Qdrant Vector Database

MCP Server for Qdrant provides a vector database integration for storing and retrieving information using semantic search capabilities. Built with Python, it supports multiple embedding providers including FastEmbed, sentence-transformers, and lightweight alternatives optimized for Alpine Linux environments with minimal dependencies. The server offers two main tools: 'qdrant-store' for saving text with optional metadata and 'qdrant-find' for semantic searching of stored information. It can be deployed via Docker or run locally, making it ideal for AI assistants that need persistent memory storage with efficient retrieval based on meaning rather than exact keyword matching.