Zillow Leads Property Data

io.github.kmatata由 GitHub 帳號 kmatata 發布v1.0.8更新於 Oct 24, 2026

MCP server for the zillow-leads-property-data actor: Zillow leads with agent contacts and history.

概覽

AI 產生的概覽

本機 MCP 伺服器,呼叫 Zillow Leads & Property Data 的 Apify actor,回傳含房仲聯絡資訊、價格與稅費歷史及風險標記的 Zillow 房源資料。

可以做什麼
  • 以 catalog 模式執行 Zillow 潛在客戶 actor,快速取得某都會區已快取的充實快照。
  • 以 custom_search 或 recent_activity 模式下單即時蒐集並取回房源結果。
  • 取得基本欄位(地址、價格、房廳數、狀態、面積),或含房仲/仲介公司聯絡資訊、價格與 20 年以上稅費歷史、法拍訊號、學校、HOA 與 resoFacts 的充實資料。
  • 在多次下單之間沿用 zpids 與 MLS ID,避免為同一筆資料重複付費。
適用情境
適合房地產潛在客戶開發與房源調查:需要助理抓取帶房仲聯絡資訊及長期價格、稅費歷史的 Zillow 房源資料,可使用快取快照或即時蒐集訂單。
執行需求
以本機 stdio 程序在使用者電腦上執行(僅桌面端)。它呼叫 Apify actor,因此需要 Apify 帳號與 Apify API 憑證,actor 依事件計費。需要連線至 Apify 與 Zillow 的網路。
安裝前請注意
此 actor 依事件計費:每 1,000 筆基本資料 0.70 美元、每 1,000 筆充實資料 1.20 美元,即時訂單會花用使用者的 Apify 帳戶餘額。資料透過真實瀏覽器工作階段從 Zillow 擷取,充實資料包含房仲姓名、電話與電子郵件等個人聯絡資訊。此儲存庫本身僅為文件與範例,並不會執行 actor。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Zillow Leads Property Data,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

zillow-leads-property-data

Code samples, a sample dataset, and a full workflow notebook for the Zillow Leads & Property Data Apify actor.

The actor pulls Zillow listings enriched with agent/broker contact info, full price-history timelines, 20yr+ tax history, foreclosure/distress flags, schools, and the resoFacts long tail (heating/cooling/construction). Pay-per-event pricing, no subscription: $0.70 per 1,000 bare rows, $1.20 per 1,000 enriched rows.

Try it in 30 seconds, no signup beyond an Apify account

The actor's catalog mode returns a cached, already-enriched snapshot instantly, no bounding box, no wait:

json
{ "mode": "catalog", "metro": "Chicago" }

Run it from the Apify Console or via apify-client (see examples/ below).

What's in this repo

PathWhat it is
sample/sample_listings.csv20 real enriched rows (Chicago/Houston/Phoenix) — flat, spreadsheet-ready
sample/sample_listings.jsonlSame rows, one JSON object per line, with a nested price_history array per listing
examples/python_quickstart.pyCall the actor from Python via apify-client, wait for results, print a summary
examples/node_quickstart.jsSame, in Node, via apify-client
mcp-server/One-tool MCP server for Claude Desktop, Cursor and any MCP client; see mcp-server/README.md
notebook/zillow_leads_workflow.ipynbA realistic lead-gen workflow: run the actor, dedupe against a prior export, filter to rows with agent phone numbers, export a clean CSV

Field reference

Two depths, listings (bare) and enriched (the default):

  • listings: address, price, beds/baths, status, lot/living area, listing-type flags — whatever Zillow's own search API returns, no detail-page fetch involved. See sample_listings.csv for the shape (a subset of the columns shown there — the sample above is enriched-depth, listings-depth rows omit everything past the bare fields).
  • enriched (default): everything in listings, plus agent/broker contact (name, phone, email, brokerage, MLS attribution), full price-history and 20yr+ tax-history timelines, foreclosure/distress signals, assigned + nearby schools, HOA fees, and the resoFacts long tail (heating/cooling/parking/construction).

Full field list, pricing table, and every input mode (catalog / custom_search / recent_activity) are documented on the actor's own README.

Dedup across repeat orders

Every delivery writes a DEDUP_UPDATE record to the run's key-value store: the union of the zpids and MLS IDs you already had plus everything just shipped. Feed those two arrays back into your next order's dedupZpids/dedupMlsIds fields and you're never charged for the same row twice. See notebook/zillow_leads_workflow.ipynb for a worked example.

Use it from an AI agent (MCP)

This actor is callable as a tool via Apify's hosted MCP server (https://mcp.apify.com) or the local @apify/actors-mcp-server, no manual input-form filling required — catalog mode (the default) is a good agent smoke test since it returns cached rows in seconds with no polling loop needed. See the actor's own README for the full agent-facing input schema and the fire/poll/fetch pattern for a live-collection order.

Questions / issues

This repo is documentation and samples only — it doesn't run the actor itself. For a specific order that isn't behaving as expected, check that run's key-value store STATUS record first (the actor writes a plain-English reason there for any zero-row or partial result), then open an issue here or reach out via the actor's Apify Store page.

來源:README.md,提交 01fa450

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v1.0.8最新Sep 16, 2026

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