What can an AI teammate do with Qdrant?

Your AI teammate 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 run autonomously.

Can my teammate use Qdrant for RAG?

Absolutely. Your teammate 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 teammate to any Qdrant instance - Qdrant Cloud or a self-hosted deployment - by providing the host URL and an API key during setup.

Developer tools

AI Teammate for Qdrant

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

Your AI teammate for Qdrant can search vector collections, retrieve points, and inspect collection metadata autonomously. Write actions - such as creating collections, upserting points, and deleting data - require your approval before execution, keeping your vector store safe.

Connecting Qdrant lets your AI teammate power semantic search, RAG pipelines, and recommendation systems directly from your vector database. Instead of writing custom queries, your teammate handles similarity search and data management so you can focus on building.

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What your AI teammate can do with Qdrant

Read-only actions run automatically. Write actions require your approval.

Read-only actions

list collections

Retrieve all vector collections in the Qdrant instance.

get collection info

Fetch metadata and configuration details for a specific collection.

search vectors

Run a similarity search against a collection using a query vector.

scroll points

Paginate through points in a collection with optional filtering.

Write actions (require approval)

create collection

Create a new vector collection with specified distance metric and vector size.

upsert points

Insert or update vectors and their payloads in a collection.

delete points

Remove points from a collection by ID or filter condition.

Example workflows with Qdrant

Real tasks you can run on a schedule or on demand.

task

semantic search over internal knowledge bases

task

retrieval-augmented generation (RAG) pipelines

task

recommendation systems based on vector similarity

task

duplicate detection and near-match clustering

How to connect Qdrant

Create a free m8tes account.

Connect Qdrant

Click Connect and complete the OAuth flow or enter your API key.

Create a task

Give your AI teammate a task that uses Qdrant. It handles the rest.

Qdrant AI teammate: FAQ

Common questions about using an AI teammate with Qdrant.

Build an AI teammate for Qdrant

Connect Qdrant to an autonomous AI teammate that reads data, runs tasks on schedule, and delivers structured output.

AI teammates — all integrations
Build a teammate that uses Qdrant alongside your other tools.

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