# AI agent

Grasp is an open-source and self-hostable humanized browser automation tool that supports the MCP and A2A protocols and can seamlessly integrate with various AI applications. Through Docker containerization deployment, it provides a browser operation experience controlled by natural language.

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.

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

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.

The TMF620 MCP Server is a middleware that connects AI agents with the remote TMF620 product catalog management API, providing functions for querying and creating catalogs, product offerings, and product specifications.

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.

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 Azure AI Agent Service MCP Server integrates the functions of Azure AI Foundry, supports connecting to existing Azure AI agents, and provides capabilities such as security authentication, session memory, and multi-tool invocation.

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

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 Agentic MCP Client is an independent AI agent runner that interacts with models such as Claude, BedRock, and OpenAI through MCP protocol tools, supporting autonomous cloud operation and secure system interaction.

An unofficial experimental MCP service for HexDocs, based on the search API, providing document search functionality for AI agents such as Claude or Cursor.

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.

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

The privateGPT MCP Server is a server implementation based on the Model Context Protocol (MCP), allowing users to interact with privateGPT through an MCP client and supporting functions such as chat, knowledge source management, and permission control.

This is a full-stack application based on Cloudflare Workers that combines a React front-end, REST API, and MCP server functionality, using Stytch for user authentication. The project demonstrates how to extend a traditional application into a solution that supports AI agents.

mcp - agent is a lightweight AI agent framework based on the Model Context Protocol (MCP), which supports building efficient agent applications through a simple and composable model. It integrates the lifecycle management of the MCP server and implements multiple workflow models, such as parallel processing, routing, evaluation optimization, etc., and is suitable for various AI application scenarios such as multi - agent collaboration and human - machine interaction.

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

AI code review and issue repair agent for analyzing codebases, detecting security vulnerabilities, reviewing code quality, and providing repair suggestions based on Sentry error logs.

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.

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.

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.

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.

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.

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 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.

Flex MCP Agent is a multi - functional agent project that integrates weather data acquisition, Confluence interaction, and email sending functions, standardizing the interaction between AI models and data sources using the Model Context Protocol (MCP).

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 Firebolt MCP Server is a service that implements the model context protocol, which can connect LLMs (large language models) with the Firebolt data warehouse, enabling AI assistants to directly query data, generate insights, and access documentation resources.

Intelligent product search system based on MCP service and OpenAI Agent SDK