RAG Anything
Processes and queries directories of documents using multimodal Retrieval-Augmented Generation (RAG) capabilities.
关于
RAG Anything provides a robust Model Context Protocol (MCP) server designed to deliver comprehensive Retrieval-Augmented Generation (RAG) functionalities. It excels at processing and querying large collections of documents, supporting full multimodal content extraction including images, tables, and equations. This server enables batch processing of entire directories, offers advanced querying with various modes (hybrid, local, global, naive, mix, bypass), and ensures persistent storage of RAG instances for efficient and repeatable information retrieval from diverse file types like PDFs, DOCX, and TXT.
主要功能
- Advanced Querying with Multiple Modes (Hybrid, Local, Global, Naive, Mix, Bypass)
- End-to-End Document Processing with Multimodal Content Extraction
- Persistent Storage for Processed RAG Instances
- Comprehensive Multimodal RAG (Images, Tables, Equations, Charts)
- Batch Processing of Entire Directories
- 1 GitHub stars
使用案例
- Performing complex queries that combine pure text input with external multimodal content for enhanced analytical insights.
- Building a searchable knowledge base from a collection of diverse documents, including research papers and corporate archives.
- Automating the extraction, indexing, and querying of information across large volumes of structured and unstructured documents.
Sponsored