Command Palette

Search for a command to run...

UnylyUnyly
Весь каталог

Qdrant Embedding Search

БесплатноНе проверен

MCP server that searches documents in Qdrant using embeddings from LMStudio. Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, a

GitHubEmbed

Описание

MCP server that searches documents in Qdrant using embeddings from LMStudio. Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, and performs semantic search in Qdrant.

README

MCP server that searches documents in Qdrant using embeddings from LMStudio.

Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, and performs semantic search in Qdrant.

Prerequisites

  • Node.js 18+
  • LMStudio running with an embedding model loaded (default: text-embedding-qwen3-embedding-4b)
  • Qdrant running with a collection containing your documents

Usage

With npx

{
  "mcpServers": {
    "qdrant-docs": {
      "command": "npx",
      "args": ["-y", "mcp-qdrant-embedding-search"],
      "env": {
        "QDRANT_URL": "http://localhost:6333",
        "QDRANT_COLLECTION": "my_docs",
        "LMSTUDIO_URL": "http://localhost:1234"
      }
    }
  }
}

With node (local)

git clone https://github.com/plixplox/mcp-qdrant-embedding-search.git
cd mcp-qdrant-embedding-search
npm install
npm run build
{
  "mcpServers": {
    "qdrant-docs": {
      "command": "node",
      "args": ["/path/to/mcp-qdrant-embedding-search/dist/index.js"],
      "env": {
        "QDRANT_COLLECTION": "my_docs"
      }
    }
  }
}

Tools

search_docs

Search documents by semantic similarity.

Parameter Type Required Description
query string yes Search query text
limit number no Max results (default: 5)
collection string no Qdrant collection (default: from config)

list_collections

List all available Qdrant collections. No parameters.

Configuration

All settings are configured via environment variables:

Variable Default Description
LMSTUDIO_URL http://localhost:1234 LMStudio server URL
LMSTUDIO_EMBEDDING_MODEL text-embedding-qwen3-embedding-4b Embedding model name
QDRANT_URL http://localhost:6333 Qdrant server URL
QDRANT_API_KEY Qdrant API key (optional)
QDRANT_COLLECTION documents Default collection to search
SEARCH_LIMIT 5 Default number of results
TOOL_SEARCH_NAME search_docs Custom name for the search tool
TOOL_SEARCH_DESCRIPTION Search documentation by semantic similarity... Custom description for the search tool
TOOL_LIST_NAME list_collections Custom name for the list tool
TOOL_LIST_DESCRIPTION List all available Qdrant collections Custom description for the list tool

Custom tool descriptions

Tool names and descriptions are visible to the LLM and affect when it decides to call them. Customize them to match your use case:

{
  "env": {
    "TOOL_SEARCH_NAME": "search_api_reference",
    "TOOL_SEARCH_DESCRIPTION": "Search the REST API reference. Use when you need endpoint specs, request/response schemas, or auth details."
  }
}

License

ISC

from github.com/plixplox/mcp-qdrant-embedding-search

Установка Qdrant Embedding Search

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/plixplox/mcp-qdrant-embedding-search

FAQ

Qdrant Embedding Search MCP бесплатный?

Да, Qdrant Embedding Search MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Qdrant Embedding Search?

Нет, Qdrant Embedding Search работает без API-ключей и переменных окружения.

Qdrant Embedding Search — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Qdrant Embedding Search в Claude Desktop, Claude Code или Cursor?

Открой Qdrant Embedding Search на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

Похожие MCP

Compare Qdrant Embedding Search with

Не уверен что выбрать?

Найди свой стек за 60 секунд

Автор?

Embed-бейдж для README

Похожее

Все в категории ai