# AI agent

mcp - searxng is an MCP server example designed for AI agents, which implements the external information search function through the open - source meta - search engine SearXNG. The project demonstrates how to integrate SearXNG and Microsoft's markdownify tool to convert web page content into Markdown - formatted text and communicate with MCP clients via the SSE protocol.

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.

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.

SecureSshMcp is a secure SSH management and control protocol project that allows AI agents to perform server operations without exposing keys.

Project exploring MCP servers and AI agents

The Dumpling AI MCP Server is a model context protocol service integrating multiple functions, providing capabilities such as data scraping, content processing, knowledge management, AI agents, and code execution, and supporting a rich set of API interfaces and tools.

MCPlite is a Python MCP service framework similar to FastAPI, which allows developers to easily define and expose server-side capabilities (such as tools, functions, or resource access) for programmatic calls by AI agents in host applications.

An MCP server that connects to the Obsidian knowledge base. Through the REST API plugin, AI agents can perform complex knowledge discovery and analysis tasks, supporting functions such as advanced search, regular expression matching, and full - text retrieval.

An OpenAI agent server based on the MCP protocol, providing various professional agents (such as web search, file search, and computer operation) and a multi-agent coordinator, which can interact with clients (such as the Claude desktop application) through the MCP protocol.

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.

An example project that includes various AI agents and RAG technologies, covering Gemini applications, MCP services, Flutter applications, and Vertex AI integration, providing AI development examples from basic to advanced.

automcp is a tool that can easily convert existing AI agent frameworks (such as CrewAI, LangGraph, etc.) into MCP servers to achieve standardized interface access. It supports the adaptation and deployment of multiple frameworks and provides functions for quick startup and configuration.

MCP Kanban is a task management toolset designed for AI agents. It manages multi-session workflows through a kanban system, supports column capacity limits, an embedded database, and Web UI monitoring. It provides API interfaces for creating, moving, and deleting tasks, as well as preset prompt words to assist in project initiation and advancement.

AI agent robot project based on multi-MCP servers

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

A Minecraft model control protocol server based on Mineflayer, providing a standardized JSON - RPC interface for AI agents to control Minecraft robots.

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.

Agent X is an autonomous AI agent based on Google Gemini Flash and Twitter API, capable of intelligently generating and posting tweets.

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.

This project implements an adapter between Langchain and the Box MCP server, integrating AI capabilities through tools and agents, supporting dynamic tool loading, creating React-style agents, and providing a friendly console interaction interface.

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.

The Ultimate MCP Server is an AI agent operating system based on the Model Context Protocol (MCP), providing a rich toolset and intelligent task delegation function, supporting multi-LLM provider integration, optimizing cost and performance, and automating complex workflows.

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.