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linkfox-ehunt-etsy-product-query

linkfox-ehunt-etsy-product-query

github.com/linkfox-aiMarketing & growth113131 installsUpdated 2w ago
Repository

About linkfox-ehunt-etsy-product-query

A skill for Etsy market researchers using LinkFox’s third-party data services MCP to query products through `_ehunt_productQuery`. It supports pagination, filters, and sorting, and can save large responses to disk for selective reading.

Key features

  1. 01Filter by product type and category
  2. 02Paginated queries and range parameters
  3. 03Sort by field and direction
  4. 04Save and selectively read large responses

Use cases

  1. 01Filter Etsy products by type
  2. 02Retrieve product results across pages
  3. 03Save large results and extract selected fields

MCP support

Calls `_ehunt_productQuery` through LinkFox’s third-party data services MCP to provide Etsy product queries to MCP clients.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-ehunt-etsy-product-query

After installing, type/linkfox-ehunt-etsy-product-queryin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
api.md
scripts/
ehunt_etsy_product_query.py
response_io.py

Details

From the project README

EHunt Etsy 商品查询（_ehunt_productQuery）

在具备 LinkFox「第三方数据服务」MCP 时，按工具名 _ehunt_productQuery 调用（MCP 展示名：Etsy商品查询，以当前环境下发的工具元数据为准）。鉴权与上游路由由网关处理；若响应含根级 code 字段，是否成功以实网为准。

要点

  • 分页：page 从 1 起；pageSize 默认 20、最大 100（建议 ≤50）。
  • 区间入参：与店铺接口相同思路，begin* / end* 成对。
  • 排序：sortBy 为 1~6（EHunt 上游 sort_by）。sortDesc：1=降序，2=升序（与 _ehunt_storeQuery 的 1/0 不同）。
  • 商品类型 productType：1 手工、2 复古、3 数字、4 定制、9 其他，多选用逗号。
  • 货币：currencyCode 默认 USD。
  • 类目 id：category 为单品类 ID；可先通过类目检索类技能拿到 id。

脚本（可选）

命令行调试：python scripts/ehunt_etsy_product_query.py '<JSON>'（需 LINKFOXAGENT_API_KEY）。详见 references/api.md 末尾。

参考

入参/出参表见 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.

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