# 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 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.

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

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 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.

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.

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

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.

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.

This project is an MCP server tool designed to enable AI agents to search for content and information on external websites through the SearXNG service.

A high-performance PostgreSQL MCP server based on Bun and TypeScript, providing multi-database interaction capabilities for AI agents.

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

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.

This project creates an AI agent based on the n8n platform that can discover and use Model Context Protocol (MCP) server tools through the Nostr network. The agent searches for available tools by querying Data Vending Machines (DVM) in the network, sends requests, and obtains responses, thereby expanding the functionality of the LLM to use MCP tools that are not installed.

The Toshl MCP Server is a bridge that connects AI agents with the Toshl Financial API, providing read access to financial data such as accounts, classifications, tags, and budgets, and supporting data - based analysis and suggestions.

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.

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.

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.

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.

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.