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EU AI Act and GDPR checks with sources: classify an AI system, trace each duty, find the supervisor.
Remote server: your requests and data go to www.praxikon.com. Claude Code: claude mcp add --transport http praxikon https://www.praxikon.com/api/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
classify_system — Use this as the first step when you hold a concrete AI system and need to know which routes of the EU AI Act come into view: prohibited pracget_applicable_obligations — Use this when you need the obligations themselves for one assessed system rather than the classification picture: which obligations apply, wexplain_applicability — Use this whenever you have to justify why an obligation does or does not bear on a case, and an outcome on its own is not enough. It returnsget_source_provenance — Use this before you quote, cite or hand on anything from this graph, and whenever a reader asks on what authority a statement rests. It retuget_national_enforcement — Use this for the national layer: which authority is designated in a member state, how far the implementing law has come, and which dated enfcheck_case — Use this when the user describes a concrete, intended use of AI or of personal data (a system, a project, a supplier) and wants to know whetexport_dpia_intake — Use this when the user wants the DPIA intake of a concrete, intended use of AI or of personal data as a Word file to work on, and, where theanswer_question — Use this for a short, general question about the EU AI Act or the GDPR (AVG), such as whether a customer service chatbot has to say that it request_expert_review — Use this only when the user asks for it in their own words: they want to talk to a person, ask for a human expert, or ask how to get in toucNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.