Qdrant Retrieve
Semantic search using the Qdrant vector database.
Qdrant Retrieve MCP Server
MCP server for semantic search with Qdrant vector database.
Features
- Semantic search across multiple collections
- Multi-query support
- Configurable result count
- Collection source tracking
Note: The server connects to a Qdrant instance specified by URL.
Note 2: The first retrieve might be slower, as the MCP server downloads the required embedding model.
API
Tools
- qdrant_retrieve
- Retrieves semantically similar documents from multiple Qdrant vector store collections based on multiple queries
- Inputs:
collectionNames(string[]): Names of the Qdrant collections to search acrosstopK(number): Number of top similar documents to retrieve (default: 3)query(string[]): Array of query texts to search for
- Returns:
results: Array of retrieved documents with:query: The query that produced this resultcollectionName: Collection name that this result came fromtext: Document text contentscore: Similarity score between 0 and 1
Usage with Claude Desktop
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"qdrant": {
"command": "npx",
"args": ["-y", "@gergelyszerovay/mcp-server-qdrant-retrive"],
"env": {
"QDRANT_API_KEY": "your_api_key_here"
}
}
}
}
Command Line Options
MCP server for semantic search with Qdrant vector database.
Options
--enableHttpTransport Enable HTTP transport [default: false]
--enableStdioTransport Enable stdio transport [default: true]
--enableRestServer Enable REST API server [default: false]
--mcpHttpPort=<port> Port for MCP HTTP server [default: 3001]
--restHttpPort=<port> Port for REST HTTP server [default: 3002]
--qdrantUrl=<url> URL for Qdrant vector database [default: http://localhost:6333]
--embeddingModelType=<type> Type of embedding model to use [default: Xenova/all-MiniLM-L6-v2]
--help Show this help message
Environment Variables
QDRANT_API_KEY API key for authenticated Qdrant instances (optional)
Examples
$ mcp-qdrant --enableHttpTransport
$ mcp-qdrant --mcpHttpPort=3005 --restHttpPort=3006
$ mcp-qdrant --qdrantUrl=http://qdrant.example.com:6333
$ mcp-qdrant --embeddingModelType=Xenova/all-MiniLM-L6-v2
İlgili Sunucular
Library Docs MCP Server
Search and fetch documentation for popular libraries like Langchain, Llama-Index, and OpenAI using the Serper API, providing updated information for LLMs.
招投标大数据服务
Provides comprehensive import and export trade data query functions, including trend analysis, product statistics, and geographic distribution.
Anime MCP Server
An AI-powered server for searching and getting recommendations for anime.
SearxNG MCP Server
Provides web search capabilities using a self-hosted SearxNG instance, allowing AI assistants to search the web.
Haloscan
Interact with the Haloscan SEO API for search engine optimization tasks.
Hatch MCP Server
Find emails, phone numbers, company data, and LinkedIn URLs using the Hatch API.
302AI Web Search
A web search server powered by the 302.AI API.
MediaWiki MCP Server
Interact with the MediaWiki API to search and retrieve content from Wikipedia or other MediaWiki sites.
Steam Game Server MCP
Model Context Protocol (MCP) server that inquires, diagnoses, and manages steam profiles, game libraries, concurrent users, and game server status.
Gemini AI MCP Server
Provides AI-powered web search and summarization using the Gemini API's grounding feature.