UltraRAG
A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
UltraRAG is an MCP server framework that enables developers to build Retrieval-Augmented Generation (RAG) pipelines through low-code YAML configuration. Created by OpenBMB, THUNLP, NEUIR, and AI9stars, it standardizes RAG components (retrievers, generators, evaluators) as modular MCP servers that can be orchestrated with complex control flows including loops, conditionals, and branches. The framework includes a visual RAG IDE with a pipeline builder, knowledge base management, and one-click conversion of logic flows into interactive web UIs, making it ideal for both research prototyping and industrial applications.
Key Features
Use Cases
- 01Building custom RAG systems for document question-answering with visual debugging
- 02Academic research on retrieval-augmented generation with standardized benchmarks
- 03Deploying Deep Research pipelines that perform multi-step retrieval and generate long-form reports
- 04Rapid prototyping of RAG applications without extensive UI development
- 05Comparing and evaluating different RAG approaches with unified metrics
- 06Creating modular, reusable RAG components that integrate across workflows
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UltraRAG — FAQ
What is UltraRAG MCP server?+
UltraRAG is a low-code MCP framework for building Retrieval-Augmented Generation pipelines. It standardizes RAG components as independent MCP servers that can be orchestrated through YAML configuration files, enabling developers to create complex retrieval and generation workflows with minimal code.
How do I install UltraRAG?+
Install UltraRAG by cloning the GitHub repository and using uv to manage dependencies. You can install core dependencies only with 'uv sync', or full functionality with 'uv sync --all-extras'. Docker deployment is also available for users who prefer containerized environments.
Which AI clients work with UltraRAG?+
UltraRAG is designed as an MCP server framework and includes its own web-based UI (UltraRAG UI) accessible at localhost:5050. It implements the Model Context Protocol standard and can integrate with MCP-compatible clients.
Do I need API keys to use UltraRAG?+
API key requirements depend on which models and services you configure. You'll need access to LLM providers for generation (such as OpenAI, or local models via vLLM) and may need keys for specific retrieval services. The framework supports both cloud and local deployment options.
Is UltraRAG free to use?+
Yes, UltraRAG is open-source and free to use. However, costs may apply for third-party services like LLM APIs, embedding models, or vector databases you choose to integrate with your RAG pipelines.
What are the prerequisites for running UltraRAG?+
You need Python 3.x and either uv package manager (recommended) or pip for installation. For GPU acceleration, CUDA 12.9 is supported. Optional components include Milvus vector database for knowledge base management and various LLM providers for generation tasks.
How do I install UltraRAG?+
Open the source repository on GitHub and follow its README. UltraRAG is a mcp server — MCP Agents Market links you directly to the official repo.
Is UltraRAG free?+
UltraRAG is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.