# Better Qdrant MCP Server A Model Context Protocol (MCP) server for enhanced Qdrant vector database functionality. This server provides tools for
Better Qdrant MCP server exists for a simple reason — assistants are far more useful when they can act on Better Qdrant directly instead of describing what you should do. # Better Qdrant MCP Server A Model Context Protocol (MCP) server for enhanced Qdrant vector database functionality. This server provides tools for managing Qdrant collections, adding documents, and performing semantic searches. <a.
The server ships on npm as better-qdrant-mcp-server, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Once Better Qdrant is connected, these are the calls the assistant has available:
Search — The Search tool exposed by this serverYou will need 8 environment variables: QDRANT_URL, QDRANT_API_KEY, DEFAULT_EMBEDDING_SERVICE, OPENAI_API_KEY, OPENAI_ENDPOINT, OPENROUTER_API_KEY, OPENROUTER_ENDPOINT, OLLAMA_ENDPOINT. 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.
This sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Better Qdrant's toolset — Search — is a fair guide to whether it matches your workflow. It is maintained by wrediam; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Better Qdrant's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Search | The Search tool exposed by this server. |
{
"mcpServers": {
"better-qdrant": {
"command": "npx",
"args": ["better-qdrant-mcp-server"],
"env": {
"QDRANT_URL": "http://localhost:6333",
"QDRANT_API_KEY": "your_api_key_if_needed",
"DEFAULT_EMBEDDING_SERVICE": "ollama",
"OPENAI_API_KEY": "your_openai_api_key",
"OPENAI_ENDPOINT": "https://api.openai.com/v1",
"OPENROUTER_API_KEY": "your_openrouter_api_key",
"OPENROUTER_ENDPOINT": "https://api.openrouter.com/v1",
"OLLAMA_ENDPOINT": "http://localhost:11434",
"OLLAMA_MODEL": "nomic-embed-text"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| QDRANT_URL | Endpoint or connection string the server talks to. | Yes |
| QDRANT_API_KEY | Credential the server authenticates with. | Yes |
| DEFAULT_EMBEDDING_SERVICE | Configuration value read at startup. | Optional |
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| OPENAI_ENDPOINT | Configuration value read at startup. | Optional |
| OPENROUTER_API_KEY | Credential the server authenticates with. | Yes |
| OPENROUTER_ENDPOINT | Configuration value read at startup. | Optional |
| OLLAMA_ENDPOINT | Configuration value read at startup. | Optional |
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.