ragdocs
If you are the rightful owner of ragdocs and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
RagDocs MCP Server provides RAG capabilities using Qdrant vector database and Ollama/OpenAI embeddings for semantic search and document management.
RagDocs MCP Server is a robust Model Context Protocol server designed to enhance documentation management through Retrieval-Augmented Generation (RAG) capabilities. It leverages the Qdrant vector database for efficient vector storage and supports both Ollama and OpenAI embeddings for semantic search. This server allows users to add, search, list, and delete documents, making it a versatile tool for managing large sets of documentation. With features like automatic text chunking and embedding generation, RagDocs MCP Server simplifies the process of organizing and retrieving information. It supports both local and cloud-based Qdrant setups, providing flexibility in deployment. The server is compatible with Node.js and can be easily configured to use either free or paid embedding services, depending on user preference.
Features
- Add documentation with metadata
- Semantic search through documents
- List and organize documentation
- Delete documents
- Support for both Ollama (free) and OpenAI (paid) embeddings
Tools
add_document
Add a document to the RAG system.
search_documents
Search through stored documents using semantic similarity.
list_documents
List all stored documents with pagination and grouping options.
delete_document
Delete a document from the RAG system.
