UltraRAG

About

UltraRAG 2.0 addresses the high engineering costs associated with reproducing and iterating on complex RAG systems, which often involve adaptive knowledge organization, multi-turn reasoning, and dynamic retrieval. It provides a RAG framework built on the Model Context Protocol (MCP) architecture, enabling researchers to declare intricate logic such as sequential, loop, and conditional branching through simple YAML files. This design significantly lowers the technical barrier and learning curve for building and experimenting with sophisticated RAG pipelines, allowing researchers to focus on algorithmic innovation and experimental design rather than extensive engineering implementation.

Key Features

• Integrate the Model Context Protocol (MCP) for standardized context provision to LLMs and seamless component reuse.
• Rapidly reproduce and extend RAG modules via a standardized MCP architecture, encapsulating components as reusable Servers and function-level Tools.
• Construct complex RAG pipelines with low code using YAML for control structures (sequential, loop, conditional branching).
• 747 GitHub stars
• Unify evaluation and comparison with built-in workflows and metric management, supporting 17 mainstream scientific benchmarks.
• Natively support multi-structured pipeline workflow control, defining logic at the YAML level for decoupled execution.

Use Cases

• Build and deploy custom RAG systems for various question-answering, multi-hop, and fact-verification tasks.
• Rapidly prototype and experiment with new RAG algorithms and research ideas.
• Reproduce and benchmark existing RAG baseline methods efficiently.