TL;DR

• I built 14 Apify actors that scrape official government registries across Poland, Spain, Austria, and France
• To make them accessible from AI coding agents, I packaged them as 6 open-source skills in the getregdata repo
• One install command gives you access across 45+ AI agents - Claude Code, GitHub Copilot, Cline, Codex, Amp, and more
• The skills provide registry-specific analysis frameworks and let you query live data through the Apify API
• Install: skills add Nolpak14/getregdata -g -y

Why Government Registry Data Is Hard

If you have ever tried to programmatically access European government registries, you know the pain. Each country has its own set of portals, each with its own quirks:

• Poland's KRS (National Court Register) deliberately anonymizes board member names in its API - returning L****** instead of full names - while the same data is available unredacted in PDF extracts from the same portal
• Poland's CRBR (Beneficial Owners Register) has no API at all - just a CAPTCHA-protected web form that accepts one company at a time
• Poland's EKW (Land Registry) blocks all datacenter IPs - you need residential Polish proxies to access property ownership data
• Spain's BORME (Corporate Gazette) publishes 500+ corporate acts daily as unstructured gazette text with no machine-readable format
• Austria's Ediktsdatei (Insolvency Publications) requires an IWG license for the official API - but the public web portal has no such restriction
• France's Societe.com aggregates data from INSEE, INPI, and BODACC behind aggressive anti-bot measures

Each registry is a separate engineering challenge. Different authentication, different anti-scraping measures, different data formats, different legal frameworks.

The Actor Suite: 14 Registries, 4 Countries

Over the past months I built Apify actors for all of these. Each actor handles the specific technical challenges of its registry and returns clean, structured JSON.

Poland (9 registries)

Spain (2 registries)

Austria (2 registries)

France (1 registry)

All actors are pay-per-result with no subscriptions. Pricing ranges from $0.003 to $0.01 per result depending on the registry. A free Apify account includes $5 credits - enough for 100-1,600 lookups.

From Actors to AI Agent Skills

The actors work great when you know exactly which registry to query. But for many users, the real question is: "I need to check this Polish company - where do I even start?"

That is where skills come in. Skills are modular packages that give AI coding agents specialized knowledge. When you install a skill, your agent learns how to handle domain-specific tasks - in this case, querying European government registries.

I packaged the 14 actors into 6 skills organized by workflow:

Each skill includes:

• Analysis frameworks specific to the registries it covers (e.g., how to interpret Polish land registry sections, what Austrian insolvency proceeding types mean)
• Data extraction instructions for both MCP mode (direct tool calls) and API mode (curl/SDK)
• Output interpretation guides so you know what the returned data actually means

Installation

One command installs all 6 skills globally across every supported agent:

skills add Nolpak14/getregdata -g -y

This works with 45+ AI agents including Claude Code, GitHub Copilot, Cline, Codex, Amp, Antigravity, and more. The skills are installed to ~/.agents/skills/ and symlinked to agent-specific locations.

How It Works in Practice

Example 1: Check beneficial owners of a Polish company

You open Claude Code (or any supported agent) and type:

Check who owns the Polish company with NIP 5213103635 in CRBR

The regdata-kyc-aml skill activates. It knows that CRBR is Poland's beneficial owners registry and that NIP is the correct identifier. It guides the extraction:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("regdata/crbr-beneficial-owners-scraper").call(
    run_input={"nip": "5213103635"}
)

for item in client.dataset(run["defaultDatasetId"]).list_items().items:
    print(f"Company: {item['name']}")
    for owner in item.get("beneficialOwners", []):
        print(f"  UBO: {owner['firstName']} {owner['lastName']}")
        print(f"  Ownership: {owner.get('sharePercentage', 'N/A')}%")

If you have the Apify MCP server configured, the agent can run the actor directly through tool calls without writing any code.

Example 2: Monitor Spanish corporate gazette for new incorporations

Search BORME for new company incorporations in Barcelona from last week

The regdata-credit-risk skill activates (BORME corporate acts). It builds the right query:

run = client.actor("regdata/borme-corporate-acts-scraper").call(
    run_input={
        "dateFrom": "2026-04-21",
        "dateTo": "2026-04-28",
        "provinces": ["Barcelona"]
    }
)

Example 3: Extract Polish land registry data

Pull EKW data for property WR1K/00094598/3

The regdata-property skill activates. It knows the KW number format, that EKW requires residential Polish proxies, and how to interpret the four sections (Dzial I-IV):

run = client.actor("regdata/ekw-ksiegi-wieczyste-scraper").call(
    run_input={
        "kwNumbers": ["WR1K/00094598/3"],
        "viewType": "aktualna",
        "sections": ["all"]
    }
)

The skill then explains what each section means - Dzial II for ownership, Dzial III for restrictions and easements, Dzial IV for mortgages - so you can actually interpret the raw data.

Example 4: Get non-anonymized KRS board members

Extract board members for Polish KRS number 0000019193

The regdata-lead-gen skill knows that the official KRS API anonymizes names, and that the actor works around this by extracting full names from PDF court extracts:

run = client.actor("regdata/krs-fullnames-scraper").call(
    run_input={
        "krsNumbers": ["0000019193"],
        "extractType": "aktualny"
    }
)

You get full first and last names of board members, supervisory board, and shareholders - not the L****** that the API returns.

What Makes This Different from a Generic Scraping Skill

The value of domain-specific skills is that they carry registry knowledge that a generic web scraping tool does not have:

• The skill knows that EKW requires residential Polish proxies (datacenter IPs are blocked)
• It knows that KRS anonymizes names in the API but not in PDFs
• It knows that BORME Section A publishes corporate acts while Section B publishes financial data
• It knows that Austria's Ediktsdatei has Konkursverfahren (bankruptcy) and Sanierungsverfahren (restructuring) and what the difference means
• It knows that a Polish KW number follows the format CODE/NUMBER/DIGIT (e.g., WR1K/00094598/3)
• It knows that CRBR defines beneficial ownership as >25% shares or voting rights

This registry-specific knowledge means your AI agent can handle queries correctly without you needing to read documentation for each portal.

Authentication Setup

The skills provide analysis frameworks for free, but extracting live data requires an Apify API token:

export APIFY_TOKEN=apify_api_xxxxx

Get your token by creating a free Apify account - includes $5 credits, enough for hundreds of registry lookups.

Pricing Quick Reference

All actors use pay-per-result pricing. No subscriptions, no minimum commitments.

Typical cost for a full company check (CRBR + KNF + KRS Board): ~$0.019.

Technical Details

The skills repo follows the standard skills ecosystem structure:

getregdata/
  skills/
    regdata/SKILL.md              # Router
    regdata-kyc-aml/SKILL.md      # + references/
    regdata-credit-risk/SKILL.md  # + references/
    regdata-property/SKILL.md     # + references/
    regdata-compliance/SKILL.md   # + references/
    regdata-lead-gen/SKILL.md     # + references/

Each SKILL.md uses YAML frontmatter for trigger matching:

---
name: regdata-kyc-aml
description: "Extract beneficial ownership data from Poland's CRBR registry,
  financial license status from KNF, non-anonymized board members from KRS..."
metadata:
  version: 1.0.0
  author: regdata
  triggers:
    - "CRBR beneficial owner lookup"
    - "check KNF registry"
    - "KRS board members extract"
    - "Polish beneficial owners"
---

Triggers are registry-specific, not generic domain terms. The skill activates when you mention a specific European registry, not when you ask about "KYC" or "compliance" in general.

The references/ subdirectories contain detailed interpretation guides (land registry section breakdowns, insolvency proceeding types across jurisdictions, UOKiK clause categories) that the agent loads on demand.

Source Code and Contributing

The skills are MIT licensed and open source:

GitHub: github.com/Nolpak14/getregdata

The underlying Apify actors are available on the Apify Store under the regdata publisher profile.

If you work with government registries in other EU countries and want to contribute skills for those, PRs are welcome.

What Is Next

• More registries: Germany (Handelsregister, Insolvenzbekanntmachungen), Italy (Registro Imprese), Netherlands (KVK)
• Deeper cross-registry workflows: automated multi-country due diligence pipelines
• Scheduled monitoring: get notified when a company's registry data changes

Install: skills add Nolpak14/getregdata -g -y

Actors: apify.com/regdata

GitHub: github.com/Nolpak14/getregdata

This article is part of the European Registry Data series covering programmatic access to government registries across the EU.