What can an AI agent do with Qdrant?

Your AI agent can search vector collections, scroll and inspect points, retrieve collection metadata, and, with your approval - create collections, upsert vectors, and delete data. This covers the full lifecycle of working with a Qdrant vector store.

Are write operations safe?

Yes. Actions that modify your data: creating collections, upserting points, or deleting records - always require explicit approval before they run. Read-only operations like searching and listing are shown to you before they run.

Can my agent use Qdrant for RAG?

Absolutely. Your agent can embed a query, run a similarity search in Qdrant, retrieve the top matching chunks, and pass them as context to a language model, all in a single automated workflow.

Does this work with self-hosted Qdrant instances?

Yes. You can connect your agent to any Qdrant instance - Qdrant Cloud or a self-hosted deployment - by providing the host URL and an API key during setup.

Developer tools

Qdrant, run by an agent.

An AI agent that searches, manages, and queries your vector database with precision.

Connect Qdrant Book a demo

What needs your approval

Qdrant never changes anything without you.

Anything that creates, edits or deletes in Qdrant waits for your approval. Approve a recurring task once and it runs unattended after that.

Connecting Qdrant

About 5 minutes

Auth: API key
Setup: About 5 minutes

Where to get access

Find your cluster URL and API key in the Qdrant Cloud console. Store as JSON: {"url": "https://...", "key": "..."}. Self-hosted: omit key field and use {"url": "http://localhost:6333", "key": ""}

cloud.qdrant.io