# Gelbeseiten Email Scraper (`email_scraper/gelbeseiten-email-scraper`) Actor

Gelbeseiten Email Scraper extracts publicly indexed email addresses from Gelbeseiten using targeted keywords, location filters, custom email domains, and exclusion terms. Build structured contact datasets with titles, descriptions, URLs, and emails for business research and lead generation.

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

## Pricing

from $1.49 / 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

### Gelbeseiten Email Scraper

The **Gelbeseiten Email Scraper** extracts publicly indexed email addresses associated with Gelbeseiten.de search results using targeted keywords, optional location filters, and configurable email domains. It is designed for users who need structured contact data from relevant Gelbeseiten listings for business research, lead research, contact discovery, and dataset creation.

Provide one or more search keywords, optionally specify a country, state, or city, select the email domains you want to find, and optionally exclude descriptions containing specific words or phrases. The Actor returns structured records containing the keyword, result title, description, URL, and extracted email address.

The Actor processes multiple keyword and email-domain combinations independently, while avoiding duplicate email addresses across the overall run. Results are added to the Apify dataset as they are collected.

> 🔍 **Search-focused extraction:** Results are collected from publicly indexed Gelbeseiten search information. An email address must be present in the indexed result description for it to be extracted.

### What Is the Gelbeseiten Email Scraper?

The **Gelbeseiten Email Scraper** is an email extraction and contact research tool for Gelbeseiten.de. Instead of manually searching business listings and checking individual results for contact information, you can define search terms and let the Actor process the corresponding search combinations automatically.

The Actor is particularly useful when your research starts with a business category, profession, service, or other descriptive keyword. For example, you can search using terms such as `Unternehmen`, `Restaurant`, `Immobilienmakler`, `Zahnarzt`, or other relevant phrases.

You can also combine multiple keywords with multiple email domains. This allows you to create targeted searches such as:

- `Restaurant` + `@gmail.com`
- `Restaurant` + `@outlook.com`
- `Immobilienmakler` + `@gmail.com`
- `Zahnarzt` + `@yahoo.com`

An optional location can further narrow the search.

### Key Features

| Feature                      | Description                                                        | User Benefit                                        |
| ---------------------------- | ------------------------------------------------------------------ | --------------------------------------------------- |
| Keyword-based search         | Search Gelbeseiten using one or more keywords or queries           | Target specific business or professional categories |
| Location filtering           | Optionally add a country, state, or city                           | Focus research on a geographic area                 |
| Custom email domains         | Specify email suffixes such as `@gmail.com` or `@yahoo.com`        | Target the types of email addresses you need        |
| Per-combination limits       | Set a maximum email target for each keyword and domain combination | Control the depth of each search                    |
| Exclude words                | Skip descriptions containing selected words or phrases             | Remove unwanted results from collection             |
| Duplicate prevention         | Previously collected email addresses are not added again           | Keep the dataset cleaner                            |
| Structured dataset           | Results are pushed into an Apify dataset                           | Make collected data easier to review and process    |
| Multiple search combinations | Process multiple keywords and domains during one run               | Expand research coverage systematically             |

### What Data Can You Extract?

Each collected record contains five user-facing fields:

- **keyword** — The keyword associated with the search that produced the result.
- **title** — The title of the indexed Gelbeseiten result.
- **description** — The description or search-result snippet associated with the result.
- **url** — The URL associated with the indexed result.
- **email** — The email address extracted from the available description text and matching the configured email domain.

The Actor does not return a separate profile schema containing additional fields such as phone numbers, ratings, addresses, categories, or social profiles. The documented output is focused on email-oriented contact research.

> 📊 **Structured output:** Every collected email is associated with the search keyword, result title, description, and URL that provided the contact context.

### Why Use This Actor?

Manual contact research can require repeatedly entering searches, reviewing results, identifying email addresses, and organizing the information into a usable dataset. The Gelbeseiten Email Scraper turns that repetitive search workflow into a configurable Apify Actor.

It is useful when your research requires:

- Multiple search keywords
- Multiple email-domain patterns
- Optional geographic targeting
- Exclusion of unwanted descriptions
- Structured email results
- Duplicate-aware collection
- A reusable Apify dataset

Because the Actor works with search-indexed information, it is especially suitable for discovery workflows where the goal is to identify publicly indexed email addresses connected with relevant Gelbeseiten results.

### Benefits

The main practical benefits include:

- **Automation:** Reduce repetitive manual searching for publicly indexed contact information.
- **Targeted discovery:** Use specific keywords rather than relying on a single broad search.
- **Geographic targeting:** Add a location when your research needs regional results.
- **Domain targeting:** Search for specific email domain suffixes.
- **Filtering:** Exclude descriptions containing words or phrases that do not match your research.
- **Structured data:** Receive consistent fields in the Apify dataset.
- **Duplicate reduction:** The Actor tracks previously collected email addresses so the same email is not repeatedly added.
- **Flexible research:** Combine different keywords and domain suffixes for broader or more focused collection.

### How to Use the Gelbeseiten Email Scraper

The basic workflow is straightforward:

1. Enter one or more keywords in the `keywords` field.
2. Optionally enter a country, state, or city in `location`.
3. Add the email domains you want to search for in `customDomains`.
4. Set `maxEmails` according to the desired collection target.
5. Optionally add words or phrases to `excludeWords`.
6. Start the Actor.
7. Review the resulting records in the Apify dataset.

For better targeting, use several specific search terms instead of relying on one very broad keyword. For example, a business research project could use `Restaurant`, `Café`, `Italian Restaurant`, and `Restaurant Betreiber` as separate search terms.

### Input

The Actor requires the `keywords` field. All other documented fields are optional.

| Field           | Type             | Required | Default                         | Description                                                                |
| --------------- | ---------------- | -------- | ------------------------------- | -------------------------------------------------------------------------- |
| `keywords`      | Array of strings | Yes      | `["Unternehmen", "Restaurant"]` | Keywords or queries used to search Gelbeseiten                             |
| `location`      | String           | No       | `""`                            | Optional country, state, or city used to narrow searches                   |
| `customDomains` | Array of strings | No       | `["@gmail.com"]`                | Email domain suffixes to search for                                        |
| `maxEmails`     | Integer          | No       | `5`                             | Maximum target per keyword + domain combination; allowed range is 1–10,000 |
| `excludeWords`  | Array of strings | No       | `[]`                            | Words or phrases that cause a result description to be skipped             |

The `keywords` field accepts multiple values. The `customDomains` field also accepts multiple email suffixes.

`location` can be left empty when geographic filtering is not required.

The `maxEmails` value applies independently to each keyword and email-domain combination. For example, two keywords and three domains create six combinations, each with its own configured target. Because duplicate email addresses are tracked globally, the final number of unique records can still be lower than the theoretical combined target.

> ⚙️ **Limit range:** `maxEmails` accepts values from `1` through `10000`. Lower targets are useful for smaller test runs, while larger targets can increase search depth where enough indexed results are available.

### Input Example

```json
{
  "keywords": [
    "Restaurant",
    "Immobilienmakler",
    "Zahnarzt"
  ],
  "location": "Berlin",
  "customDomains": [
    "@gmail.com",
    "@yahoo.com",
    "@outlook.com"
  ],
  "maxEmails": 20,
  "excludeWords": [
    "crypto",
    "onlyfans"
  ]
}
```

### Output

The Actor writes collected records to the **Gelbeseiten Emails Dataset**. The public dataset view contains the following fields:

| Field         | Description                                                                   |
| ------------- | ----------------------------------------------------------------------------- |
| `keyword`     | Search keyword responsible for the result                                     |
| `title`       | Title of the indexed search result                                            |
| `description` | Search-result description or snippet containing the relevant context          |
| `url`         | URL associated with the indexed result                                        |
| `email`       | Email address extracted from the description and matching the selected domain |

The email is extracted from the available indexed description text. Consequently, a matching email must be present in the search information available to the Actor.

> 📤 **Output format:** Results are stored as structured Apify dataset records with keyword, title, description, URL, and email fields.

### Output Example

```json
{
  "keyword": "Restaurant",
  "title": "Example Restaurant Berlin",
  "description": "Example Restaurant in Berlin. Contact: example@gmail.com",
  "url": "https://www.gelbeseiten.de/...",
  "email": "example@gmail.com"
}
```

The example above is illustrative. Actual titles, descriptions, URLs, and email addresses depend on the publicly indexed search results available for your selected inputs.

### Use Cases

The Gelbeseiten Email Scraper can support several legitimate data research workflows:

- **Business lead research:** Identify publicly indexed email contacts associated with relevant businesses.
- **Market research:** Explore businesses within selected categories and locations.
- **Local business research:** Combine business-related keywords with cities or regions.
- **B2B research:** Search for business categories and company-domain email addresses.
- **Contact discovery:** Find publicly indexed email addresses matching selected domain suffixes.
- **Dataset creation:** Build structured contact datasets for further analysis.
- **Competitive research:** Collect publicly indexed business contact information for market analysis.
- **Research workflows:** Gather search-based contact information for further manual review and validation.
- **Keyword research:** Compare the types of businesses and contacts surfaced by different search terms.

Use collected information responsibly and in accordance with applicable laws, website terms, and privacy requirements.

### Competitive Advantages

The Actor provides several practical configuration options in a single workflow:

- Multiple keywords can be processed in one run.
- Multiple email domains can be configured.
- Geographic filtering is optional.
- Exclusion terms provide additional result filtering.
- Per-keyword and per-domain targets can be configured.
- Duplicate email addresses are tracked across the run.
- Results are stored in a structured Apify dataset.

These capabilities make the Actor suitable for users who want more control than a single manual search query provides.

### Advantages

The **Gelbeseiten Email Scraper** is designed around configurable search-based contact discovery rather than a fixed search category.

Key advantages include:

- Flexible keyword selection
- Optional location targeting
- Configurable email-domain matching
- Exclusion-word filtering
- Structured dataset output
- Multiple search combinations
- Duplicate-aware collection
- Adjustable email targets
- Incremental dataset collection

This makes it possible to adapt a run to different business categories, locations, and contact research requirements without changing the Actor itself.

### Limitations

There are several important limitations to understand before running large searches:

- The Actor depends on publicly indexed search information, so it cannot guarantee that every Gelbeseiten profile or email address will be found.
- An email generally needs to appear in the available search-result description for it to be extracted.
- Results depend on the keywords, domains, and optional location supplied by the user.
- A narrow search can produce fewer results than expected.
- An email target is a collection target, not a guarantee that that number of unique emails exists.
- Duplicate email addresses are removed from the overall collected set, which can reduce the final number of records.
- Exclusion terms can intentionally remove otherwise relevant results if they appear in a description.
- Free-tier execution is limited by the Actor's configured free-user ceiling of 100 emails.
- Search availability and indexed content can change over time.

> 💡 **Important:** A `maxEmails` value represents how many addresses the Actor should attempt to collect for each keyword/domain combination. It does not guarantee that the requested number will be available.

### Pros and Cons

| Pros                                 | Cons                                                     |
| ------------------------------------ | -------------------------------------------------------- |
| Multiple keywords can be processed   | Results depend on indexed search information             |
| Supports location filtering          | Not every business listing will contain an indexed email |
| Supports custom email domains        | Narrow queries can return sparse results                 |
| Includes exclusion filtering         | Requested targets are not guaranteed                     |
| Produces structured dataset records  | Duplicate emails reduce the final unique count           |
| Configurable per-combination targets | Search results can vary over time                        |

### Comparison With Alternative Approaches

| Capability                   | Gelbeseiten Email Scraper | Manual Search                        |
| ---------------------------- | ------------------------- | ------------------------------------ |
| Multiple keyword searches    | Supported                 | Requires repeated searches           |
| Multiple email domains       | Supported                 | Requires separate filtering          |
| Location parameter           | Supported                 | Entered manually into searches       |
| Exclude-word filtering       | Supported                 | Requires manual review               |
| Structured dataset           | Supported                 | Usually requires manual organization |
| Duplicate tracking           | Supported                 | Requires manual checking             |
| Adjustable collection target | Supported                 | Manually controlled                  |
| Automated collection         | Supported                 | Primarily manual                     |

This comparison describes workflow differences rather than claiming that one approach is appropriate for every research project.

### Best Practices

For more useful results, consider the following practices:

- Start with a small `maxEmails` value to validate your keywords.
- Use several specific keywords instead of relying on one broad term.
- Add related professional or business terms when initial results are sparse.
- Use `location` when geographic relevance matters.
- Leave `location` empty when you want broader coverage.
- Add several relevant email domains when you need wider email-domain coverage.
- Use `excludeWords` carefully because matching descriptions are skipped entirely.
- Review the first results before increasing the collection target.
- Remember that duplicate email addresses are not added repeatedly.
- Validate important contact information before using it in downstream business processes.

### Troubleshooting

**Empty Results**

Check that your keywords are relevant and not overly restrictive. Try broader or related terms, remove an unnecessary location filter, or review the selected email domains.

**Too Few Emails**

A low result count does not necessarily indicate an error. The requested target depends on what is publicly indexed and what matching email addresses are available. Try additional keywords or relevant domains.

**Unexpectedly Missing Results**

Review `excludeWords`. If a selected word or phrase appears in a result description, that entire description is skipped.

**Location Produces Sparse Results**

A specific location can narrow the search significantly. Try a broader city or region, or leave the location empty when geographic filtering is not required.

**Target Is Not Reached**

`maxEmails` is a target rather than a guarantee. The Actor can only collect matching addresses that are available in the indexed search results.

**Repeated Email Addresses Are Missing**

This is expected. The Actor tracks previously collected email addresses and avoids adding the same email repeatedly.

**Large Runs Take Longer**

Broader searches involving many keywords and email domains naturally require more search combinations. For wide runs, allow sufficient Actor run time.

### Frequently Asked Questions

**What does the Gelbeseiten Email Scraper do?**

It searches publicly indexed Gelbeseiten information using your configured keywords and email domains, then extracts matching email addresses into structured dataset records.

**What inputs does the Gelbeseiten Email Scraper support?**

The required input is an array of `keywords`. Optional inputs include `location`, `customDomains`, `maxEmails`, and `excludeWords`.

**Can I use multiple keywords?**

Yes. The `keywords` field accepts multiple search terms, allowing you to target different business categories or related phrases in one run.

**Can I search a specific city or region?**

Yes. Enter a country, state, or city in `location`. Leave it empty when you do not want a geographic filter.

**Can I search for specific email domains?**

Yes. Use `customDomains` to specify suffixes such as `@gmail.com`, `@yahoo.com`, `@outlook.com`, or relevant business domains.

**What does maxEmails control?**

It controls the target number of email addresses for each keyword and email-domain combination. It is not a guarantee of the final number of unique records.

**What does excludeWords do?**

If a configured word or phrase appears in a result description, that description is skipped and no email is collected from it. Single-word matching is case-insensitive and uses whole-word matching.

**Does the Actor return full Gelbeseiten profiles?**

No. The documented output contains the keyword, result title, description, URL, and extracted email. It is focused on search-based email discovery rather than returning a complete profile schema.

**Why can the final number of emails be lower than my combined targets?**

Some searches may not contain enough matching indexed emails, and duplicate email addresses are only counted once across the run.

**Can I use the results for research and automation workflows?**

Yes. The structured Apify dataset can be used as the output of a broader research or automation workflow, subject to your own data-use requirements and applicable rules.

### NLP Keywords

- Gelbeseiten Email Scraper
- Gelbeseiten email extraction
- Gelbeseiten contact scraper
- Gelbeseiten email finder
- Gelbeseiten.de email scraper
- Gelbeseiten lead scraper
- Gelbeseiten contact extraction
- Gelbeseiten business leads
- Gelbeseiten professional contacts
- Gelbeseiten email addresses
- Gelbeseiten lead generation
- Gelbeseiten contact discovery
- Gelbeseiten search scraper
- Gelbeseiten data extraction
- Gelbeseiten public contact data
- Gelbeseiten keyword search
- Gelbeseiten location search
- Gelbeseiten business contact data
- Gelbeseiten structured dataset
- Gelbeseiten research data

### Related Keywords

- scrape emails from Gelbeseiten
- extract emails from Gelbeseiten.de
- find Gelbeseiten email addresses
- Gelbeseiten contact data scraper
- Gelbeseiten.de contact finder
- Gelbeseiten lead generation scraper
- Gelbeseiten business email finder
- Gelbeseiten professional email finder
- Gelbeseiten keyword email extractor
- Gelbeseiten email lead scraper
- Gelbeseiten contact research tool
- Gelbeseiten email data extraction
- Gelbeseiten public email discovery
- Gelbeseiten business contact extraction
- Gelbeseiten location-based email search
- Gelbeseiten email search by keyword
- Gelbeseiten email search by domain
- Gelbeseiten contact dataset
- Gelbeseiten lead research tool
- Gelbeseiten email collection

### Final Overview

The **Gelbeseiten Email Scraper** provides a configurable way to discover publicly indexed email addresses associated with Gelbeseiten.de search results. Users can combine multiple keywords, optional locations, custom email domains, collection targets, and exclusion terms to create targeted contact research workflows.

The output is organized into a structured Apify dataset containing the keyword, title, description, URL, and extracted email. Duplicate addresses are avoided, while the configurable search combinations allow users to adjust the scope of their research.

For best results, begin with focused keywords, test a small target, review the returned data, and then expand the keyword, location, or domain configuration when broader coverage is needed.

*Contact me:* <Alphascraper69@gmail.com>

# Actor input Schema

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

A list of keywords or queries to search for.

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

Optional country, state or city used to narrow the search. Leave it empty to search without a geographic filter.

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

List of custom email domains

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

How many addresses each search keyword + domain suffix combination may collect before the finder moves on to the next one. This is a per-combination target, not a run-wide total: with 3 keyword and 2 Domains and a limit of 20, the run works through all 6 combinations and aims for up to 20 addresses in each, so up to 120 overall. Lower values finish sooner and cost less; higher values dig deeper but never guarantee a fuller result, since the run can only find what is publicly listed.

## `excludeWords` (type: `array`):

Words or phrases you do not want to see.

## Actor input object example

```json
{
  "keywords": [
    "Unternehmen",
    "Restaurant"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com"
  ],
  "maxEmails": 5,
  "excludeWords": []
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# 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": [
        "Unternehmen",
        "Restaurant"
    ],
    "location": "",
    "customDomains": [
        "@gmail.com"
    ],
    "excludeWords": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("email_scraper/gelbeseiten-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": [
        "Unternehmen",
        "Restaurant",
    ],
    "location": "",
    "customDomains": ["@gmail.com"],
    "excludeWords": [],
}

# Run the Actor and wait for it to finish
run = client.actor("email_scraper/gelbeseiten-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": [
    "Unternehmen",
    "Restaurant"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com"
  ],
  "excludeWords": []
}' |
apify call email_scraper/gelbeseiten-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,email_scraper/gelbeseiten-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/UCFfc2GSennRF37FK/builds/HxVzTqbimWZqeZ9tu/openapi.json