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Why this exists

The EU AI Act is live and has teeth:

• Feb 2025 — prohibited practices enforceable. €35M or 7% of global turnover.
• Aug 2025 — GPAI model obligations active.
• Aug 2026 — transparency requirements apply.
• Dec 2027 — high-risk (Annex III) obligations due.

Most teams have no idea which tier they're in. This gives you a grounded first pass in seconds, inside the agent you already use — with a citation for every claim so you can verify it.

⚠️ Informational triage, not legal advice. Confirm classifications with qualified counsel.

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Tools

Four tools exposed to any MCP-compatible agent (Claude Code, Cursor, Claude Desktop, Windsurf, Cline, …):

Tool	What it answers
classify_risk	"Is my system prohibited / high-risk / limited / minimal?" — with Annex III category + article citations
check_obligations	"Given my tier and role (provider or deployer), what must I do?" — obligation by obligation, with the specific deadline
next_deadlines	"When does this apply to me?" — the staggered 2025–2028 enforcement timeline
scan_repo	"Which compliance artifacts am I missing?" — pass / warn / fail checklist against your actual repo

The rules live in a single versioned, citation-backed file: rules/ruleset.json. It reflects Regulation (EU) 2024/1689 as amended by the May 2026 Digital Omnibus agreement, and is date-stamped so you always know how current it is.

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Install

Option A — npx (zero install, once published to npm)

{
  "mcpServers": {
    "ai-act": {
      "command": "npx",
      "args": ["-y", "ai-act-mcp"]
    }
  }
}

Option B — clone and build

git clone https://github.com/a2welt/ai-act-mcp
cd ai-act-mcp
npm install && npm run build

{
  "mcpServers": {
    "ai-act": {
      "command": "node",
      "args": ["/absolute/path/to/ai-act-mcp/dist/index.js"]
    }
  }
}

Client config locations:

Client	File
Claude Desktop	~/Library/Application Support/Claude/claude_desktop_config.json (macOS) · %APPDATA%\Claude\claude_desktop_config.json (Windows)
Claude Code	.mcp.json in project root, or claude mcp add ai-act node /path/to/dist/index.js
Cursor	.cursor/mcp.json
Windsurf	~/.codeium/windsurf/mcp_config.json

Restart your agent and ask: "Classify my hiring tool under the EU AI Act."

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Fully offline — Ollama

Your AI-system description is exactly the kind of proprietary text you should not send to a cloud service. Run classification on a small local model instead — nothing leaves your machine:

# 1. Pull a model (any small instruct model works)
ollama pull llama3.2

# 2. Test it from your terminal (builds a vivid picture of what the tool does)
node demo/test-local.mjs

# 3. Register with your agent using the local backend

{
  "mcpServers": {
    "ai-act": {
      "command": "node",
      "args": ["/absolute/path/to/ai-act-mcp/dist/index.js"],
      "env": {
        "AI_ACT_CLASSIFIER": "local",
        "AI_ACT_SLM_MODEL": "llama3.2"
      }
    }
  }
}

The model only ever picks among the ruleset's enumerated, cited categories — it never invents law. This is what makes a small model reliable: you've constrained its job to classification-against-known-rules, not open-ended legal reasoning. If the model is unreachable for any reason, the server falls back to the deterministic keyword screen automatically.

Backend options

AI_ACT_CLASSIFIER	Where the description goes	Quality	Notes
keyword (default)	Nowhere — pure local logic	Good	Instant, zero dependencies, deterministic
local	Stays on your machine (Ollama)	Better	Privacy-first; requires Ollama running
host	Your agent's model via MCP sampling	Best	Requires client sampling support

Extra env vars for local mode:

Variable	Default	Description
AI_ACT_SLM_MODEL	llama3.2	Any model name Ollama has pulled
AI_ACT_OLLAMA_URL	http://localhost:11434	Ollama server URL
AI_ACT_SLM_TIMEOUT_MS	30000	Timeout before falling back to keyword

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Example

Prompt: I'm building a tool that screens job applicants' CVs and ranks them. Classify it under the EU AI Act.

# AI Act risk classification

**Likely tier: High-risk** (Art. 6 + Annex I / Annex III)

Permitted but subject to the heaviest obligations (risk management, data
governance, logging, human oversight, conformity assessment, registration).

## ⚠️ Possible high-risk categories (Annex III)
- **Employment**: recruitment, screening, filtering applications, evaluating
  candidates, or decisions on promotion/termination/task allocation — Annex III(4)

> Check the Art. 6(3) exemption: system does NOT pose a significant risk of harm
  to health, safety or fundamental rights…

## What to do next
Run `check_obligations` with tier "high" and your role (provider or deployer)
for the full obligation list, and `next_deadlines` for your timeline.

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Ruleset 2026.06 (current as of 2026-06-09). Informational triage only.
Not legal advice. Verify against the official text and consult qualified counsel.

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Run the tests

npm test

15 tests covering classification, obligations, deadlines, repo scanning, all three classifier backends, and the offline fallback path.

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Roadmap

• Four core tools — classify, obligations, deadlines, repo scan
• Versioned, citation-backed ruleset (rules/ruleset.json)
• Pass / warn / fail repo artifact checklist
• Per-tier deadlines in obligation output
• Pluggable classifier backends — keyword (default), local SLM (fully offline via Ollama), host-model sampling
• npm publish — zero-install npx setup
• FRIA (fundamental rights impact assessment) scaffold generator
• GPAI Code of Practice checklist
• Ruleset auto-update workflow as Omnibus amendments are adopted

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Contributing

Corrections to the ruleset — with article citations — are the most valuable contributions. See CONTRIBUTING.md for the full guide.

Quick ways to help:

• 🔍 Found a wrong classification? Open a ruleset correction issue
• 🐛 Something broken? Open a bug report
• ⭐ Find it useful? Star the repo — it helps compliance teams discover it

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License

MIT — see LICENSE