RAGFlow is an open-source platform for building and orchestrating AI agents with advanced retrieval-augmented generation (RAG) capabilities. It offers hybrid search, visual workflow design, and Model Context Protocol (MCP) integration, making it suitable for enterprise-scale AI solutions and agent development.
RAGFlow is a RAG, search & retrieval project. It focuses on enabling reliable, context-rich AI agent workflows with advanced retrieval and orchestration capabilities. It is built as an open-source project for enterprise AI developers and data engineers. The project is open source (Apache-2.0). It runs on the web and API, and it can be self-hosted.
RAGFlow first shipped in 2023. The project is developed in the open on GitHub with 82.7k stars and 1.2k commits in the last 90 days. Among its 6 catalogued features are RAG engine, agent orchestration, and hybrid search. It exposes integrations via an MCP server and a public API.
Summary written by a language model from the project’s public pages.
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