A generative AI support plugin for Unreal Engine that integrates multiple cutting - edge LLM/GenAI model APIs, providing AI integration layer support in game development, including chat and structured output functions for models such as OpenAI, Claude, and Deepseek, and supporting the Model Control Protocol (MCP) to achieve advanced functions such as scene object control and blueprint generation.

The multi-cluster MCP server provides a gateway for generative AI systems to interact with multiple Kubernetes clusters, supporting resource operations, cluster management, and monitoring.

EasyChatDM is an educational project for creating simple MCP server tools, aiming to provide random decision - making tools for D&D games through generative AI.

A repository focused on exploring and applying generative AI (GenAI), aiming to help users learn and experiment with the application of GenAI in daily tasks, including writing, programming, image generation, etc., through practical cases and resource sharing.

GenPilot is a tool that simplifies the creation and management of single/multi - agent systems for generative AI. It supports the MCP protocol and provides terminal and web interfaces for rapid development and deployment.

The WildFly MCP project aims to enhance the monitoring and management of the WildFly server through generative AI capabilities, providing tools and server integration and supporting natural language interaction.

This project designs and implements an architecture that connects the data space with generative AI. Through the Model Context Protocol (MCP) server as a secure middle layer, the language model can indirectly access the DuckDB database. It has the characteristics of modularity, extensibility, and log tracking, laying the foundation for future upgrades to the RAG architecture.

AI Toybox is a generative AI experimental platform focused on rapid prototyping and testing of MCP tools and agent workflows, providing a chat application and modular MCP service templates.

This is a generative AI course project for beginners, providing a complete learning path from environment setup to practical application. The project includes 6 concept courses and 6 programming courses, using the Azure OpenAI service for practical operations. Learners can quickly start through GitHub Codespaces or choose to install the Python environment locally. The project emphasizes the secure management of API keys and provides detailed setup guides. In addition, learners are encouraged to participate in open-source contributions, and an AI community communication platform is provided.

The WildFly MCP project aims to provide WildFly users with tools to monitor and manage servers using generative AI capabilities, including components such as MCP servers, chatbots, container images, and protocol gateways.

PydanticAI is a Python agent framework developed by the Pydantic team, aiming to simplify the development of production-grade applications based on generative AI. It supports multiple AI models, integrates Pydantic validation and structured output, provides a dependency injection system, streaming responses, and graph support, and seamlessly integrates with Pydantic Logfire. It is suitable for building AI applications that require type safety and efficiency.