
Lightning-fast, privacy-first evaluation and QA dataset generation for RAG systems.
Visit RAGScoreRAGScore is an MCP server designed to automate the generation of question-answer datasets and quantitative evaluation of Retrieval-Augmented Generation (RAG) systems using any LLM. It supports privacy-first workflows, runs locally or in the cloud, and provides instant evaluations, detailed multi-metric reports, and visualizations. It integrates seamlessly with tools like Ollama for local LLMs, Jupyter/Colab for notebooks, and production environments using a CLI or Python API, making it ideal for AI developers, ML engineers, and RAG system builders who need fast, reliable, and private evaluation of information retrieval pipelines.
Visit RAGScore's official website for product details and getting started.