MCP server that searches documents in Qdrant using embeddings from LMStudio. Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, and performs semantic search in Qdrant.
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process.env. You'll be asked to provide them before it can run.LMSTUDIO_EMBEDDING_MODEL— text-embedding-qwen3-embedding-4b Embedding model nameLMSTUDIO_URL— "": "http://localhost:1234"QDRANT_API_KEY— Qdrant API key (optional)QDRANT_COLLECTION— "": "my_docs",QDRANT_URL— "": "http://localhost:6333",SEARCH_LIMIT— 5 Default number of resultsTOOL_LIST_DESCRIPTION— List all available Qdrant collections Custom description for the list toolTOOL_LIST_NAME— list_collections Custom name for the list toolTOOL_SEARCH_DESCRIPTION— Search documentation by semantic similarity... Custom description for the search toolTOOL_SEARCH_NAME— search_docs Custom name for the search tool[](https://m8ven.ai/mcp/plixplox-mcp-qdrant-embedding-search-1al1y9)