# Intelligent Agent

This project uses the Quarkus framework and the Model Context Protocol (MCP) to implement an intelligent agent application based on multiple MCP servers. It combines LangChain4j to provide functions such as AI dialogue, restaurant recommendation, and Slack notification, and supports deployment in development and production environments.

ATLAS is an intelligent task and knowledge management system built on TypeScript and Neo4j, designed for LLM agents, providing a three - layer management architecture for projects, tasks, and knowledge.

OmniMind is an open - source Python library designed to simplify Model Context Protocol (MCP) integration and support the development of AI agents, workflows, and automation. It offers plug - and - play functionality, has built - in multiple tools, and provides intelligent responses based on Google Gemini, making it suitable for developers and beginners to quickly build AI applications.

The MCP Development Agent is an intelligent development assistant based on the Model Context Protocol (MCP), providing memory management, document search, Git/GitHub integration, and code analysis functions. It supports CLI and SSE server modes and uses local AI models to achieve intelligent-assisted development.

Solon-AI is a Java AI application development framework for all scenarios, supporting multiple AI capabilities and can be embedded in various frameworks for use.

The MCP Agent Tool Adapter is a project that implements modular tool invocation through the MCP protocol and supports dynamic inference tools of two agents, Google ADK and LangGraph.

A browser automation proxy tool based on the MCP protocol

The TypeScript version of MCP Agent is a TypeScript-based intelligent context-aware agent framework that provides features such as a modular architecture, advanced workflow management, a powerful logging system, and a flexible executor. It is a TypeScript port of the original MCP Agent.

Speelka Agent is a general LLM agent based on the Model Context Protocol (MCP), capable of invoking tools from other MCP servers to achieve complex task decomposition, multi - model collaboration, and tool orchestration.

This project uses the MCP protocol and AI technology to build automated network security tools, covering multiple fields such as red - team attack simulation, SOC analysis, malware development, and threat hunting, to achieve the intelligence and automation of security tasks.

An intelligent agent system running locally, combining inference models and tool - calling models

Agentic is an intelligent business service system based on the agent architecture. It coordinates the RAG service and monitoring service through the central application proxy to provide comprehensive solutions.

Omni_Engineer is an integrated software development efficiency system that achieves multi - functional collaboration through the FastAPI microservice architecture and the illegal - Agents platform, covering core functions such as code development, database management, version control, and team collaboration.

MCP - Codex is a tool orchestration service based on the Model Context Protocol (MCP). It realizes the dynamic discovery and invocation of tools for AI assistants through the intelligent agent 'The Librarian', solving the problem that traditional MCP requires restarting to add new tools. Although the project has stopped development, its architectural design still has reference value in the field of AI tool orchestration.

This project implements an MCP server and client for building intelligent agent applications based on Retrieval Augmented Generation (RAG). The server provides tools such as entity extraction, query optimization, and relevance checking, and the client demonstrates how to connect to the server and use these tools to enhance the performance of the RAG system.