ask_database
Answer natural-language questions by retrieving and synthesizing relevant information from your DEVONthink databases, returning answers with citations.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | Ask a natural-language question, get an answer with citations. Retrieval over the user's DEVONthink databases. By default uses BM25-only (zero setup, no embedding model download). Vector retrieval is opt-in experimental in 0.1.0 (set `ISTEFOX_RAG_ENABLED=1` and run `istefox-dt-mcp reindex <db>` to populate the local vector index). See ADR-008 for the embedding model selection roadmap. When to use: - The user asks an open question whose answer is in their archive. - You need a synthesized answer, not just a list of documents. Don't use for: - Listing candidate documents -> use `search`. - Bulk operations -> use the dedicated write tools. Examples: - {"question": "Quali isolatori abbiamo proposto a Keraglass?"} |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| success | Yes | ||
| audit_id | No | ||
| warnings | No | ||
| error_code | No | ||
| error_message | No | ||
| recovery_hint | No |