# JD.com Email Scraper (`leads-scraper/jd-com-email-scraper`) Actor

JD.com Email Scraper SD - JD.com Email Scraper is a lead generation tool that extracts leads with public contact emails, account names and profile URLs from JD.com results by keyword, location and email domain - JD.com email extractor.

- **URL**: https://apify.com/leads-scraper/jd-com-email-scraper.md
- **Developed by:** [Leads Scraper](https://apify.com/leads-scraper) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.49 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### JD.com Email Scraper — Read This Before You Run It

The **JD.com Email Scraper** searches Google's public index for JD.com pages that carry a contact email, and returns whatever it finds as clean, structured data.

Start with the honest part, because it decides whether this Actor is right for you: **JD.com is largely excluded from Google's index, so expect very low volume.**

In a measured live test the JD.com Email Scraper reached Google, parsed **10 result blocks** correctly — and extracted **zero emails** from them.

That is not a parsing failure. The blocks were read properly; the indexed pages simply did not contain a matching public address in the title, breadcrumb or snippet.

Everything below is written so you can decide with your eyes open. If you need volume today, the sibling Actors listed further down will serve you far better.

**Important:** the JD.com Email Scraper never logs into JD.com, never uses a JD.com API and never opens the site. Every record comes from publicly indexed Google search results.

***

### Why the JD.com Email Scraper Returns So Little: Google vs Baidu

The reason is straightforward and worth stating plainly rather than dressing up.

Google is not the dominant search index for Chinese retail marketplaces. **Baidu is**, and Baidu is where JD.com storefront and product pages are actually crawled, ranked and surfaced.

Google's coverage of `jd.com` is thin by comparison, so a `site:jd.com` query has very little corpus to draw on no matter how the query is phrased.

The JD.com Email Scraper is a Google-based tool by design. It queries through the Apify GOOGLE\_SERP proxy, parses Google's result blocks, and cannot reach an index it does not read.

#### Parsed blocks are not the same as extracted emails

The 10-block, zero-email result is the clearest possible illustration of the difference between reach and yield.

Reach was fine: Google answered, the structural parser found ten `<h3>` titles and their surrounding blocks, and none were mistaken for empty.

Yield was zero: JD.com's indexed pages are product and category listings, not contact pages, so the JD.com Email Scraper had no address in the snippet text to match.

#### What that means in practice

Query expansion, more keywords and higher page caps will not manufacture contact pages that Google never indexed.

So treat the JD.com Email Scraper as a **completeness tool**: cheap to run, occasionally useful for a named brand, and never the backbone of a China sourcing list.

If your goal is a working Chinese supplier email list, the honest recommendation is to use the [DHgate Email Scraper](https://apify.com/neuro-scraper/dhgate-email-scraper) or the [AliExpress Email Scraper](https://apify.com/neuro-scraper/aliexpress-email-scraper) instead — both platforms publish export-facing pages that Google indexes properly.

***

### Key Features of the JD.com Email Scraper

The table below reflects what the JD.com Email Scraper genuinely does. The engine is solid; the corpus it searches is the constraint.

| Feature | What it means in practice |
|---|---|
| Google `site:` data collection | Queries are restricted to `jd.com`, so only JD.com pages are parsed |
| Query expansion | Each keyword × domain pair is searched in several phrasings: base, quoted, `intitle:`, plus one variant per query modifier |
| Domain-filtered extraction | Only emails ending in your `customDomains` list are kept |
| Global deduplication | One email appears once across every query and every page of the run |
| Structural HTML parsing | Locates the `<h3>` title, then the smallest surrounding block — this is why 10 blocks were read cleanly in testing |
| Obfuscation-aware parser | Understands `name [at] domain [dot] com`, `name (at) domain`, `name @ domain.com`, `domain .com`, zero-width characters and the full-width `＠` |
| Junk filter | Rejects placeholders such as `email@`, `yourname@`, `test@`, `xxx@` and single-character locals |
| Boundary-correct matching | `@gmail.com` will not match inside `@gmail.company` or `@gmail.com.br` |
| Soft-wrap repair | Discards a hit that is only the tail of another email in the same result block |
| Whole-page fallback parser | If Google's markup changes, the run degrades to "emails without shop metadata" rather than "no emails" |
| Concurrency | An `asyncio` worker pool runs several queries in parallel with a shared stop signal on `maxEmails` |
| Retry logic and proxy rotation | Up to 3 attempts per page with exponential backoff and a fresh proxy session per request |
| Block detection | CAPTCHA, "unusual traffic" and consent pages are detected and retried, not silently counted as empty |
| Blocked-query requeue | Failed or blocked queries are re-queued once at the end of the run |
| Resumable state | Progress is stored in the key-value store keyed by a hash of your input, saved on `PERSIST_STATE`, `MIGRATING` and `ABORTING` |
| Streaming dataset writes | Each lead is pushed to the Apify dataset the moment it is found |
| Run summary logging | Pages fetched, blocked pages, retries and emails per page are reported at the end |

Block detection and the run summary matter more here than on most siblings. Together they let you prove the difference between "Google blocked us" and "Google had nothing useful" — and on JD.com it is reliably the second.

***

### How the JD.com Email Scraper Works: Crawler and Parser Pipeline

The pipeline is short and deliberately transparent. There is no browser, no JavaScript rendering, no authentication and no cookies.

**1. Read input.** The JD.com Email Scraper loads your keywords, optional location, email domains and limits.

**2. Build queries.** It composes ordinary Google queries with the `site:` operator, for example `site:jd.com supplier "@gmail.com"`.

**3. Fetch search result pages.** Pagination runs asynchronously with `aiohttp` through the Apify **GOOGLE\_SERP** proxy, with retry logic and a fresh proxy session on every attempt.

**4. Parse result blocks.** For each result the JD.com Email Scraper finds the `<h3>` title, walks up to the smallest enclosing block, and reads the title, the breadcrumb host and the snippet.

**5. Extract and normalise emails.** A domain-filtered regex pulls addresses out of the block text, then normalisation and the junk filter clean them up.

**6. Deduplicate and push.** Every unique email is written to the dataset immediately.

Steps 1 to 4 performed exactly as designed in live testing. Step 5 had nothing to work with, which is the whole story of this platform.

***

### What Structured Data Does the JD.com Email Scraper Extract?

The JD.com Email Scraper produces one dataset item per unique email, and every item carries the same 14 fields.

Alongside the address you get whatever account label Google printed, a `mall.jd.com` shop URL when a handle is exposed, and the snippet the email came from.

You also get full provenance: the keyword and the exact Google query that produced the lead, plus a UTC timestamp.

On JD.com that provenance is unusually valuable, because with so few results you want to know precisely which phrasing worked.

Nothing outside these 14 fields is collected. The JD.com Email Scraper does not touch orders, pricing, reviews or anything behind a login.

***

### JD.com Email Scraper Input Schema

Every field below is taken verbatim from the JD.com Email Scraper input schema.

| Field | Type | Default | Description |
|---|---|---|---|
| `keywords` | array (required) | `["supplier", "brand"]` | Search terms describing the JD.com accounts you want (niche, job title, industry) |
| `location` | string | `""` | Optional location phrase added to every query |
| `customDomains` | array | `["@gmail.com", "@yahoo.com"]` | Only emails on these domains are collected; the leading `@` is optional |
| `maxEmails` | integer (1–10000) | `20` | Stop once this many unique emails have been collected |
| `countryCode` | string | `""` | Two-letter country code for the search proxy (`US`, `GB`, `DE`…) |
| `expandQueries` | boolean | `true` | Search each keyword × domain pair with several phrasings |
| `queryModifiers` | array | `["email", "contact", "wholesale", "cooperation", "business"]` | Extra words combined with each keyword when expansion is on |
| `maxPagesPerQuery` | integer (1–50) | `30` | Page cap per query |
| `maxConcurrency` | integer (1–20) | `5` | How many queries run in parallel |

#### JSON input example

```json
{
  "keywords": ["supplier", "brand", "flagship store"],
  "location": "",
  "customDomains": ["@gmail.com", "@yahoo.com", "@outlook.com"],
  "maxEmails": 50,
  "countryCode": "US",
  "expandQueries": true,
  "queryModifiers": ["email", "contact", "wholesale", "cooperation", "business"],
  "maxPagesPerQuery": 30,
  "maxConcurrency": 5
}
```

Keep `maxEmails` modest. On this platform a high ceiling does not increase yield; it only lengthens a run that will finish nearly empty either way.

#### Why query expansion still matters

Google caps a single query at roughly 300 results, and expansion is the standard workaround across this Actor family.

On JD.com expansion is worth leaving on because the `contact`, `cooperation` and `business` modifiers are the only realistic route to a page that carries an address at all.

Because deduplication is global, expansion can only ever add rows — it never duplicates what you already have.

***

### JD.com Email Scraper Output Schema

Every dataset item produced by the JD.com Email Scraper contains all 14 fields below.

| Field | Meaning |
|---|---|
| `network` | Platform name |
| `keyword` | The keyword that produced the lead |
| `query` | The exact Google query used |
| `title` | Raw result title |
| `accountName` | Account label Google prints (handle, display name, or shop label) |
| `fullName` | Display name parsed from a profile-style title; empty for page titles that carry no name |
| `username` | URL-safe handle when the platform exposes one; otherwise `null` |
| `profileUrl` | Canonical account URL when a handle is known; otherwise empty |
| `url` | Direct platform link when exposed, else the profile URL |
| `description` | Bio or page snippet, cleaned of labels and engagement counters |
| `email` | Lower-cased email address |
| `emailDomain` | The matched domain (e.g. `@gmail.com`) |
| `possiblyTruncated` | `true` when Google's snippet ellipsis touched the email — verify before sending |
| `foundAt` | ISO 8601 UTC timestamp |

#### JSON output example — the realistic low-yield shape

The example below shows what a row looks like on the rare occasion one is produced: Google surfaced a JD.com page, exposed no shop handle, and the snippet happened to carry an address.

```json
{
  "network": "JD.com",
  "keyword": "supplier",
  "query": "site:jd.com supplier \"@gmail.com\" cooperation",
  "title": "JD Worldwide - supplier cooperation",
  "accountName": "JD.com",
  "fullName": "",
  "username": null,
  "profileUrl": "",
  "url": "",
  "description": "Supplier cooperation and wholesale enquiries: jdw.partner.export@gmail.com",
  "email": "jdw.partner.export@gmail.com",
  "emailDomain": "@gmail.com",
  "possiblyTruncated": false,
  "foundAt": "2026-08-31T09:42:17Z"
}
```

Note the `null` `username` and the empty `profileUrl`. Without a handle in Google's result there is no `mall.jd.com/index-...` URL to build, so those fields stay blank by design.

Export the JD.com Email Scraper dataset as JSON, CSV, XLSX or HTML, or pull it through the Apify API into your CRM.

***

### How to Use the JD.com Email Scraper

**Step 1 — open the Actor.** Launch the [JD.com Email Scraper](https://apify.com/leads-scraper/jd-com-email-scraper) on the Apify platform.

**Step 2 — set a small `maxEmails`.** Something like 20 to 50. There is no point paying for a long run against a thin index.

**Step 3 — use specific brand or category keywords.** A named brand you already know sells on JD.com gives you a better chance than a generic term.

**Step 4 — widen your email domains.** Add `@outlook.com`, `@hotmail.com`, `@163.com` and `@qq.com` alongside the defaults; Chinese sellers rarely use Gmail.

**Step 5 — read the run summary.** It reports pages fetched, blocked pages and emails per page, so you can distinguish "blocked" from "indexed but empty" in seconds.

A summary showing pages fetched, no blocked pages and no emails is the documented expected outcome here — not a misconfiguration.

***

### Use Cases for the JD.com Email Scraper

| Use case | How the JD.com Email Scraper helps | Realistic expectation |
|---|---|---|
| Named-brand contact lookup | Search a specific brand plus `cooperation` or `business` | Best-case scenario for this Actor |
| Cross-border sourcing research | Check whether a JD Worldwide page carries a public address | Occasional hits at best |
| Coverage completeness | Add JD.com to a multi-platform sweep so the gap is documented | Reliable, but usually returns nothing |
| Index auditing | Measure how much of `jd.com` Google actually holds for your niche | Works exactly as intended |
| CRM enrichment | Match any recovered shop label to accounts you already track | Very small volume |
| China market research | Read `description` snippets from whatever Google does surface | Thin sample |

Every row above is framed modestly on purpose. Anyone promising a large JD.com seller email list from Google search is not describing something that exists.

***

### When to Use the JD.com Email Scraper — and When to Use a Sibling

Use the JD.com Email Scraper when you specifically need JD.com, accept the volume, and want the search done properly rather than by hand.

Use a sibling when you need contactable Chinese suppliers at scale. The strongest options in this family are:

- [DHgate Email Scraper](https://apify.com/neuro-scraper/dhgate-email-scraper) — wholesale suppliers whose export pages Google indexes well.
- [AliExpress Email Scraper](https://apify.com/neuro-scraper/aliexpress-email-scraper) — cross-border sellers with international-facing storefronts.
- [Temu Email Scraper](https://apify.com/leads-scraper/temu-email-scraper) — the newer export-first marketplace from the same manufacturing base.

If your real target is Western storefronts rather than Chinese marketplaces, the footprint-based [Shopify Store Email Scraper](https://apify.com/leads-scraper/shopify-store-email-scraper) and [Wix Stores Email Scraper](https://apify.com/leads-scraper/wix-stores-email-scraper) return merchant domains at a far higher rate.

The [Tmall Email Scraper](https://apify.com/leads-scraper/tmall-email-scraper) and [Taobao Email Scraper](https://apify.com/leads-scraper/taobao-email-scraper) share the same indexing problem, since all three sit on the same side of the Great Firewall.

***

### Limitations of the JD.com Email Scraper

These are real constraints. The first one dominates everything else.

- **Very low volume by design of the index, not the Actor.** JD.com is largely excluded from Google's index. A live test parsed 10 result blocks and produced zero emails. Baidu, not Google, is where these pages are properly indexed, and the JD.com Email Scraper does not read Baidu.
- **Indexed pages are listings, not contact pages.** What Google does hold for `jd.com` is mostly product and category pages, which carry no public address to extract.
- **Only publicly indexed emails.** If an address is not visible in Google's index, it cannot be found. Private data is never accessed.
- **Google's ~300-result cap.** A single query returns roughly 300 results at most. Query expansion exists to work around this, though on JD.com the ceiling is rarely the binding constraint.
- **`possiblyTruncated`.** When Google's snippet ellipsis touches an address, this flag is set to `true`. Verify those rows before sending anything.
- **Apify GOOGLE\_SERP proxy required.** The Actor cannot run without Apify proxy credentials.
- **Free-plan cap.** Free Apify plans are limited to 100 emails per run. Paid plans are uncapped — a limit you are very unlikely to reach here.
- **`username` and `profileUrl` availability.** These are only populated when Google's result exposes a shop handle. Most JD.com rows show only a display label, leaving `username` as `null` and `profileUrl` empty. That is a Google limitation, not a bug.
- **Language and domain mismatch.** JD.com sellers overwhelmingly use Chinese mailbox providers, so the default `@gmail.com` and `@yahoo.com` filters suppress most of what little exists.
- **No guaranteed volume.** Results vary with keywords, domains and location, and on this platform the variance floor is zero.

Nothing here is affiliated with, endorsed by or officially supported by JD.com.

***

### Related Actors

| Actor | What it collects |
|---|---|
| [JD.com Email and Phone Number Scraper](https://apify.com/leads-scraper/jd-com-email-and-phone-number-scraper) | Emails and phone numbers from JD.com |
| [JD.com Phone Number Scraper](https://apify.com/leads-scraper/jd-com-phone-number-scraper) | Public phone numbers from JD.com |
| [AliExpress Email Scraper](https://apify.com/neuro-scraper/aliexpress-email-scraper) | Public contact emails from AliExpress |
| [Allegro Email Scraper](https://apify.com/neuro-scraper/allegro-email-scraper) | Public contact emails from Allegro |
| [Amazon Email Scraper](https://apify.com/leads-scraper/amazon-email-scraper) | Public contact emails from Amazon |
| [Best Buy Seller Email Scraper](https://apify.com/leads-scraper/best-buy-seller-email-scraper) | Public contact emails from Best Buy |
| [BigCommerce Store Email Scraper](https://apify.com/neuro-scraper/bigcommerce-store-email-scraper) | Public contact emails from BigCommerce Store |
| [Cdiscount Email Scraper](https://apify.com/neuro-scraper/cdiscount-email-scraper) | Public contact emails from Cdiscount |
| [Coupang Email Scraper](https://apify.com/neuro-scraper/coupang-email-scraper) | Public contact emails from Coupang |
| [Depop Email Scraper](https://apify.com/leads-scraper/depop-email-scraper) | Public contact emails from Depop |
| [DHgate Email Scraper](https://apify.com/neuro-scraper/dhgate-email-scraper) | Public contact emails from DHgate |
| [eBay Email Scraper](https://apify.com/leads-scraper/ebay-email-scraper) | Public contact emails from eBay |
| [Ecwid Store Email Scraper](https://apify.com/neuro-scraper/ecwid-store-email-scraper) | Public contact emails from Ecwid Store |
| [Etsy Email Scraper](https://apify.com/leads-scraper/etsy-email-scraper) | Public contact emails from Etsy |
| [Faire Email Scraper](https://apify.com/leads-scraper/faire-email-scraper) | Public contact emails from Faire |
| [Flipkart Email Scraper](https://apify.com/leads-scraper/flipkart-email-scraper) | Public contact emails from Flipkart |
| [Home Depot Seller Email Scraper](https://apify.com/leads-scraper/home-depot-seller-email-scraper) | Public contact emails from Home Depot |
| [Lazada Email Scraper](https://apify.com/neuro-scraper/lazada-email-scraper) | Public contact emails from Lazada |
| [Lowe's Seller Email Scraper](https://apify.com/leads-scraper/lowes-seller-email-scraper) | Public contact emails from Lowe's |
| [MercadoLibre Email Scraper](https://apify.com/neuro-scraper/mercadolibre-email-scraper) | Public contact emails from MercadoLibre |
| [Mercari Email Scraper](https://apify.com/neuro-scraper/mercari-email-scraper) | Public contact emails from Mercari |
| [Newegg Email Scraper](https://apify.com/leads-scraper/newegg-email-scraper) | Public contact emails from Newegg |
| [Otto Email Scraper](https://apify.com/leads-scraper/otto-email-scraper) | Public contact emails from Otto |
| [Overstock Email Scraper](https://apify.com/leads-scraper/overstock-email-scraper) | Public contact emails from Overstock |
| [Poshmark Email Scraper](https://apify.com/leads-scraper/poshmark-email-scraper) | Public contact emails from Poshmark |
| [Rakuten Email Scraper](https://apify.com/neuro-scraper/rakuten-email-scraper) | Public contact emails from Rakuten |
| [Shopee Email Scraper](https://apify.com/leads-scraper/shopee-email-scraper) | Public contact emails from Shopee |
| [Shopify Store Email Scraper](https://apify.com/leads-scraper/shopify-store-email-scraper) | Public contact emails from Shopify Store |
| [Taobao Email Scraper](https://apify.com/leads-scraper/taobao-email-scraper) | Public contact emails from Taobao |
| [Target Seller Email Scraper](https://apify.com/neuro-scraper/target-seller-email-scraper) | Public contact emails from Target |
| [Temu Email Scraper](https://apify.com/leads-scraper/temu-email-scraper) | Public contact emails from Temu |
| [Tmall Email Scraper](https://apify.com/leads-scraper/tmall-email-scraper) | Public contact emails from Tmall |
| [Vinted Email Scraper](https://apify.com/leads-scraper/vinted-email-scraper) | Public contact emails from Vinted |
| [Walmart Email Scraper](https://apify.com/leads-scraper/walmart-email-scraper) | Public contact emails from Walmart |
| [Wayfair Email Scraper](https://apify.com/neuro-scraper/wayfair-email-scraper) | Public contact emails from Wayfair |
| [Wish Email Scraper](https://apify.com/leads-scraper/wish-email-scraper) | Public contact emails from Wish |
| [Wix Stores Email Scraper](https://apify.com/leads-scraper/wix-stores-email-scraper) | Public contact emails from Wix Stores |
| [WooCommerce Email Scraper](https://apify.com/neuro-scraper/woocommerce-email-scraper) | Public contact emails from WooCommerce |
| [Zalando Email Scraper](https://apify.com/leads-scraper/zalando-email-scraper) | Public contact emails from Zalando |
| [AliExpress Email and Phone Number Scraper](https://apify.com/neuro-scraper/aliexpress-email-and-phone-number-scraper) | Emails and phone numbers from AliExpress |
| [Allegro Email and Phone Number Scraper](https://apify.com/neuro-scraper/allegro-email-and-phone-number-scraper) | Emails and phone numbers from Allegro |
| [Amazon Email and Phone Number Scraper](https://apify.com/leads-scraper/amazon-email-and-phone-number-scraper) | Emails and phone numbers from Amazon |

### JD.com Email Scraper Example Run

A sourcing consultant is compiling a China supplier map and wants JD.com represented rather than silently skipped.

They run the JD.com Email Scraper with `keywords: ["supplier", "brand"]`, `customDomains: ["@gmail.com", "@outlook.com"]` and `maxEmails: 30`, expecting little.

The run finishes quickly. The summary logs ten pages fetched, no blocked pages and no emails — proof that Google was reached and the indexed pages simply carried no addresses.

They record the gap in their notes, then re-run the same keywords through the [DHgate Email Scraper](https://apify.com/neuro-scraper/dhgate-email-scraper), which is where the usable supplier contacts actually come from.

***

### JD.com Email Scraper FAQ

#### How many results should I expect from the JD.com Email Scraper?

Very few, and quite possibly none. In a measured live test it parsed 10 result blocks and produced zero emails. Plan for that outcome and do not build a campaign around this Actor.

#### Why is the yield so low — is something broken?

No. JD.com is largely excluded from Google's index. Baidu is the dominant search engine for Chinese marketplaces and is where these pages are properly crawled. The JD.com Email Scraper reads Google only.

#### Ten blocks but no emails — is that a parser bug?

No, and the distinction matters. The parser located all ten blocks correctly. The blocks were product and listing pages that contained no public address in their snippet text, so there was nothing to extract.

#### Will more keywords or more pages fix it?

No. Expansion widens the search over the same thin corpus. It is worth leaving on, but it cannot create index coverage that does not exist.

#### Which sibling should I use instead?

For Chinese suppliers, the DHgate, AliExpress and Temu Actors. For Western storefronts, the footprint-based Shopify, Wix and Squarespace Actors return merchant domains at a far higher rate.

#### Does the JD.com Email Scraper log into JD.com?

No. It never logs in, never uses a JD.com API and never opens the site. All data comes from publicly indexed Google search results.

#### Why are `username` and `profileUrl` usually empty?

Because Google rarely exposes a JD.com shop handle in its result blocks. Without a handle there is no `mall.jd.com` URL to build, so `username` stays `null` and `profileUrl` stays empty.

#### Should I change the email domains?

Yes. JD.com sellers overwhelmingly use Chinese providers, so adding domains such as `@163.com` and `@qq.com` gives the JD.com Email Scraper more to match against than Gmail alone.

#### Do I need an Apify proxy?

Yes. The JD.com Email Scraper requires the Apify GOOGLE\_SERP proxy and cannot run without Apify proxy credentials.

#### How many emails can it collect per run?

Free Apify plans are capped at 100 emails per run and paid plans are uncapped — but on this platform the index, not the plan, is your ceiling.

#### What does `possiblyTruncated: true` mean?

Google's snippet ellipsis touched the email, so the address may be cut off. Verify those rows before sending.

#### Is this affiliated with JD.com?

No. The JD.com Email Scraper is an independent tool and is not affiliated with, endorsed by or officially supported by JD.com.

***

### Responsible Use and GDPR

Publicly visible does not mean consent to bulk marketing. Treat every address the JD.com Email Scraper returns as personal data belonging to a real business contact.

Follow GDPR, CAN-SPAM, PIPL and any other regime that applies to you: identify yourself, state why you are contacting them, honour opt-outs immediately and delete records on request.

With volumes this low, individual, well-researched outreach is the only sensible approach anyway.

***

### Leave a review

If the JD.com Email Scraper saved you time, please leave a star rating and a short review on
the Actor page.

Reviews are how other buyers judge whether a tool works, and they tell us which features to
build next.

If something did not work, email <neurodata.apify@gmail.com>
instead - bugs get fixed faster than they get complained about.

### Support

Questions, bug reports or a custom build request? Email **neurodata.apify@gmail.com** and include your run ID so the JD.com Email Scraper logs can be checked quickly.

# Actor input Schema

## `keywords` (type: `array`):

Search terms describing the JD.com accounts you want (niche, job title, industry).

## `location` (type: `string`):

Optional location phrase added to every query (e.g. "New York").

## `customDomains` (type: `array`):

Only emails ending with one of these domains are collected. With or without the leading @. Each domain is searched separately, so more domains means more results but a longer run - remove some for a faster, narrower search, or add your own (e.g. @company.com).

## `maxEmails` (type: `integer`):

Stop once this many unique emails have been collected.

## `countryCode` (type: `string`):

Two-letter country code for the search proxy (e.g. US, GB, DE). Empty for any.

## `expandQueries` (type: `boolean`):

Search each keyword x domain pair with several phrasings. Recommended - Google caps a single query at ~300 results.

## `queryModifiers` (type: `array`):

Extra words combined with each keyword when Expand queries is on. Tuned for JD.com.

## `maxPagesPerQuery` (type: `integer`):

Google rarely returns more than ~30 pages for one query.

## `maxConcurrency` (type: `integer`):

How many queries run in parallel.

## Actor input object example

```json
{
  "keywords": [
    "supplier",
    "brand"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com",
    "@yahoo.com"
  ],
  "maxEmails": 20,
  "countryCode": "",
  "expandQueries": true,
  "queryModifiers": [
    "email",
    "contact",
    "wholesale",
    "cooperation",
    "business"
  ],
  "maxPagesPerQuery": 30,
  "maxConcurrency": 5
}
```

# Actor output Schema

## `results` (type: `string`):

Records produced by JD.com Email Scraper, stored in the run's default dataset.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "supplier",
        "brand"
    ],
    "location": "",
    "customDomains": [
        "@gmail.com",
        "@yahoo.com"
    ],
    "countryCode": "",
    "queryModifiers": [
        "email",
        "contact",
        "wholesale",
        "cooperation",
        "business"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("leads-scraper/jd-com-email-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": [
        "supplier",
        "brand",
    ],
    "location": "",
    "customDomains": [
        "@gmail.com",
        "@yahoo.com",
    ],
    "countryCode": "",
    "queryModifiers": [
        "email",
        "contact",
        "wholesale",
        "cooperation",
        "business",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("leads-scraper/jd-com-email-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "keywords": [
    "supplier",
    "brand"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com",
    "@yahoo.com"
  ],
  "countryCode": "",
  "queryModifiers": [
    "email",
    "contact",
    "wholesale",
    "cooperation",
    "business"
  ]
}' |
apify call leads-scraper/jd-com-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,leads-scraper/jd-com-email-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/bDqce8G7kv9NK7e6r/builds/pkWLvX7x4aS3OrlFu/openapi.json