Search
Search through store content using natural language queries.
Perform semantic search that understands meaning rather than just keywords. Uses advanced multimodal embedding models to find relevant content based on context and intent with sub-second response times. Search across text chunks within stores using natural language queries like "comfortable running shoes" to find "cushioned athletic sneakers".
Command
mxbai store search <name-or-id> <query> [options]Options
--top-k <n>- Number of results to return (default:10, range:1-100)--threshold <score>- Minimum similarity score (range:0.0-1.0)--return-metadata- Include file metadata in results--rerank- Enable result reranking for better relevance (default:false)--file-search- Search files instead of chunks
Note: Default values for --top-k and --rerank can be configured using mxbai config. See the Configuration Guide for details.
Examples
# Basic search
mxbai store search "my-knowledge-base" "how to get started"
# Search with more results
mxbai store search "my-knowledge-base" "authentication" --top-k 20
# Search with similarity threshold
mxbai store search "my-knowledge-base" "configuration" --threshold 0.8
# Search and include metadata in results
mxbai store search "my-knowledge-base" "deployment" --return-metadata
# Search and rerank results
mxbai store search "my-knowledge-base" "best practices" --rerank
# Search showing text chunks
mxbai store search "my-knowledge-base" "error handling" --file-search
# Combine multiple options
mxbai store search "my-knowledge-base" "API usage" --top-k 15 --rerank --return-metadata