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Qdrant MCP Server

Built by Vinkius GDPR ToolsFree

Empower your AI to interact directly with your Qdrant vector database — query clusters, perform similarity searches, and manage collections effortlessly.

Vinkius AI Gateway supports streamable HTTP and SSE.

Qdrant

Works with every AI agent you already use

…and any MCP-compatible client

CursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWSCursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWS

Qdrant MCP Server: see your AI Agent in action

AI AgentVinkiusQdrant
You

Vinkius AI Gateway
GDPR·High Security·Kill Switch·Ultra-Low Latency·Plug and Play

Built-in capabilities (7)

count

Counts the total number of points in a collection

delete

This action is irreversible. Deletes specific points from a collection

get_collection

Retrieves detailed information about a specific collection

get_points

Retrieves specific points by their IDs

list_collections

Lists all collections in the Qdrant instance

scroll

Returns points with their payloads. Scrolls through points in a collection, useful for pagination

search

You must provide a JSON array of floats for the query vector. Performs a nearest neighbor vector search in a collection

What this connector unlocks

Connect your Qdrant vector database (Cloud or Self-Hosted) to any AI agent and bring powerful semantic retrieval and database management into your conversation.

What you can do

  • Discover Collections — List all vector collections in your cluster, fetch detailed distance metrics, and monitor total payload points instantly
  • Semantic Vector Search — Perform nearest neighbor similarity searches. Pass a JSON array of floats and retrieve the exact payloads matching your query
  • Data Management — Read specific points by ID or scroll sequentially through giant datasets to debug payloads and embedding quality
  • Mutation Operations — Delete redundant data points safely without building separate admin scripts

How it works

1. Subscribe to this server
2. Provide your Qdrant Base URL and API Key
3. Start querying your embeddings directly from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • AI & ML Engineers — query embedded spaces directly from your console while building RAG (Retrieval-Augmented Generation) applications
  • Data Scientists — inspect payloads and test distance parameters on live indices without launching Jupyter Notebooks
  • Backend Developers — manage vector cluster configuration and clear bad datasets efficiently

Frequently asked questions

Give your AI agents the power of Qdrant

Access Qdrant and 2,000+ MCP servers — ready for your agents to use, right now. No glue code. No custom integrations. Just plug Vinkius AI Gateway and let your agents work.