search_content

io.github.simonmak-ascent/esg-hub · Verify this server

Hybrid search that fuses 384-dim semantic similarity with BM25 and ESG re-ranking across ESG Hub articles and external resources. Use for conceptual or paraphrased questions — natural-language phrases work better than single tokens because `query` is embedded; when the user gives an exact identifier or phrase prefer the cheaper search_esg. `query` must be non-empty and `limit` defaults to 10 and is capped at 50. Returns one ranked page of up to `limit` items, each carrying a fused relevance score (higher is better); there is no pagination, so raise `limit` to widen, and unlike search_esg there is no `source` filter. Zero matches returns an empty item list, not an error. Cached ~2 minutes; rate-limited per IP; retry on 5xx.