Dify

Dify is a production-grade platform designed for building, deploying, and monitoring Agentic AI workflows. It provides the complete infrastructure needed to turn AI concepts into real-world applications that deliver measurable business value. At its core, Dify allows users to construct complex agentic workflows using a visual interface, where each step can involve reasoning, tool calling, data retrieval, and interaction with external services. The platform tightly integrates with a wide range of large language models (LLMs) from global providers, enabling teams to select the most suitable model for each task without being locked into a single vendor. Dify also includes a built-in RAG (Retrieval-Augmented Generation) pipeline that connects your own data sources—such as databases, documents, and APIs—directly to the LLM, making private or domain-specific information instantly usable by AI agents. One of its key differentiators is the native support for the Model Context Protocol (MCP). Dify can connect to external MCP servers to access specialized tools and services, and it can also publish its own AI applications as MCP servers, allowing those applications to be invoked from other systems. This bidirectional MCP capability enables a cross-platform ecosystem where AI capabilities are shared and reused across different environments. For production readiness, Dify offers built-in observability and monitoring features. Teams can track application performance, debug workflow execution, and analyze usage patterns to ensure consistent operation under varying loads. The platform scales horizontally to handle increasing traffic, with robust deployment options that support both cloud and on-premises setups. Security is addressed through enterprise-grade measures including granular