databasesai-ml

Better Qdrant

by wrediam

Better Qdrant connects AI to Qdrant vector database, enabling seamless semantic search and efficient document management

Connects AI systems to Qdrant vector database for semantic search capabilities through multiple embedding services, enabling efficient document management and similarity searches without leaving the conversation interface.

github stars

2

Multiple embedding providers (OpenAI, Ollama, FastEmbed)Local embedding options available

best for

  • / Building RAG applications with document search
  • / AI developers working with vector databases
  • / Semantic search implementations

capabilities

  • / List Qdrant collections
  • / Add documents to vector collections
  • / Perform semantic searches
  • / Delete collections
  • / Generate embeddings with multiple services

what it does

Connects to Qdrant vector databases to store documents and perform semantic searches using various embedding services. Enables AI systems to manage vector collections and find similar documents through natural language queries.

about

Better Qdrant is a community-built MCP server published by wrediam that provides AI assistants with tools and capabilities via the Model Context Protocol. Better Qdrant connects AI to Qdrant vector database, enabling seamless semantic search and efficient document management It is categorized under databases, ai ml.

how to install

You can install Better Qdrant in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Better Qdrant is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

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 href="https://glama.ai/mcp/servers/@wrediam/better-qdrant-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@wrediam/better-qdrant-mcp-server/badge" alt="Better Qdrant Server MCP server" /> </a>

Features

  • List Collections: View all available Qdrant collections
  • Add Documents: Process and add documents to a Qdrant collection with various embedding services
  • Search: Perform semantic searches across your vector database
  • Delete Collection: Remove collections from your Qdrant database

Installation

npm install -g better-qdrant-mcp-server

Or use it directly with npx:

npx better-qdrant-mcp-server

Configuration

The server uses environment variables for configuration. You can set these in a .env file in your project root:

# Qdrant Configuration
QDRANT_URL=http://localhost:6333
QDRANT_API_KEY=your_api_key_if_needed

# Embedding Service API Keys
OPENAI_API_KEY=your_openai_api_key
OPENROUTER_API_KEY=your_openrouter_api_key
OLLAMA_ENDPOINT=http://localhost:11434

Supported Embedding Services

  • OpenAI: Requires an API key
  • OpenRouter: Requires an API key
  • Ollama: Local embedding models (default endpoint: http://localhost:11434)
  • FastEmbed: Local embedding models

Usage with Claude

To use this MCP server with Claude, add it to your MCP settings configuration file:

{
  "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"
      }
    }
  }
}

Example Commands

List Collections

use_mcp_tool
server_name: better-qdrant
tool_name: list_collections
arguments: {}

Add Documents

use_mcp_tool
server_name: better-qdrant
tool_name: add_documents
arguments: {
  "filePath": "/path/to/your/document.pdf",
  "collection": "my-collection",
  "embeddingService": "openai",
  "chunkSize": 1000,
  "chunkOverlap": 200
}

Search

use_mcp_tool
server_name: better-qdrant
tool_name: search
arguments: {
  "query": "your search query",
  "collection": "my-collection",
  "embeddingService": "openai",
  "limit": 5
}

Delete Collection

use_mcp_tool
server_name: better-qdrant
tool_name: delete_collection
arguments: {
  "collection": "my-collection"
}

Requirements

  • Node.js >= 18.0.0
  • A running Qdrant server (local or remote)
  • API keys for the embedding services you want to use

License

MIT

FAQ

What is the Better Qdrant MCP server?
Better Qdrant is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Better Qdrant?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Better Qdrant is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Better Qdrant against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Better Qdrant is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Better Qdrant reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Better Qdrant for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Better Qdrant surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Better Qdrant has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Better Qdrant benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Better Qdrant into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Better Qdrant is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.