# Bundesanzeiger Filings Scraper (`automation-lab/bundesanzeiger-filings-scraper`) Actor Scrape Bundesanzeiger Federal Gazette search results and publication notices for German compliance, accounting, and risk monitoring. - **URL**: https://apify.com/automation-lab/bundesanzeiger-filings-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Business - **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 ## Bundesanzeiger Filings Scraper Export structured publication rows from the German Federal Gazette (Bundesanzeiger) for compliance, accounting, credit-risk, and corporate-intelligence workflows. ### What does Bundesanzeiger Filings Scraper do? Bundesanzeiger Filings Scraper searches the public Federal Gazette website and saves publication rows as a clean dataset. It can search by company name, fund name, or keyword. It can limit searches to major Bundesanzeiger sections. It can optionally open detail pages and include notice text. The actor is designed for repeat monitoring and export workflows. ### Who is it for? #### Compliance and KYC teams Compliance teams use this actor to monitor official company notices for onboarding, periodic review, and watchlist checks. Schedule recurring searches for customer names, export new publication rows, and route changes into case-management or audit workflows. #### Credit-risk and lending analysts Credit-risk teams use it to track German corporate disclosures before underwriting, renewal, or portfolio-review decisions. Search borrower names, subsidiaries, and guarantors, then compare publication dates and titles across repeat runs. #### Accounting and audit teams Accounting teams use it to find financial report publications and supporting Federal Gazette notices. Use company-name batches to collect structured rows for audit evidence, month-end close checks, or client monitoring. #### Corporate-intelligence and data teams Corporate-intelligence teams use it to maintain German company watchlists. Data vendors and enrichment teams can combine the extracted title, date, area, company, and detail URL with internal company profiles or CRM records. #### Legal operations teams Legal operations teams use it to archive notice metadata and optional notice text for internal review. Keep detail extraction on for evidence collection, or keep it off for cheaper monitoring runs. ### Why use this actor? Bundesanzeiger search results are useful but not convenient for automation. This actor turns the public table into typed JSON records. You can schedule runs, export CSV files, or send results to downstream tools. You can monitor several companies in one run. You can keep detail extraction off for fast watchlist runs. You can enable detail extraction when notice text is required. ### What data can you extract? The actor extracts one dataset item per publication row. | Field | Description | | --- | --- | | `query` | Search query that produced the row | | `searchArea` | Bundesanzeiger area filter used | | `companyName` | Company, fund, or publisher name | | `location` | Location shown under the name | | `area` | Federal Gazette area/category | | `publicationTitle` | Linked publication title | | `information` | Full information cell text | | `publicationDate` | Publication date from the result table | | `detailUrl` | Detail page URL for the notice | | `noticeText` | Optional detail-page notice text | | `sourceUrl` | Search result page URL | | `fetchedAt` | ISO timestamp of extraction | ### How much does it cost to scrape Bundesanzeiger filings? This actor uses pay-per-event pricing: a fixed run-start charge plus a small per-publication charge for every saved dataset item. | Charge | FREE | BRONZE | SILVER | GOLD | PLATINUM | DIAMOND | | --- | ---: | ---: | ---: | ---: | ---: | ---: | | Run start | $0.005000 | $0.005000 | $0.005000 | $0.005000 | $0.005000 | $0.005000 | | Publication saved | $0.000034251 | $0.000029784 | $0.000023231 | $0.000017870 | $0.000011914 | $0.000010000 | Example cost estimates before Apify platform fees or discounts: | Run size | FREE estimate | BRONZE estimate | What it is good for | | --- | ---: | ---: | --- | | 20 publications | about $0.0057 | about $0.0056 | First test run or one-company lookup | | 120 publications | about $0.0091 | about $0.0086 | Realistic monitoring export | | 1,000 publications | about $0.0393 | about $0.0348 | Larger portfolio or historical collection | The Apify free plan can usually cover many small tests because the default example input saves only 20 publications and costs well under one cent in actor charges. For predictable spend, start with `maxItems: 20`, review the dataset, then increase the limit for scheduled monitoring. Cost tips: - Keep `maxItems` low for exploratory runs. - Disable detail extraction when you only need search rows. - Enable detail extraction when you need the notice body for evidence or summarization. - Batch related company names in one run to avoid repeated start charges. ### How to use Bundesanzeiger Filings Scraper 1. Enter one or more company names or keywords. 2. Choose a Bundesanzeiger search area if needed. 3. Set `maxItems` to the maximum number of publications to save. 4. Decide whether to open detail pages. 5. Run the actor. 6. Download the dataset as JSON, CSV, Excel, or XML. ### Input options #### `queries` Company names, fund names, or keywords. Examples: - `Siemens` - `BASF` - `Deutsche Bank` - `Jahresabschluss` #### `searchArea` Use `all` for the broadest search. Use `business` for business disclosures. Use `accounting` for accounting and financial reports. Use `capital_market` for funds and capital-market publications. #### `maxItems` The total number of publication rows to save across all queries. The default is intentionally small so the first run is cheap. #### `includeDetails` When false, the actor saves search result rows only. When true, the actor opens each result page and saves `noticeText`. #### `startUrls` Advanced users can provide existing Bundesanzeiger result URLs. This is useful when you want to continue from a known result page. ### Output example ```json { "query": "Siemens", "searchArea": "all", "companyName": "Siemens Gamesa Renewable Energy Deutschland GmbH", "location": "Bremerhaven", "area": "Business Disclosures", "publicationTitle": "Aufsichtsrat", "information": "Aufsichtsrat", "publicationDate": "06/26/2026", "detailUrl": "https://www.bundesanzeiger.de/pub/en/search2?...", "noticeText": "Siemens Gamesa Renewable Energy Deutschland GmbH ...", "sourceUrl": "https://www.bundesanzeiger.de/pub/en/search2?2", "fetchedAt": "2026-06-28T04:52:50.488Z" } ```` ### Tips for better results Use exact company names for targeted monitoring. Use broader keywords for discovery workflows. Run separate tasks for separate portfolios. Use `accounting` when you only need annual financial statements. Use `business` when you need corporate notices and shareholder information. Use `capital_market` when monitoring funds or securities publications. ### Monitoring workflows Create an Apify task with a fixed query list. Schedule it daily, weekly, or monthly. Export the dataset to your data warehouse. Compare new rows against previous runs using publication title and date. Send alerts when a watched company appears. ### Integrations Use Apify webhooks to notify your compliance system after each run. Use Make or Zapier to push CSV rows to Google Sheets. Use the Apify API to load results into a CRM or risk platform. Use datasets to keep a historical archive of notices. Use storage integrations to export files to S3-compatible storage. ### API usage with Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/bundesanzeiger-filings-scraper').call({ queries: ['Siemens'], searchArea: 'business', maxItems: 50, includeDetails: false, }); console.log(run.defaultDatasetId); ``` ### API usage with Python ```python from apify_client import ApifyClient import os client = ApifyClient(os.environ['APIFY_TOKEN']) run = client.actor('automation-lab/bundesanzeiger-filings-scraper').call(run_input={ 'queries': ['BASF'], 'searchArea': 'accounting', 'maxItems': 50, 'includeDetails': True, }) print(run['defaultDatasetId']) ``` ### API usage with cURL ```bash curl -X POST 'https://api.apify.com/v2/acts/automation-lab~bundesanzeiger-filings-scraper/runs?token=YOUR_APIFY_TOKEN' \ -H 'Content-Type: application/json' \ -d '{"queries":["Siemens"],"maxItems":20,"includeDetails":false}' ``` ### MCP access You can use this actor from Claude Desktop, Claude Code, or any MCP client through Apify MCP. MCP URL: ```text https://mcp.apify.com/?tools=automation-lab/bundesanzeiger-filings-scraper ``` Claude Code setup: ```bash claude mcp add apify-bundesanzeiger --transport http https://mcp.apify.com/?tools=automation-lab/bundesanzeiger-filings-scraper ``` Claude Desktop or generic MCP JSON configuration: ```json { "mcpServers": { "apify-bundesanzeiger": { "url": "https://mcp.apify.com/?tools=automation-lab/bundesanzeiger-filings-scraper" } } } ``` Example prompts: - "Search Bundesanzeiger for Siemens business disclosures." - "Find the latest accounting publications for BASF." - "Monitor these German companies and summarize new publication titles." ### Reliability notes The Bundesanzeiger website uses session-scoped Wicket links. The actor preserves cookies and follows pagination links within one HTTP session. Detail URLs may be session-specific. For persistent references, store the extracted title, date, company, and source page. ### Legality, legal, and ethical use This actor extracts publicly available Federal Gazette pages. You are responsible for complying with applicable laws and terms. Do not use the actor to overload the target website. Keep schedules reasonable. Store only data you are allowed to process. ### Troubleshooting #### Why do I get fewer rows than expected? The search area may be too narrow, or the query may have few matches. Try `searchArea: all` and a broader keyword. #### Why is `noticeText` empty? Enable `includeDetails` to open detail pages. Some rows may not expose a long body beyond the publication title. #### Why are detail URLs unusual? Bundesanzeiger uses session-scoped links. Use the saved row fields as the stable data record. ### Related scrapers Explore other Automation Lab actors for public records, company intelligence, and compliance monitoring. - https://apify.com/automation-lab/handelsregister-de-scraper - https://apify.com/automation-lab/insolvenzbekanntmachungen-de-scraper - https://apify.com/automation-lab/website-contact-finder ### Changelog Initial version supports keyword search, section filters, pagination, optional detail extraction, and typed output. ### Support If the site changes or your workflow needs another Bundesanzeiger section, open an issue on the actor page. ### FAQ #### Can I search multiple companies at once? Yes. Add multiple strings to `queries`. #### Can I extract financial reports only? Yes. Set `searchArea` to `accounting`. #### Can I extract capital market publications? Yes. Set `searchArea` to `capital_market`. #### Can I run this actor every day? Yes. Create an Apify task and schedule it. #### Does the actor require login? No. It uses the public Bundesanzeiger search pages. #### Does it download PDFs? The initial version focuses on search rows and notice text. If a publication exposes document links, request PDF extraction as a follow-up feature. # Actor input Schema ## `queries` (type: `array`): German company names, fund names, or publication keywords to search in the Federal Gazette. ## `startUrls` (type: `array`): Optional Bundesanzeiger search result URLs to continue from instead of starting a new keyword search. ## `searchArea` (type: `string`): Limit search to a Bundesanzeiger section, or keep all public areas. ## `maxItems` (type: `integer`): Maximum number of publication rows to save across all queries. ## `includeDetails` (type: `boolean`): When enabled, the actor opens each publication page and adds noticeText. Disable for faster monitoring runs. ## `maxDetailCharacters` (type: `integer`): Maximum characters to keep from each detail notice when detail extraction is enabled. Leave unchanged unless you need longer notice bodies. ## Actor input object example ```json { "queries": [ "Siemens", "BASF" ], "startUrls": [], "searchArea": "all", "maxItems": 20, "includeDetails": false } ``` # Actor output Schema ## `overview` (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 = { "queries": [ "Siemens", "BASF" ], "startUrls": [], "searchArea": "all", "maxItems": 20, "includeDetails": false }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/bundesanzeiger-filings-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 = { "queries": [ "Siemens", "BASF", ], "startUrls": [], "searchArea": "all", "maxItems": 20, "includeDetails": False, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/bundesanzeiger-filings-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 '{ "queries": [ "Siemens", "BASF" ], "startUrls": [], "searchArea": "all", "maxItems": 20, "includeDetails": false }' | apify call automation-lab/bundesanzeiger-filings-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/bundesanzeiger-filings-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bundesanzeiger Filings Scraper", "description": "Scrape Bundesanzeiger Federal Gazette search results and publication notices for German compliance, accounting, and risk monitoring.", "version": "0.1", "x-build-id": "7kEaGUQdIkbfBKuYf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~bundesanzeiger-filings-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-bundesanzeiger-filings-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~bundesanzeiger-filings-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-bundesanzeiger-filings-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~bundesanzeiger-filings-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-bundesanzeiger-filings-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "queries" ], "properties": { "queries": { "title": "Company or keyword queries", "type": "array", "description": "German company names, fund names, or publication keywords to search in the Federal Gazette.", "items": { "type": "string" } }, "startUrls": { "title": "Existing Bundesanzeiger result URLs", "type": "array", "description": "Optional Bundesanzeiger search result URLs to continue from instead of starting a new keyword search.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "searchArea": { "title": "Search area", "enum": [ "all", "official", "unofficial", "judicial", "business", "accounting", "capital_market", "various" ], "type": "string", "description": "Limit search to a Bundesanzeiger section, or keep all public areas.", "default": "all" }, "maxItems": { "title": "Maximum publications", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of publication rows to save across all queries.", "default": 20 }, "includeDetails": { "title": "Open publication detail pages", "type": "boolean", "description": "When enabled, the actor opens each publication page and adds noticeText. Disable for faster monitoring runs.", "default": false }, "maxDetailCharacters": { "title": "Maximum notice text characters", "minimum": 500, "maximum": 100000, "type": "integer", "description": "Maximum characters to keep from each detail notice when detail extraction is enabled. Leave unchanged unless you need longer notice bodies." } } }, "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 } } } } } } } } } } ```