# UltraRAG

> A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines

- **URL**: https://www.freshcrate.ai/projects/UltraRAG
- **Author**: OpenBMB
- **Category**: MCP Servers
- **Latest version**: `v0.3.0.2` (2026-04-09)
- **License**: Apache-2.0
- **Source**: https://github.com/OpenBMB/UltraRAG
- **Homepage**: https://ultrarag.github.io/
- **Language**: Python
- **GitHub**: 5,510 stars, 411 forks
- **Registry**: github
- **Tags**: `deepseek`, `demo`, `easy`, `embedding`, `flask`, `gpt`, `huggingface-transformers`, `llm`, `python`

## Description

A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines

## Recent releases

| Version | Date | Urgency | Changes |
| --- | --- | --- | --- |
| `v0.3.0.2` | 2026-04-09 | High | Release date: 2026.4.9  ## Highlights  This release delivers a major end-to-end memory upgrade for UltraRAG, introducing persistent user memory, project memory retrieval, and a dedicated memory-aware RAG demo. It also makes the demo experience significantly more stateful and personalized with SQLite-backed authentication, persistent chat sessions, nickname and model settings management, and knowledge base visibility controls supporting public, private, and shared access.  The frontend is s |
| `v0.3.0.1` | 2026-03-10 | Medium | Release date: 2026.3.10  ## Highlights  This release introduces expanded document parsing for `.doc `and `.wps` formats, alongside new web search capabilities for the demo environment. We have significantly enhanced the chat experience by adding `DOCX` and `markdown` export functionality, downloadable text actions, and a streamlined flow for session creation and interruption handling. The citation system has been further optimized with automatic renumbering and improved source sorting for be |
| `v0.3.0` | 2026-01-26 | Low | Release date: 2026.1.23  ## Highlights  Introducing UltraRAG 3.0: Reject "Black Box" Development. Make Every Line of Inference Logic Visible! UltraRAG 3.0 solves the "Last Mile" problem in RAG development, developed by THUNLP, NEUIR, OpenBMB & AI9Stars. This release represents a significant milestone with **129 pull requests** merged, bringing major enhancements to functionality, UI/UX, and system stability.  * WYSIWYG Pipeline Builder: From logic to prototype in seconds. Our dual-mode bui |
| `v0.2.1.3` | 2026-01-12 | Low | Release date: 2026.1.12  ## Highlights  This release focuses on improving system stability and core logic. We have addressed a path indexing bug in the generation server to ensure reliable image rendering. Additionally, the search-o1 pipeline has been completely reimplemented, resolving previous implementation flaws.  ## What's Changed  1. Fixed index reference for image paths in generation server. by @xhd0728  #146  2. Reimplemented the search-o1 pipeline by @mssssss123 @lifelsl   #158 |
| `v0.2.1.2` | 2025-11-25 | Low | Release date: 2025.11.25  ## Highlights  This release introduces a refreshed UltraRAG front-end UI, fixes several logical issues, and adds new ToolCall and PipelineCall capabilities for directly invoking UltraRAG tools or pipelines from your own code. The retriever server has been further optimized to support full deployment without repeated corpus/index initialization, significantly improving experimental efficiency. We also refine the GPU/CPU configuration logic for more stable and flexibl |
| `v0.2.1.1` | 2025-11-13 | Low | Release date:  2025.11.13  ## Highlights  This release improves the stability and flexibility of UltraRAG. Retriever and index are now fully decoupled, with added support for Milvus and Faiss. The VisRAG 2.0 pipeline is newly supported, and compatibility with chonkie 1.4.0+ has been updated. Several pipelines, including Search-o1 and WebNote, have been fixed. User experience is improved through progress-bar support during document parsing, a script for saving retrieval results, and zoom-in s |
| `v0.2.1` | 2025-10-22 | Low | **Release date:** 2025.10.22    ## Highlights  1. Comprehensive Multimodal Upgrade: Both the Retriever and Generation Servers now support multimodal inputs, enabling a complete end-to-end multimodal workflow from retrieval to generation. 2. Corpus Parsing and Chunking Redesign: The Corpus Server adds multi-format file parsing with deep MinerU integration, supporting token-level, sentence-level, and customizable chunking strategies to flexibly adapt to diverse corpus structures. 3. Unified |
| `v0.2.0` | 2025-10-21 | Low | **Release date:** 2025.08.28    ## Highlights  UltraRAG 2.0 introduces a complete redesign of the system architecture, fully adopting the MCP-based modular structure. This release significantly improves flexibility, extensibility, and developer experience, enabling researchers and engineers to rapidly build, customize, and reproduce complex RAG pipelines with minimal overhead.  The core of UltraRAG 2.0 is the new MCP Server–Client workflow, providing a clean separation between functional c |

## Citation

- HTML: https://www.freshcrate.ai/projects/UltraRAG
- Markdown: https://www.freshcrate.ai/projects/UltraRAG.md
- Dependencies JSON: https://www.freshcrate.ai/api/projects/UltraRAG/deps

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