# AI agent

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

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.

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 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 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.

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.

Engram is a hosted MCP service that provides reliable memory for AI agents, enabling AI to remember past conversations, facts, and decisions, making it more like a real team member.

SecureSshMcp is a secure SSH management and control protocol project that allows AI agents to perform server operations without exposing keys.

Project exploring MCP servers and AI agents

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

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.

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 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.

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.

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).

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 based on the CrewAI framework, providing AI agent and task management functions, supporting the creation of agents, tasks, and workflows, and running automatically.

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.

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

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.

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

Sequential Thinking MCP is an MCP server that supports AI agents in advanced metacognition and dynamic reflective problem-solving, guiding the step-by-step execution of complex tasks through virtual thought recording and planning.

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.

ipybox is a lightweight Python code execution sandbox based on IPython and Docker, supporting secure code execution in local or remote environments. It is suitable for data analysis and code execution scenarios of AI agents.

An MCP server for GitLab and Jira integration, providing functions for AI agents to interact with GitLab and Jira instances, including project management, merge request processing, file viewing, user activity tracking, and Jira ticket management.

Omni-LPR is a self-hosted server with multiple interfaces (REST and MCP) that provides automatic license plate recognition (ALPR) functions and can be used as an independent microservice or a toolbox for AI agents.