# Kaggle Email Scraper (`neuro-scraper/kaggle-email-scraper`) Actor Kaggle Email Scraper SD - Kaggle Email Scraper is a lead generation tool that extracts leads with public contact emails, account names and profile URLs from Kaggle results by keyword, location and email domain - Kaggle email extractor. - **URL**: https://apify.com/neuro-scraper/kaggle-email-scraper.md - **Developed by:** [Neuro Scraper](https://apify.com/neuro-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 ### Kaggle Email Scraper - extract public data scientist and ML practitioner emails from Kaggle The **Kaggle Email Scraper** collects publicly indexed contact emails from Kaggle: data scientists, machine learning engineers, notebook authors, dataset publishers and competition participants who left an address in public text. You supply keywords, an optional location and a list of email domains. The Kaggle Email Scraper builds domain-scoped Google queries against `kaggle.com`, parses each result block and writes every matching address into a structured dataset. There is no login, no Kaggle API, no headless browser and no cookies. This Kaggle email extractor reads only what Google has already indexed publicly. One honest caveat up front. Kaggle yields less cleanly than creator platforms, because a large share of indexed `kaggle.com` pages are datasets, competitions and notebooks rather than user profiles, so a fair proportion of rows arrive with an email but no `username` and no profile URL. That is worth knowing before you plan a run. The addresses are still real and usable; you simply get fewer rows where a handle and a `kaggle.com` profile URL come attached. Technical recruiters, ML tooling vendors, developer-relations teams, bootcamps and research groups use the Kaggle Email Scraper for contact discovery across the data science community. *** ### Features of the Kaggle Email Scraper Everything below is implemented in the Kaggle Email Scraper today. No roadmap items, no aspirational claims. | Feature | What it means in practice | |---|---| | Google `site:` search automation | Every query is scoped to `kaggle.com`, so results stay on-platform | | Query expansion | Base, quoted and `intitle:` variants plus one variant per query modifier | | Recruiting-tuned modifiers | Defaults are `email`, `contact`, `inquiries`, `hire`, `work with me` | | Domain-filtered extraction | Only emails on your `customDomains` list are kept | | Global deduplication | Each unique address reaches the dataset exactly once across all queries and pages | | Obfuscation-aware parser | Understands `name [at] domain [dot] com`, `name (at) domain`, `name @ domain.com`, `domain .com` | | Unicode normalisation | Handles zero-width characters and the full-width at sign | | 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 | | Concurrency control | An `asyncio` worker pool runs queries in parallel with a shared stop signal on `maxEmails` | | Retry logic | 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, never scored as empty | | Re-queue pass | Blocked or failed queries are retried once more at the end of the run | | Resumable state | Progress persists in the key-value store, keyed by a hash of your input | | Structural parsing | Result blocks are located via the `

` title, not by Google's CSS class names | | Fallback parser | A Google markup change degrades to "emails without account details", not "no emails" | | Streaming dataset writes | Leads appear in the dataset immediately, so exports can begin mid-run | *** ### How the Kaggle Email Scraper works The Kaggle Email Scraper is a search-results crawler. It never opens kaggle.com, never downloads a dataset and never executes a notebook. **1. Read input.** Keywords, location, email domains, page caps and concurrency are validated first. **2. Build queries.** Queries use the `site:` operator, for example: `site:kaggle.com machine learning engineer "@gmail.com" "Bangalore"`. **3. Expand queries.** With `expandQueries` on, each keyword and domain pair is issued as a base query, a quoted variant, an `intitle:` variant and one variant per entry in `queryModifiers`. Base queries always run first. **4. Fetch pages.** The Kaggle Email Scraper fetches result pages asynchronously with `aiohttp` through the Apify GOOGLE_SERP proxy, paginating up to `maxPagesPerQuery`. **5. Parse result blocks.** The parser locates the `

` title, then the smallest surrounding block, so titles, snippets and site labels stay attached to the correct record. **6. Extract and normalise.** A domain-filtered regex pulls candidates from the block text, normalises them, and removes junk, tails and boundary mismatches. **7. Deduplicate and store.** Every new address is deduplicated globally and pushed straight into the Apify dataset as structured data. The Kaggle Email Scraper run summary logs pages fetched, blocked pages, retries and emails per page, which is especially useful here for comparing profile-shaped keywords against notebook-shaped ones. *** ### What data does the Kaggle Email Scraper extract? Each row is one email paired with whatever metadata Google exposed alongside it. You get the address, the matched domain, the account or page label, a parsed name where the title looks like a profile, a handle and profile URL where Kaggle exposes one, a cleaned snippet and full provenance. Provenance matters. The `keyword` and `query` fields tell you which phrasing surfaced this record, which is how you steer the next Kaggle Email Scraper run toward profile pages rather than dataset pages. When a handle is available the Kaggle Email Scraper rebuilds `profileUrl` as `https://www.kaggle.com/`. When Google returns a dataset, competition or notebook page instead, `username` will be `null` and `profileUrl` empty. *** ### Input schema for the Kaggle Email Scraper Every Kaggle Email Scraper input field is listed below with the exact name, type and default from the Actor input schema. | Field | Type | Default | Description | |---|---|---|---| | `keywords` | array (required) | `["data scientist", "machine learning"]` | Search terms describing the Kaggle accounts you want (niche, job title, industry) | | `location` | string | `""` | Optional location phrase added to every query, e.g. `"New York"` | | `customDomains` | array | `["@gmail.com", "@yahoo.com"]` | Only emails ending with one of these domains are collected; leading `@` 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). Empty for any | | `expandQueries` | boolean | `true` | Search each keyword and domain pair with several phrasings | | `queryModifiers` | array | `["email", "contact", "inquiries", "hire", "work with me"]` | 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 | #### Input example ```json { "keywords": ["data scientist", "machine learning engineer", "computer vision"], "location": "", "customDomains": ["@gmail.com", "@outlook.com"], "maxEmails": 300, "countryCode": "US", "expandQueries": true, "queryModifiers": ["email", "contact", "inquiries", "hire", "work with me"], "maxPagesPerQuery": 30, "maxConcurrency": 5 } ``` *** ### Output schema of the Kaggle Email Scraper Every dataset item the Kaggle Email Scraper produces carries all fourteen 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 page label) | | `fullName` | Display name parsed from a profile-style title; empty for dataset and notebook titles | | `username` | URL-safe handle when Kaggle exposes one; otherwise `null` | | `profileUrl` | Canonical account URL when a handle is known; otherwise empty | | `url` | Direct Kaggle 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 | #### Output example ```json { "network": "Kaggle", "keyword": "computer vision", "query": "site:kaggle.com computer vision \"@gmail.com\" contact", "title": "Ravi Deshmukh | Notebooks Expert | Kaggle", "accountName": "ravideshmukh", "fullName": "Ravi Deshmukh", "username": "ravideshmukh", "profileUrl": "https://www.kaggle.com/ravideshmukh", "url": "https://www.kaggle.com/ravideshmukh", "description": "Computer vision and medical imaging. Open to consulting and research collaborations. Contact: ravi.deshmukh.ml@gmail.com", "email": "ravi.deshmukh.ml@gmail.com", "emailDomain": "@gmail.com", "possiblyTruncated": false, "foundAt": "2026-08-31T14:12:09.348Z" } ``` The Kaggle Email Scraper dataset exports as JSON, CSV, Excel or XML from the Apify console, or streams through the Apify API into your ATS, CRM or outreach tool. *** ### How to use the Kaggle Email Scraper **Step 1 - bias your keywords toward people, not projects.** Terms like `data scientist`, `machine learning engineer`, `NLP researcher` or `Kaggle Master` bring back more profile pages; terms like `titanic dataset` bring back competition pages with no owner attached. **Step 2 - pick sensible email domains.** `@gmail.com` dominates among individual practitioners. Add academic or corporate domains if you are targeting a specific institution. **Step 3 - start small.** Run the Kaggle Email Scraper with `maxEmails` at 20 to 50 first, then inspect how many rows came back with a populated `username`. **Step 4 - keep the recruiting-tuned modifiers.** `hire`, `contact`, `inquiries` and `work with me` match the phrasing people use when they are open to work. **Step 5 - add `location` for geography-bound hiring.** Practitioners sometimes state a city or country, but many do not, so expect location filtering to reduce volume noticeably. **Step 6 - clean before you send.** Filter out rows where `possiblyTruncated` is `true`, split rows with and without a `username`, then run the remaining Kaggle Email Scraper results through email verification. *** ### Use cases for the Kaggle Email Scraper | Use case | Who runs it | Typical keywords | |---|---|---| | Data science and ML recruiting | Technical recruiters and in-house sourcers | `data scientist`, `machine learning engineer`, `kaggle master` | | Developer tools and MLOps prospecting | Founders and sales teams at ML vendors | `deep learning`, `pytorch`, `feature engineering` | | Developer relations and community building | DevRel and community managers | `notebook`, `tutorial`, `open source` | | Research collaboration outreach | Labs, universities and research groups | `nlp researcher`, `computer vision`, `time series` | | Bootcamp and course enrolment | Education providers and training platforms | `beginner`, `learning data science`, `portfolio` | | Freelance and contract data work | Agencies and consultancies | `freelance data scientist`, `analytics consultant` | | Conference and hackathon recruiting | Event organisers and sponsors | `competition`, `hackathon`, `benchmark` | | Talent-market research | Analysts studying the ML labour market | any role keyword, varied by `location` | Kaggle is a demonstrated-skill community rather than a resume site, which is why sourcers value it, and why the Kaggle Email Scraper is best used as one input among several rather than a standalone list. For academic contacts the [ResearchGate Email Scraper](https://apify.com/neuro-scraper/researchgate-email-scraper) and the [Academia.edu Email Scraper](https://apify.com/neuro-scraper/academia-edu-email-scraper) are usually richer, and practitioners who publish courses often appear in the **Coursera Email Scraper** or the [Pluralsight Email Scraper](https://apify.com/leads-scraper/pluralsight-email-scraper). *** ### Why choose this Kaggle Email Scraper Manual sourcing on Kaggle means paging through leaderboards, opening profiles, reading bios and copying addresses. The Kaggle Email Scraper automates that loop and returns a deduplicated dataset. Every row is auditable. The `query` and `keyword` fields show exactly how a lead was found, which matters more here than elsewhere because it lets you separate profile-shaped queries from dataset-shaped ones. The extraction layer is deliberately conservative. Junk filtering, boundary-correct domain matching and soft-wrap repair mean far fewer garbage rows to clean downstream. Long Kaggle Email Scraper runs survive interruption. State persists in the key-value store and saves fire on Apify's `PERSIST_STATE`, `MIGRATING` and `ABORTING` events. *** ### Worked example: a computer vision hiring pipeline You are hiring three computer vision engineers and want a top-of-funnel list of 300 practitioners. Set `keywords` to `["computer vision", "image segmentation", "kaggle master"]`, `customDomains` to `["@gmail.com"]`, `countryCode` to `"US"` and `maxEmails` to `300`, leaving `expandQueries` on. The Kaggle Email Scraper issues base, quoted and `intitle:` variants plus one query per modifier, paginating each independently and streaming leads as they are found. Export the Kaggle Email Scraper dataset to CSV, drop `possiblyTruncated` rows, then sort by whether `username` is populated so your sourcers work the identifiable profiles first. *** ### Limitations you should know before running The Kaggle Email Scraper is deliberately transparent about its boundaries. Read these before planning a large data collection run. **Weaker identity resolution than creator platforms.** Many indexed `kaggle.com` pages are datasets, competitions and notebooks rather than user profiles, so a fair share of Kaggle Email Scraper rows carry an email with no handle attached. **Only publicly indexed emails.** The Kaggle Email Scraper returns addresses that already appear in Google's index. Practitioners who never published an address will not surface. **Google's per-query ceiling.** A single query caps out at roughly 300 results. Query expansion exists to work around that ceiling, which is why it defaults to on. **`possiblyTruncated`.** When Google's snippet ellipsis touches an address, this field is `true` and the email may be incomplete. Verify those rows before sending. **Apify GOOGLE_SERP proxy required.** The Kaggle Email Scraper cannot run without Apify proxy credentials that include the GOOGLE_SERP group. **Free-plan cap.** Running the Kaggle Email Scraper on a free Apify plan limits results to 100 emails per run. Paid plans are uncapped. **Handle availability.** `username` and `profileUrl` are populated only when Google's result exposes a Kaggle handle. Rows without one still carry `accountName` and, sometimes, `fullName`. This is a Google limitation, not a bug. **No guaranteed volume.** Kaggle Email Scraper yield varies with keywords, domains and location. No result count is promised. The Kaggle Email Scraper is not affiliated with, endorsed by or officially supported by Kaggle. *** ### Related Actors Every Actor below runs the same engine as the Kaggle Email Scraper, with identical input fields and an identical output schema; only the target platform differs. | Actor | What it collects | |---|---| | [Kaggle Email and Phone Number Scraper](https://apify.com/neuro-scraper/kaggle-email-and-phone-number-scraper) | Emails and phone numbers from Kaggle | | [Kaggle Phone Number Scraper](https://apify.com/neuro-scraper/kaggle-phone-number-scraper) | Public phone numbers from Kaggle | | [Academia.edu Email Scraper](https://apify.com/neuro-scraper/academia-edu-email-scraper) | Public contact emails from Academia.edu | | [Buy Me a Coffee Email Scraper](https://apify.com/neuro-scraper/buy-me-a-coffee-email-scraper) | Public contact emails from Buy Me a Coffee | | [Carrd Email Scraper](https://apify.com/neuro-scraper/carrd-email-scraper) | Public contact emails from Carrd | | [Domestika Email Scraper](https://apify.com/neuro-scraper/domestika-email-scraper) | Public contact emails from Domestika | | [edX Email Scraper](https://apify.com/leads-scraper/edx-email-scraper) | Public contact emails from edX | | [Gumroad Email Scraper](https://apify.com/leads-scraper/gumroad-email-scraper) | Public contact emails from Gumroad | | [Kajabi Email Scraper](https://apify.com/neuro-scraper/kajabi-email-scraper) | Public contact emails from Kajabi | | [Ko-fi Email Scraper](https://apify.com/neuro-scraper/ko-fi-email-scraper) | Public contact emails from Ko-fi | | [Linktree Email Scraper](https://apify.com/leads-scraper/linktree-email-scraper) | Public contact emails from Linktree | | [MasterClass Email Scraper](https://apify.com/neuro-scraper/masterclass-email-scraper) | Public contact emails from MasterClass | | [Meetup Email Scraper](https://apify.com/leads-scraper/meetup-email-scraper) | Public contact emails from Meetup | | [Pluralsight Email Scraper](https://apify.com/leads-scraper/pluralsight-email-scraper) | Public contact emails from Pluralsight | | [Preply Email Scraper](https://apify.com/neuro-scraper/preply-email-scraper) | Public contact emails from Preply | | [ResearchGate Email Scraper](https://apify.com/neuro-scraper/researchgate-email-scraper) | Public contact emails from ResearchGate | | [Skillshare Email Scraper](https://apify.com/neuro-scraper/skillshare-email-scraper) | Public contact emails from Skillshare | | [Teachable Email Scraper](https://apify.com/neuro-scraper/teachable-email-scraper) | Public contact emails from Teachable | | [Udemy Email Scraper](https://apify.com/leads-scraper/udemy-email-scraper) | Public contact emails from Udemy | | [Academia.edu Email and Phone Number Scraper](https://apify.com/neuro-scraper/academia-edu-email-and-phone-number-scraper) | Emails and phone numbers from Academia.edu | | [Buy Me a Coffee Email and Phone Number Scraper](https://apify.com/neuro-scraper/buy-me-a-coffee-email-and-phone-number-scraper) | Emails and phone numbers from Buy Me a Coffee | | [Carrd Email and Phone Number Scraper](https://apify.com/neuro-scraper/carrd-email-and-phone-number-scraper) | Emails and phone numbers from Carrd | | [Domestika Email and Phone Number Scraper](https://apify.com/neuro-scraper/domestika-email-and-phone-number-scraper) | Emails and phone numbers from Domestika | | [edX Email and Phone Number Scraper](https://apify.com/neuro-scraper/edx-email-and-phone-number-scraper) | Emails and phone numbers from edX | | [Gumroad Email and Phone Number Scraper](https://apify.com/leads-scraper/gumroad-email-and-phone-number-scraper) | Emails and phone numbers from Gumroad | | [Kajabi Email and Phone Number Scraper](https://apify.com/neuro-scraper/kajabi-email-and-phone-number-scraper) | Emails and phone numbers from Kajabi | | [Ko-fi Email and Phone Number Scraper](https://apify.com/neuro-scraper/ko-fi-email-and-phone-number-scraper) | Emails and phone numbers from Ko-fi | | [Linktree Email and Phone Number Scraper](https://apify.com/leads-scraper/linktree-email-and-phone-number-scraper) | Emails and phone numbers from Linktree | | [MasterClass Email and Phone Number Scraper](https://apify.com/neuro-scraper/masterclass-email-and-phone-number-scraper) | Emails and phone numbers from MasterClass | | [Meetup Email and Phone Number Scraper](https://apify.com/neuro-scraper/meetup-email-and-phone-number-scraper) | Emails and phone numbers from Meetup | | [Pluralsight Email and Phone Number Scraper](https://apify.com/neuro-scraper/pluralsight-email-and-phone-number-scraper) | Emails and phone numbers from Pluralsight | | [Preply Email and Phone Number Scraper](https://apify.com/neuro-scraper/preply-email-and-phone-number-scraper) | Emails and phone numbers from Preply | | [ResearchGate Email and Phone Number Scraper](https://apify.com/neuro-scraper/researchgate-email-and-phone-number-scraper) | Emails and phone numbers from ResearchGate | | [Skillshare Email and Phone Number Scraper](https://apify.com/neuro-scraper/skillshare-email-and-phone-number-scraper) | Emails and phone numbers from Skillshare | | [Teachable Email and Phone Number Scraper](https://apify.com/neuro-scraper/teachable-email-and-phone-number-scraper) | Emails and phone numbers from Teachable | | [Academia.edu Phone Number Scraper](https://apify.com/neuro-scraper/academia-edu-phone-number-scraper) | Public phone numbers from Academia.edu | | [Buy Me a Coffee Phone Number Scraper](https://apify.com/neuro-scraper/buy-me-a-coffee-phone-number-scraper) | Public phone numbers from Buy Me a Coffee | | [Carrd Phone Number Scraper](https://apify.com/neuro-scraper/carrd-phone-number-scraper) | Public phone numbers from Carrd | | [Domestika Phone Number Scraper](https://apify.com/neuro-scraper/domestika-phone-number-scraper) | Public phone numbers from Domestika | | [edX Phone Number Scraper](https://apify.com/neuro-scraper/edx-phone-number-scraper) | Public phone numbers from edX | | [Gumroad Phone Number Scraper](https://apify.com/leads-scraper/gumroad-phone-number-scraper) | Public phone numbers from Gumroad | | [Kajabi Phone Number Scraper](https://apify.com/neuro-scraper/kajabi-phone-number-scraper) | Public phone numbers from Kajabi | ### FAQ about the Kaggle Email Scraper #### What is the Kaggle Email Scraper? It is an Apify Actor that extracts publicly indexed contact emails from Kaggle by running domain-scoped Google searches and parsing the resulting search-result blocks. #### Does the Kaggle Email Scraper log into Kaggle or use its API? No. It never logs in, never calls a Kaggle API and never opens a browser, so there are no cookies and no authentication anywhere in the pipeline. #### Why do so many rows have no `username`? Because much of Kaggle's indexed surface is datasets, competitions and notebooks rather than profiles. Those pages have no handle for the Kaggle Email Scraper to resolve, so `username` is `null` and `profileUrl` is empty. #### Can I improve the share of rows with a handle? Often, yes. Role-shaped keywords such as `data scientist`, `machine learning engineer` or `kaggle master` return more profile pages than dataset-shaped keywords. #### Where do the emails actually come from? From publicly indexed titles, snippets and site labels, typically bios and descriptions where someone published an address themselves. #### What does `possiblyTruncated: true` mean? Google's snippet ellipsis touched the address, so it may be cut off. Verify those rows before contacting anyone. #### How many emails will one run of the Kaggle Email Scraper return? `maxEmails` accepts 1 to 10000, but free Apify plans are capped at 100 emails per run and paid plans are uncapped. Real volume depends on keywords, domains and location. #### Is a proxy required? Yes. The Kaggle Email Scraper requires the Apify GOOGLE_SERP proxy and cannot run without Apify proxy credentials. #### Should I leave `expandQueries` on? Almost always. Google returns roughly 300 results per query, and expansion multiplies your reachable surface through base, quoted, `intitle:` and modifier variants. #### Can I target a specific country? Yes. Set `countryCode` for the search proxy and optionally add a `location` phrase, keeping in mind that many practitioners never state a city. #### What happens if my run is interrupted or migrated? State persists in the key-value store keyed by a hash of your input, with throttled saves plus saves on `PERSIST_STATE`, `MIGRATING` and `ABORTING`, so an interrupted run resumes instead of restarting. #### Can I email everyone in the dataset immediately? Treat the Kaggle Email Scraper output as raw lead data. Deduplication is automatic, but verification, consent and compliance with GDPR, CAN-SPAM and Kaggle's terms remain your responsibility. *** ### Leave a review If the Kaggle 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 instead - bugs get fixed faster than they get complained about. ### Support Questions about the Kaggle Email Scraper, bug reports or a custom build? Email **neurodata.apify@gmail.com**. # Actor input Schema ## `keywords` (type: `array`): Search terms describing the Kaggle 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 Kaggle. ## `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": [ "data scientist", "machine learning" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "maxEmails": 20, "countryCode": "", "expandQueries": true, "queryModifiers": [ "email", "contact", "inquiries", "hire", "work with me" ], "maxPagesPerQuery": 30, "maxConcurrency": 5 } ``` # Actor output Schema ## `results` (type: `string`): Records produced by Kaggle 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "data scientist", "machine learning" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "countryCode": "", "queryModifiers": [ "email", "contact", "inquiries", "hire", "work with me" ] }; // Run the Actor and wait for it to finish const run = await client.actor("neuro-scraper/kaggle-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "data scientist", "machine learning", ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com", ], "countryCode": "", "queryModifiers": [ "email", "contact", "inquiries", "hire", "work with me", ], } # Run the Actor and wait for it to finish run = client.actor("neuro-scraper/kaggle-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": [ "data scientist", "machine learning" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "countryCode": "", "queryModifiers": [ "email", "contact", "inquiries", "hire", "work with me" ] }' | apify call neuro-scraper/kaggle-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuro-scraper/kaggle-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 ` 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/y8O5JHGeOVGruOotJ/builds/Rpl72PyCmbUyrl5XF/openapi.json