RagDocs
Enables semantic search and management of documentation through vector similarity using RAG techniques.
About
RagDocs is a Model Context Protocol (MCP) server that leverages Retrieval-Augmented Generation (RAG) capabilities for enhanced document search and management. It utilizes Qdrant vector database and supports both Ollama and OpenAI embeddings to enable semantic search through documentation. RagDocs facilitates adding, listing, organizing, and deleting documents, making it a comprehensive solution for managing and accessing information through vector similarity.
Key Features
- Adds documentation with metadata
- Performs semantic search through documents
- Lists and organizes documentation
- Deletes documents
- Supports Ollama and OpenAI embeddings
Use Cases
- Creating a searchable knowledge base from documentation
- Implementing semantic search in a document management system
- Building RAG-based applications for information retrieval
Sponsored