# German News Scraper — Tagesschau, Spiegel, FAZ & more (`ambitious_silo/german-news-scraper`) Actor Scrape breaking news and articles from 7 major German news sources: Tagesschau, Spiegel, Welt, FAZ, Süddeutsche Zeitung, Bild, and Die Zeit. Filter by source, region, or topic. Returns structured data with title, summary, author, publication date, full URL, and categories. - **URL**: https://apify.com/ambitious\_silo/german-news-scraper.md - **Developed by:** [Ambition Silo](https://apify.com/ambitious_silo) (community) - **Categories:** News - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 article-results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## German News Scraper Scrape breaking news and articles from **7 major German news sources** in one API call. ### Supported sources | Source | URL | Content | |--------|-----|---------| | Tagesschau | tagesschau.de | Public broadcaster news (via API2) | | Spiegel | spiegel.de | Investigative journalism, politics | | Welt | welt.de | National and international news | | FAZ | faz.net | Frankfurter Allgemeine Zeitung | | Süddeutsche | sueddeutsche.de | Süddeutsche Zeitung | | Bild | bild.de | Germany's largest tabloid | | Die Zeit | zeit.de | Weekly newspaper, deep analysis | ### Why use this scraper - **7 sources in one call** — aggregate German news in a single run - **Structured data** — title, summary, date, categories, source, URL - **Filterable** — pick specific sources or all of them - **$0.002 per article** — cheapest news scraper on Apify - **RSS-based** — fast, reliable, no bot detection issues ### Output fields Every article includes: - `title` — article headline - `url` — direct link to the full article - `description` — summary or lead paragraph - `publishDate` — publication timestamp - `categories` — topic tags (Politik, Sport, Wirtschaft, etc.) - `source` — which outlet published it - `guid` — unique article identifier ### Use cases - News aggregation and monitoring - Media analysis and sentiment tracking - Content curation for German-language sites - Journalism research - SEO content planning (trending topics) ### Pricing **Free tier:** First 10 articles per run are free. After that: $0.002 per article. Example costs: - 10 articles (free tier): **$0.00** - 50 articles: ~$0.08 - 100 articles: ~$0.18 # Actor input Schema ## `maxResults` (type: `integer`): Maximum number of articles to scrape. ## `rssSources` (type: `array`): Which German news sources to include. Leave default for all. ## `regions` (type: `array`): Filter tagesschau articles by German federal state. ## `topics` (type: `array`): Filter articles by topic/ressort. ## Actor input object example ```json { "maxResults": 50, "rssSources": [ "tagesschau", "spiegel", "welt", "faz", "sueddeutsche", "bild", "zeit" ] } ```` # Actor output Schema ## `results` (type: `string`): All scraped items stored in the default dataset. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("ambitious_silo/german-news-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = {} # Run the Actor and wait for it to finish run = client.actor("ambitious_silo/german-news-scraper").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 '{}' | apify call ambitious_silo/german-news-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ambitious_silo/german-news-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "German News Scraper — Tagesschau, Spiegel, FAZ & more", "description": "Scrape breaking news and articles from 7 major German news sources: Tagesschau, Spiegel, Welt, FAZ, Süddeutsche Zeitung, Bild, and Die Zeit. Filter by source, region, or topic. Returns structured data with title, summary, author, publication date, full URL, and categories.", "version": "0.6", "x-build-id": "clLWShAGQM0i0UcJQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ambitious_silo~german-news-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ambitious_silo-german-news-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ambitious_silo~german-news-scraper/runs": { "post": { "operationId": "runs-sync-ambitious_silo-german-news-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ambitious_silo~german-news-scraper/run-sync": { "post": { "operationId": "run-sync-ambitious_silo-german-news-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "maxResults": { "title": "Max results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of articles to scrape.", "default": 50 }, "rssSources": { "title": "RSS sources", "type": "array", "description": "Which German news sources to include. Leave default for all.", "items": { "type": "string" }, "default": [ "tagesschau", "spiegel", "welt", "faz", "sueddeutsche", "bild", "zeit" ] }, "regions": { "title": "Regions (tagesschau only)", "type": "array", "description": "Filter tagesschau articles by German federal state.", "items": { "type": "string" } }, "topics": { "title": "Topics", "type": "array", "description": "Filter articles by topic/ressort.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```