This project shows how to create an MCP server and client for Azure Cosmos DB, including a front - end application (product catalog and AI assistant) and an MCP server component that connects to the database.

Gaia-X is an enterprise-level AI application platform based on a new generation of AI paradigms. It solves the core pain points of enterprise AI products through an innovative technical architecture and provides core functions such as multi-agent collaboration, natural language RPA, and MCP protocol support.

A curated list of high-quality remote MCP servers, focusing on official and well-maintained services to help developers discover reliable AI application services suitable for production environments.

Rube is an MCP server based on the Composio platform that connects AI chat tools to over 500 business and productivity applications, enabling automated task execution through natural language commands.

This is a curated list of resources for the Model Context Protocol (MCP) ecosystem, covering multiple categories such as official resources, development tools, MCP servers, web integrations, databases, blockchains, AI integrations, voice, mobile applications, development environments, security testing, productivity tools, and system tools.

Bilt MCP Server is a tool designed specifically for AI agents, providing 8 powerful tools through the Model Context Protocol, enabling AI to independently create, build, and deploy production-ready mobile applications, supporting full application development lifecycle management.

An MCP server integrated with the addTaskManager application, implementing the ADD (Assess - Decide - Do) productivity framework created by Dragos Roua, providing AI - assisted task management functions through strict domain restrictions.

A production-ready MCP console automation server that allows AI assistants to fully interact with console applications, monitor output, detect errors, and automate terminal workflows, supporting multiple platforms and console types.

The Squad MCP server is a protocol service that connects the Squad product discovery platform with large language model applications, providing a rich toolset for creating, querying, and updating product strategy artifacts directly from an AI assistant.

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.

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.