonAI is a production-ready multi-AI agent framework with self-reflection capabilities, designed to create AI agents to automate the solution of various problems from simple tasks to complex challenges. It simplifies the construction and management of multi-agent LLM systems by integrating PraisonAI agents, AG2, and CrewAI into a low-code solution, emphasizing simplicity, customization, and effective human-machine collaboration.

DomainKits MCP is a domain name intelligent agent framework designed for AI assistants. It integrates tools such as domain name search, analysis, monitoring, trend discovery, and batch processing, and can transform general - purpose AI assistants into professional domain name agents with industry - specific knowledge.

The Florentine.ai MCP Server allows AI agents to query MongoDB and MySQL databases through natural language, supporting functions such as multi - tenant data isolation, automatic schema exploration, and semantic vector search.

An AI - driven architecture analysis and intelligent coding agent system for GitHub repositories. By deeply analyzing the codebase structure, generating architecture blueprints, and using real - time MCP tools, it ensures that AI coding agents follow unified architecture specifications, improving code quality and consistency.

A stateful Bluetooth Low Energy (BLE) Model Context Protocol (MCP) server that provides development tools and AI agents with the ability to interact with real BLE hardware. It supports operations such as scanning, connecting, reading and writing, and subscribing to notifications, and can extend device protocol specifications and plugins.

An MCP server based on pykrx, providing Korean stock market data query functions for AI agents, supporting multi - dimensional analysis of stock prices, financial indicators, investor transactions, short - selling data, etc.

Pincer-MCP is a security-hardened MCP gateway that protects the API keys of AI agents through a proxy token architecture, ensuring that agents can only use proxy tokens and cannot access real keys. It supports various AI services and GPG signing tools.

PumpClaw is a project that provides revenue infrastructure for autonomous AI agents, allowing users to deploy ERC - 20 tokens on the Base chain at zero cost and create Uniswap V4 liquidity pools. Creators can get an 80% share of transaction fees.

Airweave is an open - source context retrieval layer for AI agents and RAG systems. It connects and synchronizes data from various applications, tools, and databases, and provides relevant, real - time, multi - source contextual information to AI agents through a unified search interface.

This is an AI intelligent agent project that integrates the Kali Linux Docker environment and the local Windows host, providing unrestricted security testing and control capabilities.

TEN Agent is a multi-functional AI agent framework that integrates real-time vision, voice recognition, and screen sharing detection capabilities, and supports rapid expansion and development.

An AI agent server based on the Model Context Protocol (MCP), providing system prompt management and tool expansion functions, supporting the creation, management, and version control of AI agents.