# Gelbeseiten Scraper (`ahmed-data-lab/gelbeseiten-scraper`) Actor

Unofficial scraper for public German business listings. Search by keyword and location, collect paginated results, and extract contact details, ratings, websites, opening hours, and profile URLs.

- **URL**: https://apify.com/ahmed-data-lab/gelbeseiten-scraper.md
- **Developed by:** [Ahmed Ali](https://apify.com/ahmed-data-lab) (community)
- **Categories:** Lead generation, Developer tools, Automation
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.01 / 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.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Gelbe Seiten Apify Scraper

An Apify Actor that accepts a Gelbe Seiten results URL, loads all result batches through the site's public `/ajaxsuche` loader, visits each public profile page, deduplicates by profile URL, and pushes structured rows to the default Apify Dataset.

### Input

```json
{
  "searchKeyword": "Zahnarzt",
  "searchLocation": "Bonn",
  "maxResults": -1,
  "requestDelay": 0.15
}
```

The Actor automatically converts `searchKeyword` and `searchLocation` into a Gelbe Seiten results URL. `maxResults` controls the number of unique listings returned. Set it to a positive integer such as `25` for a capped run, or set it to `-1` to collect all available results. `requestDelay` is the pause between pagination and detail-page requests; the default `0.15` seconds provides basic throttling and can be increased if the target site responds slowly or rate-limits requests.

### Local run

Install the Apify CLI, then run:

```bash
apify actor:push
apify call --input='{"searchKeyword":"Zahnarzt","searchLocation":"Bonn","maxResults":25}'
```

Or run the Python entrypoint directly after installing dependencies:

```bash
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python actor.py
```

For a direct local Actor run with Apify storage emulation:

```bash
apify run --input='{"searchKeyword":"Zahnarzt","searchLocation":"Bonn","maxResults":-1}'
```

### Output

Each Dataset item contains listing fields plus public detail-page fields such as business name, category, address parts, phone, fax, email, website, rating, review count, opening hours, description, and profile URL. Missing fields remain empty. Detail-page failures are retained in `detail_fetch_error` without discarding the listing.

### Notes

- The scraper is intended for public Gelbe Seiten results URLs.
- Gelbe Seiten currently exposes additional results through a POST request to `/ajaxsuche`; the Actor repeats that request until no more rows are returned.
- The Apify SDK is pinned to the tested v4 line so it stays compatible with the Crawlee/Pydantic dependencies in the Actor image.
- Respect the target site's terms, robots guidance, and request limits. Increase `requestDelay` if the site responds slowly or begins rate-limiting.

# Actor input Schema

## `searchKeyword` (type: `string`):

The business category or search keyword, for example Zahnarzt or Restaurant.

## `searchLocation` (type: `string`):

The city or location, for example Bonn or Berlin.

## `requestDelay` (type: `number`):

Delay in seconds between pagination/detail requests.

## `maxResults` (type: `integer`):

Maximum number of unique listings to return. Use -1 for all available results.

## Actor input object example

```json
{
  "searchKeyword": "Zahnarzt",
  "searchLocation": "Bonn",
  "requestDelay": 0.15,
  "maxResults": -1
}
```

# Actor output Schema

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

API URL for the structured Dataset items produced by the Actor.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("ahmed-data-lab/gelbeseiten-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("ahmed-data-lab/gelbeseiten-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 '{}' |
apify call ahmed-data-lab/gelbeseiten-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,ahmed-data-lab/gelbeseiten-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/ljh4I3RTy1pIAnP03/builds/i0pyLFA4YdVzH8I7D/openapi.json