Qdrant Retrieve FAQs

Question 1

Why might the first retrieve be slower?

Accepted Answer

The first retrieve might be slower because the MCP server needs to download the required embedding model to encode the queries into vector embeddings.

Question 2

What are the key features of Qdrant Retrieve?

Accepted Answer

Key features include semantic search across multiple collections, multi-query support, configurable result count (topK), and tracking the collection source of each retrieved document.

Question 3

What is Qdrant Retrieve?

Accepted Answer

Qdrant Retrieve is a tool that allows you to perform semantic searches across multiple collections in a Qdrant vector store using natural language queries. It helps you find relevant documents based on meaning, not just keywords.

Question 4

What inputs does the qdrant_retrieve tool require?

Accepted Answer

It requires an array of collection names (`collectionNames`), a number specifying the topK results to return (`topK`), and an array of query texts (`query`).

Question 5

How does Qdrant Retrieve work?

Accepted Answer

It connects to a Qdrant instance using a specified URL, encodes your queries into vectors using an embedding model, and then searches for similar vectors across your chosen collections in Qdrant.  The closest matches are returned as results.

Qdrant Retrieve

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