A unified Docker container that runs Qdrant vector database and provides REST API and MCP interfaces for vector storage and semantic search, compatible with Claude vector hooks.
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process.env. You'll be asked to provide them before it can run.QDRANT_MCP_CONFIGQDRANT_DATA_PATH— Data storage path (default: /qdrant/storage)QDRANT_SNAPSHOTS_PATH— Snapshots path (default: /qdrant/snapshots)QDRANT_LOG_PATHQDRANT_HOST— Qdrant server host (default: localhost)QDRANT_PORT— Qdrant server port (default: 6333)QDRANT_GRPC_PORTCOLLECTION_NAME— Default collection (default: claude_vectors)EMBEDDING_MODEL— Model name (default: all-MiniLM-L6-v2)VECTOR_SIZE— Vector dimensions (default: 384)MAX_TOKENS— Max tokens before vectorization (default: 512)TOP_KMIN_SCOREAPI_HOST— API server host (default: 0.0.0.0)API_PORT— API server port (default: 8000)API_LOG_LEVELMCP_PORT— MCP HTTP server port (default: 8001)MCP_SERVER_NAMEMCP_SERVER_VERSIONLOG_PATHLOG_LEVELAPI_KEY— Optional API key for authenticationENABLE_TLS— Enable HTTPS (default: false)QDRANT_MCP_HOSTQDRANT_MCP_PORTQDRANT_MCP_API— export ="http://your-server:8000"QDRANT_MCP_VERIFY_SSLQDRANT_MCP_SSL_CERTQDRANT_MCP_CA_BUNDLEQDRANT_MCP_CA_CERTS_DIRREQUESTS_CA_BUNDLE[](https://m8ven.ai/mcp/stigenai-qdrant-mcp-lzyx93)