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Connect Qdrant to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Query and manage your vector clusters through any AI client.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 7 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-04

4 capabilities in this set.

Part of 7 available through Qdrant.

  1. 01

    Get points

    This capability retrieves specific data points using their unique IDs.

  2. 02

    List collections

    Use this to see every collection currently active in your Qdrant instance.

  3. 03

    Get collection

    This capability pulls detailed configuration and metadata for a specific collection.

  4. 04

    Search

    This capability performs a nearest neighbor similarity search using a JSON array of floats.

Capability set02 / 02

05-07

3 capabilities in this set.

Part of 7 available through Qdrant.

  1. 05

    Scroll

    This capability lets you paginate through points in a collection to view their payloads.

  2. 06

    Count

    Use this to get the total number of points stored in a collection.

  3. 07

    Delete

    This capability removes specific points from a collection. This action cannot be undone.

Real work

What teams actually run

01

RAG Debugging

Check if your retrieval is pulling the correct payloads by running similarity searches through your agent.

02

Dataset Cleanup

Remove redundant or incorrect data points directly from your chat interface.

03

Index Monitoring

Quickly check the total point count and configuration of your collections.

04

Payload Inspection

Scroll through large datasets to verify that your embeddings and metadata are correctly stored.

Automate a task

Put Qdrant to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Qdrant works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Qdrant to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

867ms average. Fast in production.

Qdrant is checked daily against the live service.

Daily averagePeak 1106ms
Oct 3Today
Fastest day
757ms
Slowest day
1106ms
14-day trend
Slowing+23%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 7 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Qdrant, so you can see the experience inside your AI.

It does not authenticate your account with Qdrant. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Qdrant Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_q8RmctE5Ixu7FdouvzysiVBMHUlpWlDBAdtwVmus/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Qdrant capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "qdrant-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_q8RmctE5Ixu7FdouvzysiVBMHUlpWlDBAdtwVmus/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Qdrant in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Qdrant owners hand off.

This MCP is built for technical professionals working with high-dimensional data and RAG systems.

  • 01

    AI & ML Engineers

    They use the agent to query embedded spaces while building RAG applications.

  • 02

    Data Scientists

    They inspect payloads and test distance parameters on live indices.

  • 03

    Backend Developers

    They manage vector cluster configurations and clear out bad datasets.

FAQ

Questions Qdrant owners ask.

  • 01

    Does this work with self-hosted Qdrant?

    Yes, this MCP connects to both Qdrant Cloud and self-hosted instances.

  • 02

    Which AI clients can I use with this MCP?

    You can use any MCP-compatible client, including Claude, Cursor, and Windsurf.

  • 03

    Can I perform similarity searches?

    Yes, you can perform nearest neighbor similarity searches by providing a JSON array of floats to the search capability.

  • 04

    Is deleting data permanent?

    Yes, the delete capability performs an irreversible action on the specified points.

  • 05

    How do I see my data payloads?

    You can use the scroll capability to paginate through points and view their associated payloads.

  • 06

    How do I find my Qdrant URL and API Key?

    For Qdrant Cloud: Go to the Qdrant Cloud Console, select your cluster to open the Cluster Detail Page. The endpoint will be displayed there (e.g., xyz.us-east4-0.gcp.cloud.qdrant.io), and you can generate Database API Keys underneath it (they start with eyJhb). For Self-hosted: Provide your custom URL and the static custom key you defined in your config.yaml.

  • 07

    Can my AI use this for a RAG architecture directly?

    Yes contextually, but practically your agent acts as the database debugger. It can formulate vector arrays to query search_points, retrieving identical payload structures. It's meant for the engineer building the RAG, helping you inspect distances and debug faulty retrieval mechanisms mid-code.

  • 08

    Does it support deleting vectors?

    Yes. If an embedding got corrupted or references dropped articles, use the delete capability. Pass the collection name and the list of specific IDs. Qdrant handles the mutation instantly and updates the index without rebuilding.

  • 09

    What if I have millions of points?

    Instead of overloading your chat context, instruct your agent to use the count capability to grasp the scale, and the scroll capability with a small limit constraint (e.g., 5-10 records at a time). This paginates large bodies cleanly when analyzing index health.

Explore

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