Qdrant Packages

A RAG-based document question answering system

A Model Context Protocol server for fetching and storing documentation in a vector database, enabling semantic search and retrieval to augment LLM capabilities with relevant documentation context.

MCP server implementation for RAG with vector database support

AI-powered MCP server for codebase navigation and LLM prompt optimization

An MCP server for semantic documentation search and retrieval using vector databases to augment LLM capabilities.

A Model Context Protocol server for fetching and storing documentation in a vector database, enabling semantic search and retrieval to augment LLM capabilities with relevant documentation context.

Qdrant vector search engine client library for node

A Model Context Protocol server for fetching and storing documentation in a vector database, enabling semantic search and retrieval to augment LLM capabilities with relevant documentation context.

An MCP server that scrapes websites, indexes content into Qdrant, and provides a query tool.

A NodeJS RAG framework to easily work with LLMs and custom datasets

Core memory engine with vector operations for AI agents

A Model Context Protocol server for fetching and storing documentation in a vector database, enabling semantic search and retrieval to augment LLM capabilities with relevant documentation context.