eu-reg-mcp

Let your AI agent check the ESMA MiCAR register and cite EU AI Act provisions instead of guessing — with every answer framed as a fact or a candidate flag for human review.

Scope today: the ESMA interim MiCAR register (search, summary, change tracking), MiCAR white paper linting, and EU AI Act risk-tier classification. Other EU regulation is not covered.

Try it

eu-reg-mcp is on PyPI. With uv installed, uvx fetches and runs it:

claude mcp add eu-reg -- uvx eu-reg-mcp

Then ask your agent: "Is <entity> on the MiCAR register, and what format is its white paper?" The register tools need no API key. For all five tools, add the lint and classify extras instead:

claude mcp add eu-reg -- uvx --from 'eu-reg-mcp[lint,classify]' eu-reg-mcp

Without uv, run pip install 'eu-reg-mcp[lint,classify]' in a Python 3.13+ virtual environment and start eu-reg-mcp with that environment active. Install options and network use: docs/tools.md.

{
  "mcpServers": {
    "eu-reg": {
      "command": "uvx",
      "args": ["eu-reg-mcp"]
    }
  }
}

Example output

Synthetic data. Produced on 2026-10-14 by running this repo's register code (register.search_entries / register.recent_changes) against the synthetic test fixtures in tests/fixtures/, not the live register. The entity and its LEI are test data. Output shape is what a live call returns; values are not.

search_micar_register(query="skygate"):

{
  "snapshot_date": "2026-07-07",
  "total_matches": 1,
  "results": [
    {
      "register": "other-wp",
      "entity_name": "SKYGATE Network GmbH",
      "lei": "984500BBFE52FE449926",
      "member_state": "AT",
      "authority": "FMA",
      "whitepaper_url": "WWW.SKYGATETOKEN.AT",
      "format_class": "unspecified",
      "register_last_update": "30/12/2024"
    }
  ],
  "truncated": false,
  "notice": "Facts from the public ESMA interim MiCAR register (Art. 109 MiCAR) as mirrored by the MiCAR Register Observatory. No legal assessment of any entity; not legal advice."
}

micar_register_changes(change_type="removed") returns the same kind of cited record (snapshot date, register, entity) and notes that "the register itself does not state why" an entry was removed. With the extras installed, the lint and classify tools cite the provision behind each finding, for example Anhang I Teil A MiCAR (MiCAR Annex I, Part A), Art. 5(1)(f) AIA, Annex III(4)(a) AIA, and Art. 51 AIA for a general-purpose AI model with systemic risk. Sample output from synthetic inputs: docs/tools.md.

Tools

Parameters, data sources, caching and network requirements: docs/tools.md.

Why not just ask an LLM?

An ungrounded model can invent register entries or provisions. Here, register answers come from a dated snapshot of the public register, and lint/classification output comes from deterministic rules with citations. Review-gated means the output is a candidate flag pending human legal review — never a legal assessment or legal advice. Details: docs/guardrails.md.

Links

• PyPI: eu-reg-mcp, micar-whitepaper-linter, eu-ai-act-classifier
• Register data: micar-register-observatory (weekly snapshots of the public ESMA register, Art. 109 VO (EU) 2023/1114)
• Linter: micar-whitepaper-linter (36 rules mapped to Annex I–III) · Classifier: eu-ai-act-classifier — both MIT-licensed
• Development and tests: docs/development.md

Part of the EU regulation as code suite

By sebastianfoerste:

• awesome-eu-fintech-regulation
• contract-review-eval-harness
• legal-function-operating-system
• eu-ai-act-classifier
• micar-whitepaper-linter
• eu-reg-mcp (this repo)
• micar-register-observatory

Caveats

Register results are public-register facts with extraction artifacts possible; lint and classification outputs are candidate flags pending human legal review. Nothing here is legal advice. MIT licensed.