linkfox-ehunt-etsy-product-query

EHunt Etsy Product Search (_ehunt_productQuery）

When the LinkFox "Third-Party Data Service" MCP is available, call by tool name _ehunt_productQuery (MCP display name:Etsy Product Search; refer to the tool metadata issued in the current environment). Authentication and upstream routing are handled by the gateway; if the response contains a root-level code field, whether it succeeded is subject to the live network.

Key Points

• Pagination：page starts from 1;pageSize defaults to 20, maximum 100 (recommended ≤50).
• Range parameters: same idea as the shop interface,begin* / end* in pairs.
• Sorting：sortBy is 1~6(EHunt upstream sort_by）。sortDesc：1=descending, 2=ascending(different from _ehunt_storeQuery 's 1/0).
• Product type productType：1 handmade,2 vintage,3 digital,4 custom,9 other; use commas for multiple selections.
• Currency：currencyCode defaults to USD。
• Category id：category is a single category ID; you can first obtain the id via the category search skill.

Script (optional)

Command-line debugging:python scripts/ehunt_etsy_product_query.py '<JSON>'(requires LINKFOXAGENT_API_KEY). See the end of references/api.md .

Reference

See the input/output parameter table at references/api.md。

Handling Large Responses

To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:

python scripts/response_io.py run --script scripts/ehunt_etsy_product_query.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"

Pick --out-dir outside any git working tree (e.g. /tmp/... on Unix, %TEMP%/... on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.

run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.

When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:

• High field count per record, or fields you don't need
• Batch/paginated results (multiple items per call)
• Long-text fields (descriptions, reviews, HTML, time series)
• Output reused across later steps rather than consumed immediately

For small, single-use responses, calling the main script directly is fine.

⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read.