# Denmark Government Data API (`lentic_clockss/denmark-data-search`) Actor Search 24 Danish government data sources — GLEIF LEI entities, Statistics Denmark (StatBank) business/health/property/construction data, clinical trials, PlanData building zones, parliament cases and votes, EUR-Lex directives, and TED procurement. - **URL**: https://apify.com/lentic\_clockss/denmark-data-search.md - **Developed by:** [kane liu](https://apify.com/lentic_clockss) (community) - **Categories:** Lead generation, MCP servers - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Denmark Government Data Search Search **24 official Danish government data sources** in a single API call — GLEIF LEI entities, Statistics Denmark (StatBank) business, health, property and construction statistics, Danish clinical trials, PlanData building zones and local plans, Folketinget parliament cases and votes, EUR-Lex directives, and TED procurement notices. All data from official Danish government databases through the SIP Public Data Gateway. ### What is Denmark Government Data Search? Denmark Government Data Search is an Apify Actor that queries official Danish government databases across business, construction, health, legal, and procurement domains. Instead of navigating StatBank, PlanData, Folketinget, and sundhedsdata portals separately, you search them all at once. The Actor calls the **SIP Public Data Gateway** — a unified API that normalizes responses from 24 Danish data products. No browser, no scraping — just HTTPS API calls. ### Why use Denmark Government Data Search? - **One search, 24 sources** — Query company data, building zones, health statistics, parliament records, and procurement simultaneously - **Official government data** — All sources are public databases from Statistics Denmark, PlanData, Folketinget, and Danish health authorities - **Rich StatBank coverage** — Business demographics, construction activity, property prices, health expenditure, municipal and regional accounts - **Parliament transparency** — Folketinget cases, votes, and legislative proceedings - **Nordic market entry** — Essential data for companies entering the Danish/Nordic market #### Use cases | Who | What | |-----|------| | **Market researchers** | Access StatBank business demographics, construction activity, and property statistics | | **Healthcare analysts** | Search Danish clinical trials, health expenditure, and WHO health indicators | | **Property developers** | Find PlanData building zones, local plans, and StatBank property/construction data | | **Legal professionals** | Query EUR-Lex directives for Denmark and Folketinget legislative proceedings | | **Government contractors** | Monitor TED procurement notices and public finance data | | **Nordic investors** | Access GLEIF LEI entities and business statistics for Danish companies | ### What data can Denmark Government Data Search extract? | Source | Data type | Example fields | |--------|-----------|----------------| | GLEIF LEI | Danish LEI-registered entities | legal_name, lei, entity_status | | StatBank business | Business demographics and statistics | indicator, industry, value, period | | StatBank construction | Construction activity and permits | indicator, municipality, value | | StatBank property | Property prices and transactions | area, price_index, transactions | | StatBank health | Health system statistics | indicator, region, value | | StatBank health expenditure | Healthcare spending data | category, expenditure, year | | PlanData building zones | Zoning and land use | zone_type, municipality, area | | PlanData local plans | Municipal planning documents | plan_name, municipality, status | | Clinical trials | Danish clinical trials | title, sponsor, phase, status | | WHO health indicators | Health metrics for Denmark | indicator, value, year | | Parliament cases | Folketinget legislative cases | title, type, status, committee | | Parliament votes | Parliamentary voting records | case, result, date | | EUR-Lex directives | EU directives applicable to Denmark | title, celex, date | | TED procurement | EU procurement for Denmark | title, buyer, value, deadline | | StatBank govt finance | Government revenue and expenditure | category, amount, year | | StatBank municipal | Municipal financial accounts | municipality, indicator, value | ### How to search Danish data 1. Open the Actor in Apify Console 2. Enter search terms (e.g. "Novo Nordisk", "København", "bolig", "sundhed") 3. Select data categories — business, construction, and health are on by default 4. Click **Start** — the Actor queries all enabled sources in parallel 5. Download results as JSON, CSV, or Excel #### Example input ```json { "searchTerms": ["Novo Nordisk", "Maersk"], "includeBusiness": true, "includeConstruction": false, "includeHealth": false, "includeLegal": false, "includeProcurement": false, "maxResultsPerSource": 50 } ```` ### Output ```json { "legal_name": "Novo Nordisk A/S", "lei": "549300I6KHWHOQO2XR19", "entity_status": "ACTIVE", "_product_id": "dk_gleif_lei", "_source": "gleif_lei", "_search_term": "Novo Nordisk", "_collected_at": "2026-04-08T14:00:00Z" } ``` ### How much does it cost? Pay-per-event pricing at $3.00 per 1,000 records returned. - **Company lookup** (1 term, business only): ~$0.01–0.03 - **Full scan** (3 terms, all 24 sources): ~$0.30–2.00 No browser overhead. Control costs with `maxResultsPerSource`. ### Data sources (24 Danish products) | Category | Sources | Count | |----------|---------|-------| | Business | GLEIF LEI, StatBank business, business aggregate | 3 | | Construction | PlanData (zones/local plans), StatBank (construction/property), construction aggregate | 5 | | Health | Clinical trials, StatBank (health/expenditure/demographics), WHO indicators, health aggregate | 6 | | Legal | EUR-Lex (directives/regulations), Folketinget (cases/votes), legal aggregate | 5 | | Procurement | TED procurement, StatBank (govt finance/municipal/regional accounts), procurement aggregate | 5 | ### FAQ **Does it support Danish search terms?** Yes. SIP passes terms directly to Danish APIs. StatBank and PlanData support Danish. GLEIF and EUR-Lex work with English. **What is StatBank?** Statistics Denmark's statistical database (statistikbanken.dk) — the national statistics office providing detailed socioeconomic data across 2,000+ tables. **Can I access municipal-level data?** Yes. StatBank municipal accounts and PlanData local plans provide kommune-level granularity. ### Use as MCP Tool (AI Agent Integration) This Actor works as an MCP tool — AI agents (Claude, GPT, Cursor) can discover and run it automatically. #### Quick setup (Claude Desktop / Cursor / VS Code) Add to your MCP config: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com", "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" } } } } ``` Then ask your AI: *"Search for Novo Nordisk in Danish government databases"* #### Direct API call ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("lentic_clockss/denmark-data-search").call( run_input={"searchTerms": ["Novo Nordisk"], "maxResultsPerSource": 50} ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### Other Data API Actors - [EU Business & Company Registry API](https://apify.com/lentic_clockss/eu-business-data-search) - [Switzerland Government Data API](https://apify.com/lentic_clockss/switzerland-data-search) - [UK Government Data API](https://apify.com/lentic_clockss/uk-data-search) - [US Business Entity Data API](https://apify.com/lentic_clockss/us-business-entity-search) # Actor input Schema ## `searchTerms` (type: `array`): Keywords to search (e.g. 'Novo Nordisk', 'Copenhagen', 'bolig', 'sundhed'). Each term is searched across all enabled Danish data sources in parallel. ## `includeBusiness` (type: `boolean`): Search GLEIF Danish LEI entities, StatBank business statistics, and business aggregate (3 sources). ## `includeConstruction` (type: `boolean`): Search PlanData building zones and local plans, StatBank construction, property statistics, and construction aggregate (5 sources). ## `includeHealth` (type: `boolean`): Search Danish clinical trials, StatBank health statistics, health expenditure, demographics, WHO health indicators, and health aggregate (6 sources). ## `includeLegal` (type: `boolean`): Search Folketinget parliament cases and votes, EUR-Lex directives and regulations for Denmark, and legal aggregate (5 sources). ## `includeProcurement` (type: `boolean`): Search TED Danish procurement, StatBank government finance, municipal accounts, regional accounts, and procurement aggregate (5 sources). ## `maxResultsPerSource` (type: `integer`): Maximum records to return per data source (gateway caps at 200). ## Actor input object example ```json { "searchTerms": [ "Novo Nordisk" ], "includeBusiness": true, "includeConstruction": true, "includeHealth": true, "includeLegal": false, "includeProcurement": false, "maxResultsPerSource": 50 } ``` # Actor output Schema ## `records` (type: `string`): Dataset containing business, construction, health, legal, and procurement data from 24 Danish government sources. # 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 = { "searchTerms": [ "Novo Nordisk" ] }; // Run the Actor and wait for it to finish const run = await client.actor("lentic_clockss/denmark-data-search").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 = { "searchTerms": ["Novo Nordisk"] } # Run the Actor and wait for it to finish run = client.actor("lentic_clockss/denmark-data-search").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 '{ "searchTerms": [ "Novo Nordisk" ] }' | apify call lentic_clockss/denmark-data-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lentic_clockss/denmark-data-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Denmark Government Data API", "description": "Search 24 Danish government data sources — GLEIF LEI entities, Statistics Denmark (StatBank) business/health/property/construction data, clinical trials, PlanData building zones, parliament cases and votes, EUR-Lex directives, and TED procurement.", "version": "0.1", "x-build-id": "7iFROeCXHedRfAb4J" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lentic_clockss~denmark-data-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lentic_clockss-denmark-data-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lentic_clockss~denmark-data-search/runs": { "post": { "operationId": "runs-sync-lentic_clockss-denmark-data-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lentic_clockss~denmark-data-search/run-sync": { "post": { "operationId": "run-sync-lentic_clockss-denmark-data-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchTerms" ], "properties": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Keywords to search (e.g. 'Novo Nordisk', 'Copenhagen', 'bolig', 'sundhed'). Each term is searched across all enabled Danish data sources in parallel.", "items": { "type": "string" } }, "includeBusiness": { "title": "Include business data", "type": "boolean", "description": "Search GLEIF Danish LEI entities, StatBank business statistics, and business aggregate (3 sources).", "default": true }, "includeConstruction": { "title": "Include construction & property data", "type": "boolean", "description": "Search PlanData building zones and local plans, StatBank construction, property statistics, and construction aggregate (5 sources).", "default": true }, "includeHealth": { "title": "Include health data", "type": "boolean", "description": "Search Danish clinical trials, StatBank health statistics, health expenditure, demographics, WHO health indicators, and health aggregate (6 sources).", "default": true }, "includeLegal": { "title": "Include legal & parliament data", "type": "boolean", "description": "Search Folketinget parliament cases and votes, EUR-Lex directives and regulations for Denmark, and legal aggregate (5 sources).", "default": false }, "includeProcurement": { "title": "Include procurement & public finance", "type": "boolean", "description": "Search TED Danish procurement, StatBank government finance, municipal accounts, regional accounts, and procurement aggregate (5 sources).", "default": false }, "maxResultsPerSource": { "title": "Max results per source", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum records to return per data source (gateway caps at 200).", "default": 50 } } }, "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 } } } } } } } } } } ```