MCP Qdrant Server with OpenAI Embeddings provides vector search capabilities by connecting AI assistants to Qdrant vector databases. The server exposes three main tools: semantic search in collections using OpenAI embeddings, listing available collections, and viewing collection information. It handles the generation of embeddings from natural language queries and performs vector similarity search against Qdrant collections, making it valuable for applications requiring semantic document retrieval, knowledge base search, or any use case where finding contextually similar content is important.
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Search a Qdrant collection using semantic search with OpenAI embeddings. Parameters: collection_name (string), query_text (string), limit (optional integer, default: 5), model (optional string, default: text-embedding-3-small)
List all available collections in the Qdrant database.
Get information about a specific collection. Parameters: collection_name (string)
