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.

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

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

A Model Context Protocol server that enables semantic search capabilities by providing tools to manage Qdrant vector database collections, process and embed documents using various embedding services, and perform semantic searches across vector embeddings.

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