Enables semantic search in Qdrant vector databases using OpenAI embeddings.
Qdrant MCP server exists for a simple reason — assistants are far more useful when they can act on Qdrant directly instead of describing what you should do. Enables semantic search in Qdrant vector databases using OpenAI embeddings.
This MCP server provides vector search capabilities using Qdrant vector database and OpenAI embeddings.
Once Qdrant is connected, these are the calls the assistant has available:
query_collection — Search a Qdrant collection using semantic search with OpenAI embeddingslist_collections — The list_collections tool exposed by this servercollection_info — The collection_info tool exposed by this serverYou will need 3 environment variables: OPENAI_API_KEY, QDRANT_URL, QDRANT_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
@smithery/cli on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Qdrant's toolset — query_collection, list_collections, collection_info — is a fair guide to whether it matches your workflow. It is maintained by amansingh0311; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| query_collection | Search a Qdrant collection using semantic search with OpenAI embeddings. |
| list_collections | The list_collections tool exposed by this server. |
| collection_info | The collection_info tool exposed by this server. |
{
"mcpServers": {
"qdrant-openai": {
"command": "npx",
"args": ["-y", "@smithery/cli"],
"env": {
"OPENAI_API_KEY": "your-value",
"QDRANT_URL": "your-value",
"QDRANT_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| QDRANT_URL | Endpoint or connection string the server talks to. | Yes |
| QDRANT_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.