Workspace Qdrant FAQs

Question 1

What is Workspace Qdrant?

Accepted Answer

Workspace Qdrant is an intelligent, project-scoped vector database server that operates via the Model Context Protocol (MCP). It provides advanced data operations, including hybrid search and configurable collections, specifically designed to enhance AI assistants like Claude Desktop and Claude Code with contextual data.

Question 2

What is hybrid search and how does it benefit me?

Accepted Answer

Hybrid search combines the precision of keyword matching with the relevance of semantic search. It uses Reciprocal Rank Fusion (RRF) to blend these methods, ensuring your AI assistant retrieves the most comprehensive and contextually accurate results from your vector database.

Question 3

Can I choose my own embedding model?

Accepted Answer

Yes, Workspace Qdrant offers configurable embedding model options. You can select from various models (e.g., all-MiniLM-L6-v2, BAAI/bge-base-en-v1.5) to balance performance, quality, and resource usage according to your specific requirements.

Question 4

How do I get started with Workspace Qdrant?

Accepted Answer

After installing it globally with `uv` or `pip`, simply run `workspace-qdrant-setup`. This interactive wizard will guide you through the configuration, test your Qdrant connection, help choose an embedding model, and integrate it seamlessly with Claude Desktop or Claude Code.

Question 5

How does Workspace Qdrant handle data organization?

Accepted Answer

It offers automatic project detection to manage data within project-specific collections. Additionally, it supports global collections and a dedicated 'scratchbook' functionality, allowing for flexible organization of contextual information relevant to your AI assistant's tasks.

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