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Qdrant MCP ServerUnclaimed
by Qdrant
Gives LLM apps semantic memory stored and searched in Qdrant
- MCP Servers
- Open source
- MCP server
Overview
mcp-server-qdrant is an official Model Context Protocol server for the Qdrant vector search engine. It lets an LLM application keep and retrieve memories, acting as a semantic memory layer on top of a Qdrant database.
The server exposes two tools. qdrant-store saves a piece of information, with optional metadata, into a collection. qdrant-find takes a natural language query and returns the stored information most relevant to it, up to a configurable limit that defaults to 10 results. Setting QDRANT_READ_ONLY disables the store tool for read-only use.
It is aimed at developers who build AI-powered IDEs, chat interfaces or custom AI workflows and want a standard way to connect their models to stored context. The page includes setup steps for Claude Desktop, Claude Code, Cursor, Windsurf and VS Code, along with a Docker image.
The server runs over stdio by default, or over SSE or streamable HTTP for remote clients. It can connect to a Qdrant server by URL with an API key, or to a local Qdrant database path. Embeddings are generated with FastEmbed models, with sentence-transformers/all-MiniLM-L6-v2 as the default. A collection is created automatically if it does not already exist.
The project is licensed under Apache-2.0 and the repository is public. The page does not list prices for the server itself. Running it still requires a Qdrant database, either self-hosted or hosted by Qdrant, and the page does not say what that costs.
- The problem it solves
- AI assistants have no store of their own to save information in and search later, so useful context is lost between sessions
- Who it's for
- Businesses (B2B)
Used for
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Pricing
- Model
- Open source
The maker hasn't added plans or prices yet.
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