# GelbeSeiten Lead Extractor (`kawsar/gelbeseiten-lead-extractor`) Actor GelbeSeiten Lead Extractor pulls business contacts from Germany's online business directory, so sales teams and marketers can build prospect lists for any city and industry without manual searching. - **URL**: https://apify.com/kawsar/gelbeseiten-lead-extractor.md - **Developed by:** [Kawsar](https://apify.com/kawsar) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## GelbeSeiten Lead Extractor Extract business leads from [GelbeSeiten](https://www.gelbeseiten.de), Germany's largest online business directory. Search by keyword and city to collect names, phone numbers, addresses, websites, ratings, reviews, and opening hours, all in a clean structured dataset ready for CRM import, outreach, or market research. Supports multiple keywords and multiple cities in a single run. The result limit applies per keyword and city pair, so you can scrape dozens of combinations at once. --- ### What data you get Each business listing returns the following fields: | Field | Description | |---|---| | `name` | Business name | | `category` | Industry category (e.g. Cafe-Restaurants, Arztpraxen, Rechtsanwaelte) | | `street` | Street name and number | | `postalCode` | German 5-digit postal code | | `city` | City name | | `address` | Full formatted address | | `phone` | Primary phone number | | `website` | Business website URL | | `rating` | Average star rating out of 5.0 | | `reviewCount` | Total number of customer reviews | | `businessDescription` | Short description or tagline from the listing | | `openingHours` | Current open/closed status and closing time | | `profileUrl` | Direct link to the GelbeSeiten business profile | | `sourceUrl` | Search results page the listing was found on | | `keyword` | Search keyword used | | `searchLocation` | Location searched | --- ### How to use #### Basic input ```json { "keywords": ["cafe"], "locations": ["berlin"], "maxItems": 50 } ```` #### Multi-city, multi-keyword run ```json { "keywords": ["arzt", "zahnarzt"], "locations": ["berlin", "münchen", "hamburg"], "maxItems": 100 } ``` This runs 6 searches (2 keywords × 3 cities) and returns up to 600 results total. *** ### Input parameters | Parameter | Required | Default | Description | |---|---|---|---| | `keywords` | Yes | — | One or more German search terms. Each keyword is searched in every location. | | `locations` | Yes | — | One or more German cities or regions. Each location is paired with every keyword. | | `maxItems` | No | `50` | Maximum listings per keyword and location pair. Pagination runs automatically until this limit is reached. | | `requestTimeoutSecs` | No | `30` | Seconds to wait for each page request before timing out. | #### How maxItems works The limit is **per search pair**, not across the entire run. | Keywords | Locations | maxItems | Max total results | |---|---|---|---| | 1 | 1 | 100 | 100 | | 2 | 3 | 50 | 300 | | 5 | 10 | 200 | 10,000 | *** ### Sample output ```json { "name": "FreudenGrün", "category": "Cafés", "street": "Chausseestr. 9", "postalCode": "10115", "city": "Berlin", "address": "Chausseestr. 9, 10115 Berlin", "phone": "030 25 76 25 96", "website": "https://freudengrun.de/", "rating": 5.0, "reviewCount": 1, "businessDescription": null, "openingHours": "Geöffnet – Schließt um 18:00", "profileUrl": "https://www.gelbeseiten.de/gsbiz/45c22f1a-3b99-4c04-9f0e-534ca0cd64d8", "sourceUrl": "https://www.gelbeseiten.de/suche/cafe/berlin", "keyword": "cafe", "searchLocation": "berlin" } ``` *** ### Use cases - **Sales prospecting** — build targeted contact lists for any German city and industry - **Email outreach** — collect phone numbers and websites for direct marketing campaigns - **Competitor research** — find all businesses in a category across multiple cities - **Market analysis** — compare business density, ratings, and coverage by region - **Local SEO audits** — gather category, address, and rating data for analysis - **CRM enrichment** — bulk-import German business contacts into your CRM *** ### Common search keywords GelbeSeiten is a German directory so keywords should be in German. | English | German keyword | |---|---| | Doctor | `arzt` | | Dentist | `zahnarzt` | | Lawyer | `rechtsanwalt` | | Notary | `notar` | | Tax advisor | `steuerberater` | | Architect | `architekt` | | Restaurant | `restaurant` | | Cafe | `cafe` | | Hotel | `hotel` | | Bakery | `baeckerei` | | Supermarket | `supermarkt` | | Pharmacy | `apotheke` | | Gym | `fitnessstudio` | | Hairdresser | `friseur` | | Electrician | `elektriker` | | Plumber | `klempner` | | Painter | `maler` | | Car dealer | `autohaendler` | | Insurance | `versicherung` | | Real estate | `immobilien` | | Bank | `bank` | | Cleaning service | `reinigungsservice` | | Driving school | `fahrschule` | | Kindergarten | `kindergarten` | | Physiotherapy | `physiotherapie` | *** ### Common locations Any German city, district, postal code, or region is accepted. **Major cities:** `berlin`, `münchen`, `hamburg`, `frankfurt`, `köln`, `stuttgart`, `düsseldorf`, `dortmund`, `essen`, `leipzig`, `bremen`, `dresden`, `hannover`, `nürnberg`, `duisburg`, `bochum`, `wuppertal`, `bielefeld`, `bonn`, `münster`, `mannheim`, `karlsruhe`, `augsburg`, `wiesbaden`, `gelsenkirchen`, `mönchengladbach`, `braunschweig`, `kiel`, `chemnitz`, `aachen` **By state:** `bayern`, `nordrhein-westfalen`, `baden-württemberg`, `niedersachsen`, `hessen`, `sachsen`, `berlin`, `rheinland-pfalz`, `schleswig-holstein`, `thüringen` *** ### Output formats Results are stored in the Apify dataset and can be exported as: - **JSON** — for API integrations and pipelines - **CSV** — for Excel and Google Sheets - **Excel (XLSX)** — ready-to-open spreadsheet - **XML** — for legacy system imports - **RSS** — for feed-based workflows Use the **Export** button in the Apify console or download via the [Apify API](https://docs.apify.com/api/v2#/reference/datasets/item-collection/get-items). *** ### Tips and notes - GelbeSeiten returns up to 50 listings per page. Pagination is automatic. - Fields with no data on the listing page return `null`. - Ratings are shown in German format (comma decimal) and are automatically converted to standard decimal numbers. - For bulk city coverage, list all cities in `locations` instead of running the actor separately per city. - Keywords are case-insensitive. `Arzt` and `arzt` return the same results. - If a city has fewer results than `maxItems`, the actor stops when results run out and moves to the next pair. *** # Actor input Schema ## `keywords` (type: `array`): One or more search terms, e.g. cafe, arzt, restaurant, rechtsanwalt. Each keyword is run against every location. ## `locations` (type: `array`): One or more German cities or regions, e.g. berlin, münchen, hamburg. Each location is paired with every keyword. ## `maxItems` (type: `integer`): Maximum listings to collect per keyword + location combination. With 2 keywords and 3 locations, up to 6 × maxItems results are returned. ## `requestTimeoutSecs` (type: `integer`): Seconds to wait for each page before timing out ## Actor input object example ```json { "keywords": [ "restaurant", "cafe", "arzt" ], "locations": [ "berlin", "münchen", "hamburg" ], "maxItems": 50, "requestTimeoutSecs": 30 } ``` # 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": [ "cafe" ], "locations": [ "berlin" ] }; // Run the Actor and wait for it to finish const run = await client.actor("kawsar/gelbeseiten-lead-extractor").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": ["cafe"], "locations": ["berlin"], } # Run the Actor and wait for it to finish run = client.actor("kawsar/gelbeseiten-lead-extractor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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": [ "cafe" ], "locations": [ "berlin" ] }' | apify call kawsar/gelbeseiten-lead-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kawsar/gelbeseiten-lead-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GelbeSeiten Lead Extractor", "description": "GelbeSeiten Lead Extractor pulls business contacts from Germany's online business directory, so sales teams and marketers can build prospect lists for any city and industry without manual searching.", "version": "0.0", "x-build-id": "exznwMzb8GfFzimjL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kawsar~gelbeseiten-lead-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kawsar-gelbeseiten-lead-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kawsar~gelbeseiten-lead-extractor/runs": { "post": { "operationId": "runs-sync-kawsar-gelbeseiten-lead-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kawsar~gelbeseiten-lead-extractor/run-sync": { "post": { "operationId": "run-sync-kawsar-gelbeseiten-lead-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "keywords", "locations" ], "properties": { "keywords": { "title": "Search keywords", "type": "array", "description": "One or more search terms, e.g. cafe, arzt, restaurant, rechtsanwalt. Each keyword is run against every location.", "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "One or more German cities or regions, e.g. berlin, münchen, hamburg. Each location is paired with every keyword.", "items": { "type": "string" } }, "maxItems": { "title": "Max items per query", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum listings to collect per keyword + location combination. With 2 keywords and 3 locations, up to 6 × maxItems results are returned.", "default": 50 }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 10, "maximum": 120, "type": "integer", "description": "Seconds to wait for each page before timing out", "default": 30 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```