# Chefkoch Recipe Scraper (`jungle_synthesizer/chefkoch-german-recipe-scraper`) Actor Scrape recipes from Chefkoch.de — Germany's largest recipe community with 380,000+ recipes. Extracts full structured data including ingredients, instructions, nutrition, ratings, and Chefkoch-specific fields (Schwierigkeitsgrad, Portionen). Supports bulk export and filtering by keyword or category. - **URL**: https://apify.com/jungle\_synthesizer/chefkoch-german-recipe-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** E-commerce, Education - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Chefkoch Recipe Scraper Scrape recipes from **Chefkoch.de** — Germany's largest recipe community with 380,000+ recipes. Extracts full structured data per recipe including ingredients, step-by-step instructions, nutrition facts, ratings, and Chefkoch-specific fields (Schwierigkeitsgrad, Portionen). ### What you get Each recipe record includes: | Field | Description | |-------|-------------| | `recipe_id` | Chefkoch numeric recipe ID | | `url` | Canonical recipe URL (with slug) | | `name` | Recipe title in German | | `author` | Community author username | | `description` | Short recipe description | | `recipe_category` | Category (e.g. Tarte/Quiche, Kochen, Backen) | | `recipe_cuisine` | Cuisine type (e.g. Deutsch, Frankreich, Thai) | | `difficulty` | `simpel` / `normal` / `pfiffig` (Chefkoch-specific) | | `prep_time` | Preparation time (ISO 8601 duration) | | `total_time` | Total cooking time (ISO 8601 duration) | | `recipe_yield` | Servings (Portionen) | | `recipe_ingredients` | Full ingredient list with quantities | | `recipe_instructions` | Step-by-step cooking instructions | | `aggregate_rating` | Average star rating (1–5) | | `rating_count` | Number of ratings | | `review_count` | Number of written reviews | | `nutrition_calories` | Calories per serving (where published) | | `nutrition_protein` | Protein content per serving | | `nutrition_fat` | Fat content per serving | | `nutrition_carbs` | Carbohydrate content per serving | | `keywords` | Tags and keywords | | `image_url` | Primary recipe image URL | | `date_published` | Publication date (ISO 8601) | ### Use cases - **German LLM training data** — The largest German-language recipe corpus (380K+ community recipes) for multilingual food-domain RAG or fine-tuning. - **Meal planning apps** — Build DACH-market recipe applications with full ingredient lists and structured cooking steps. - **Food trend analytics** — Track rating trends, popular ingredients, and difficulty distribution across the German cooking community. - **Recipe aggregators** — Bulk export for cross-platform recipe comparison or culinary research. ### How to use #### Bulk export (all recipes) Leave **Search Query** empty to export the full corpus. Set **Max Items** to control the batch size or leave blank for all 380,000+ recipes. ```json { "maxItems": 1000 } ```` #### Keyword search Use **Search Query** to filter recipes by keyword (German or English terms both work): ```json { "maxItems": 50, "searchQuery": "Lasagne" } ``` Other examples: `Kuchen`, `Pasta`, `vegan`, `Weihnachten`, `schnell` ### Technical notes - **Source**: Chefkoch public API (`api.chefkoch.de/v2/recipes`) for pagination + recipe HTML pages for full structured data via schema.org/Recipe JSON-LD - **Rate limiting**: Conservative 200ms delay between API requests - **Proxy**: Datacenter IPs sufficient — no Cloudflare or geo-lock on Chefkoch - **Language**: All field values are in German (no machine translation applied per source spec) # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of recipes to scrape. Leave blank to scrape all available recipes (~380,000+). ## `searchQuery` (type: `string`): Filter recipes by keyword (e.g. 'Lasagne', 'Kuchen'). Leave blank for bulk export of all recipes. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 } ``` # Actor output Schema ## `results` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "searchQuery": "" }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/chefkoch-german-recipe-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "searchQuery": "", } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/chefkoch-german-recipe-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "searchQuery": "" }' | apify call jungle_synthesizer/chefkoch-german-recipe-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/chefkoch-german-recipe-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Chefkoch Recipe Scraper", "description": "Scrape recipes from Chefkoch.de — Germany's largest recipe community with 380,000+ recipes. Extracts full structured data including ingredients, instructions, nutrition, ratings, and Chefkoch-specific fields (Schwierigkeitsgrad, Portionen). Supports bulk export and filtering by keyword or category.", "version": "0.1", "x-build-id": "RNPvJ0FRhopoKkPP4" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~chefkoch-german-recipe-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-chefkoch-german-recipe-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/jungle_synthesizer~chefkoch-german-recipe-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-chefkoch-german-recipe-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/jungle_synthesizer~chefkoch-german-recipe-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-chefkoch-german-recipe-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", "required": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of recipes to scrape. Leave blank to scrape all available recipes (~380,000+)." }, "searchQuery": { "title": "Search Query (optional)", "type": "string", "description": "Filter recipes by keyword (e.g. 'Lasagne', 'Kuchen'). Leave blank for bulk export of all recipes." } } }, "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 } } } } } } } } } } ```