# AI agent

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.

Demonstrate connecting the Keboola Registry API to the MCP server through the CrewAI wrapper, enabling AI agents to call registered skills.

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

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.

The MCP Dust Server is a server-side implementation of the Model Context Protocol (MCP) for interacting with Dust AI agents. The project consists of an MCP server and a test client, supporting real-time streaming responses, the complete JSON-RPC 2.0 protocol, session management, and other functions. It can be integrated into development environments such as Windsurf IDE and Claude Desktop.

MCPML is a Python framework for building servers compliant with the Model Context Protocol (MCP), supporting CLI tools and OpenAI agent functions, and providing features such as dynamic loading and structured output.

AI agents interact intelligently through the MCP server and use the model context protocol tool to execute operations input by the user.

An MCP server implementation for AdGuard Home, supporting querying and managing DNS records, filtering rules, etc. through an AI agent.

This project demonstrates how to integrate OpenAI, Azure OpenAI, and GitHub models through the MCP protocol to build a terminal application for a TODO list agent. The project includes three major components: MCP host, client, and server, supports HTTP and SSE protocols, and provides tool invocation and database storage functions.

Filesystem MCP is a Node.js-based Model Context Protocol server that provides secure, relative-path file system access services for AI agents (such as Cline and Claude).

An AI agent application based on Spring Boot and Spring AI, helping users book accommodation in tourist cities, supporting multiple AI models and tool integration.

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

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.

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 AI agent server based on the Model Context Protocol, providing system prompt and tool management functions

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.

Solana MCP is a protocol server designed for AI agents, providing a standard interface for interacting with the Solana blockchain and DeFi protocols, supporting operations such as balance query, fund transfer, and trading.

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.

The Screeny MCP Server is a privacy-first screenshot service designed specifically for macOS, allowing AI agents to securely capture screenshots of pre-approved application windows and providing a visual context for development and debugging tasks.

A Gmail email management server based on the Model Context Protocol (MCP), supporting searching, reading, deleting, and sending emails through an AI agent. It needs to be used with a voice interaction client.

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 - 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.

The Graphiti MCP Server is a server based on multi - project knowledge graphs, supporting the rapid construction and management of temporary knowledge graphs for AI agents to query through the model context protocol. This project extends the official getzep/graphiti MCP Server, adds support for multiple servers and a single database, and provides a CLI tool with an optimized developer experience.

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

The MCP iCal Server is a macOS calendar management tool based on an AI agent. It enables natural language interaction through a single interface and supports functions such as event creation, schedule query, and intelligent update.

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.