# 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.

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.

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.

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

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

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.

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

AnalyticDB for MySQL MCP Server is a universal interface service that connects AI agents and AnalyticDB for MySQL databases, supporting metadata retrieval and SQL operation execution.

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.

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

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.

This is an MCP server project built for the Norwegian power supplier Tibber, allowing AI agents to access the Tibber API through the Model Context Protocol to query energy prices and electricity consumption data. The project provides a local running solution and supports connection through clients such as Claude Desktop.

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

This project demonstrates how to integrate an AI agent powered by Azure OpenAI with the Microsoft Fabric data warehouse through the Model Context Protocol (MCP), using GraphQL as a common data connection layer to achieve bidirectional access to enterprise data.

An MCP server that supports Claude for API testing, providing general API testing and OpenAI - specific tools

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.

A web - based dialogue agent based on multiple large language models (such as Google Gemini, Anthropic Claude, etc.), which implements multi - step tool execution through the Vercel AI SDK and can interact with external services (such as WhatsApp, GitHub, etc.).

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.

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).

PG-MCP is a model context protocol server designed for PostgreSQL databases, providing APIs for AI agents to discover, connect, query, and understand databases. It supports multi - database connection, rich catalog information, and query explanation functions.

The ThingsBoard MCP Server is a service that provides a natural language interface for LLMs and AI agents, allowing interaction with the ThingsBoard IoT platform through natural language commands to achieve functions such as device management, data query, and analysis.

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.