# AI agent

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.

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

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.

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.

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

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.

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.

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.

Graphiti MCP Pro is a memory storage MCP service and management platform enhanced based on the Graphiti framework, providing asynchronous parallel processing, task management tools, unified configuration management, broader AI model compatibility, and a comprehensive visual management system.

A browser automation service based on Puppeteer and Steel, providing web page interaction capabilities for LLMs

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 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.

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.

MCP speech synthesis server based on Edge-TTS

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

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.

MCP Server is an AI agent tool designed specifically for macOS that improves work efficiency through system-level control, is compatible with MCP models, and integrates AI functions.

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.

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.

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.

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.

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.

trackio-mcp is a Python package that provides MCP (Model Context Protocol) server support for the trackio experiment tracking tool, enabling AI agents to observe and interact with trackio experiments through the MCP protocol. It can automatically enable the MCP server functionality by a simple import without modifying existing code, and supports local and Hugging Face Spaces deployment.

BNBChain MCP is a server based on the Model Context Protocol (MCP), providing secure interaction between AI agents and applications with the Binance Smart Chain (BSC) ecosystem. It integrates functions such as wallet management, token transfer, PancakeSwap decentralized exchange operations, Meme token trading, and GoPlus security analysis. It is developed using TypeScript and supports seamless integration with Claude Desktop.

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.