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Better Qdrant MCP Server

by wrediam
OverviewInspectNewSchemaRelated ServersScore
TypeScript
Remote
MIT License
56
1

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

Deploy Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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