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CSOAI-ORG

GDPR Compliance for AI Systems MCP Server

crosswalk_to_eu_ai_act

Map GDPR requirements to EU AI Act obligations. Determine where GDPR compliance satisfies, complements, or conflicts with AI Act requirements for EU AI deployments.

Instructions

Map GDPR requirements to EU AI Act obligations. Shows where GDPR compliance satisfies, complements, or creates tension with EU AI Act requirements. Essential for organizations deploying AI in the EU that must comply with both regulations simultaneously.

Args:
    gdpr_articles: Specific GDPR articles to map (or all if omitted)
    focus_area: Focus on "all", "transparency", "automated_decisions", "data_governance", or "risk"
    caller: Caller identifier for rate limiting
    tier: Access tier (free/pro)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gdpr_articlesNo
focus_areaNoall
callerNoanonymous
tierNofree
api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'crosswalk_to_eu_ai_act' tool. Maps GDPR requirements to EU AI Act obligations using the GDPR_EU_AI_ACT_CROSSWALK dictionary, with filtering by specific GDPR articles or focus area (transparency, automated_decisions, data_governance, risk). Returns mappings with alignment assessment (strong, complementary, tension, partial) and key findings.
    @mcp.tool()
    def crosswalk_to_eu_ai_act(
        gdpr_articles: Optional[list[str]] = None,
        focus_area: str = "all",
        caller: str = "anonymous",
        tier: str = "free", api_key: str = "") -> str:
        """Map GDPR requirements to EU AI Act obligations. Shows where GDPR
        compliance satisfies, complements, or creates tension with EU AI Act
        requirements. Essential for organizations deploying AI in the EU that
        must comply with both regulations simultaneously.
    
        Args:
            gdpr_articles: Specific GDPR articles to map (or all if omitted)
            focus_area: Focus on "all", "transparency", "automated_decisions", "data_governance", or "risk"
            caller: Caller identifier for rate limiting
            tier: Access tier (free/pro)
        """
        allowed, msg, tier = check_access(api_key)
        if not allowed:
            return {"error": msg, "upgrade_url": "https://meok.ai/pricing"}
        if err := _check_rate_limit(caller, tier):
            return {"error": err}
    
        focus_filters = {
            "transparency": ["Art.13_14_transparency", "Art.22_automated"],
            "automated_decisions": ["Art.22_automated"],
            "data_governance": ["Art.5_principles", "Art.6_lawfulness", "Art.9_special_categories"],
            "risk": ["Art.35_dpia", "Art.33_breach", "Art.25_by_design"],
        }
    
        if gdpr_articles:
            target_keys = [k for k in GDPR_EU_AI_ACT_CROSSWALK if any(a.replace(".", "") in k for a in gdpr_articles)]
        elif focus_area in focus_filters:
            target_keys = focus_filters[focus_area]
        else:
            target_keys = list(GDPR_EU_AI_ACT_CROSSWALK.keys())
    
        mappings = []
        strong = 0
        complementary = 0
        tension = 0
        partial = 0
    
        for key in target_keys:
            if key not in GDPR_EU_AI_ACT_CROSSWALK:
                continue
            xw = GDPR_EU_AI_ACT_CROSSWALK[key]
            mappings.append({
                "mapping_id": key,
                "gdpr_article": xw["gdpr"],
                "eu_ai_act_article": xw["eu_ai_act"],
                "alignment": xw["alignment"],
                "analysis": xw["note"],
            })
            if xw["alignment"] == "strong":
                strong += 1
            elif xw["alignment"] == "complementary":
                complementary += 1
            elif xw["alignment"] == "tension":
                tension += 1
            else:
                partial += 1
    
        result = {
            "crosswalk_type": "GDPR to EU AI Act Regulatory Crosswalk",
            "timestamp": datetime.now(timezone.utc).isoformat(),
            "focus_area": focus_area,
            "mappings": mappings,
            "summary": {
                "total_mappings": len(mappings),
                "strong_alignment": strong,
                "complementary": complementary,
                "tension_points": tension,
                "partial": partial,
            },
            "key_findings": [
                "GDPR and EU AI Act are designed to work together — most obligations are complementary",
                "Article 10(5) EU AI Act creates a specific pathway for processing special categories for AI bias detection, partially derogating from GDPR Article 9",
                "GDPR DPIA and EU AI Act fundamental rights impact assessment can be conducted as integrated assessment",
                "Organizations already GDPR-compliant have a strong foundation for EU AI Act compliance",
                "Key tension: EU AI Act may require data retention for AI monitoring that conflicts with GDPR storage limitation",
            ],
            "recommendation": (
                "Conduct an integrated compliance programme covering both GDPR and EU AI Act. "
                "Use GDPR DPIA as foundation for EU AI Act fundamental rights impact assessment. "
                "Pay special attention to Article 9/10(5) tension regarding bias monitoring data."
            ),
        }
    
        return result
  • server.py:1027-1028 (registration)
    The tool is registered via the @mcp.tool() decorator on the FastMCP instance named 'mcp' (line 62), which automatically registers it as an MCP tool named 'crosswalk_to_eu_ai_act'.
    @mcp.tool()
    def crosswalk_to_eu_ai_act(
  • Input schema/parameters for the tool: gdpr_articles (optional list of GDPR articles), focus_area (with choices all/transparency/automated_decisions/data_governance/risk), caller, tier, and api_key for auth.
    def crosswalk_to_eu_ai_act(
        gdpr_articles: Optional[list[str]] = None,
        focus_area: str = "all",
        caller: str = "anonymous",
        tier: str = "free", api_key: str = "") -> str:
        """Map GDPR requirements to EU AI Act obligations. Shows where GDPR
        compliance satisfies, complements, or creates tension with EU AI Act
        requirements. Essential for organizations deploying AI in the EU that
        must comply with both regulations simultaneously.
    
        Args:
            gdpr_articles: Specific GDPR articles to map (or all if omitted)
            focus_area: Focus on "all", "transparency", "automated_decisions", "data_governance", or "risk"
            caller: Caller identifier for rate limiting
            tier: Access tier (free/pro)
        """
  • The GDPR_EU_AI_ACT_CROSSWALK dictionary containing the mapping data between GDPR articles and EU AI Act articles, used by the crosswalk_to_eu_ai_act handler.
    GDPR_EU_AI_ACT_CROSSWALK = {
        "Art.5_principles": {
            "gdpr": "Article 5 — Data protection principles",
            "eu_ai_act": "Article 10 — Data and data governance",
            "alignment": "strong",
            "note": "GDPR data quality principles (accuracy, minimisation) directly map to EU AI Act data governance requirements for training, validation and testing datasets.",
        },
        "Art.6_lawfulness": {
            "gdpr": "Article 6 — Lawful basis for processing",
            "eu_ai_act": "Article 10(2) — Training data requirements",
            "alignment": "complementary",
            "note": "EU AI Act requires lawful data collection for training sets. GDPR lawful basis is a prerequisite for compliant AI training data.",
        },
        "Art.9_special_categories": {
            "gdpr": "Article 9 — Special categories of data",
            "eu_ai_act": "Article 10(5) — Processing of special categories for bias detection",
            "alignment": "tension",
            "note": "EU AI Act Article 10(5) explicitly permits processing special categories for bias monitoring, creating a specific derogation pathway from GDPR Article 9 restrictions. Requires strict safeguards.",
        },
        "Art.13_14_transparency": {
            "gdpr": "Articles 13-14 — Transparency obligations",
            "eu_ai_act": "Article 13 — Transparency and information to deployers",
            "alignment": "strong",
            "note": "Both require transparency about AI processing. EU AI Act adds technical documentation and instructions for use. GDPR focuses on individual notice.",
        },
        "Art.22_automated": {
            "gdpr": "Article 22 — Automated decision-making",
            "eu_ai_act": "Article 14 — Human oversight, Article 26(3) — Deployer obligations",
            "alignment": "strong",
            "note": "GDPR Article 22 right to human intervention aligns with EU AI Act human oversight requirements. EU AI Act goes further requiring human oversight by design.",
        },
        "Art.25_by_design": {
            "gdpr": "Article 25 — Data protection by design and by default",
            "eu_ai_act": "Article 9 — Risk management system",
            "alignment": "complementary",
            "note": "Privacy-by-design aligns with EU AI Act risk management. Both require proactive measures. EU AI Act extends to broader AI risks beyond data protection.",
        },
        "Art.35_dpia": {
            "gdpr": "Article 35 — Data Protection Impact Assessment",
            "eu_ai_act": "Article 27 — Fundamental rights impact assessment",
            "alignment": "strong",
            "note": "GDPR DPIA maps to EU AI Act fundamental rights impact assessment. Organizations deploying high-risk AI may satisfy both through an integrated assessment.",
        },
        "Art.33_breach": {
            "gdpr": "Article 33 — Notification to supervisory authority",
            "eu_ai_act": "Article 62 — Reporting of serious incidents",
            "alignment": "complementary",
            "note": "GDPR 72-hour breach notification requirement parallels EU AI Act serious incident reporting. AI incidents may trigger both notification obligations simultaneously.",
        },
        "Art.44_transfers": {
            "gdpr": "Articles 44-49 — International transfers",
            "eu_ai_act": "Article 2(7) — Territorial scope",
            "alignment": "partial",
            "note": "GDPR international transfer rules affect AI systems processing EU personal data abroad. EU AI Act has its own territorial scope covering AI systems placed on EU market.",
        },
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description does not disclose behavioral traits such as side effects, required permissions, performance implications, or rate limits. For a tool with no annotations, the description carries the full burden, but it only covers purpose and parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a two-paragraph format: purpose first, then parameter documentation. It is front-loaded and efficient, though the Args block could be slightly more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has an output schema (details not provided), and the description explains the main purpose and key parameters. However, it lacks behavioral details and misses the 'api_key' parameter in its description. For a regulatory mapping tool, more guidance on expected outputs or edge cases would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It includes an Args block explaining 'gdpr_articles' and 'focus_area' with some detail, but 'caller' and 'tier' are minimally described, and 'api_key' is missing from the Args block despite being in the schema. Thus, it adds value but is incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states what the tool does: map GDPR requirements to EU AI Act obligations, specifying it shows where compliance satisfies, complements, or creates tension. This verb+resource+distinction clearly differentiates it from sibling tools like breach_notification or dpia_generator.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states it is 'essential for organizations deploying AI in the EU that must comply with both regulations simultaneously,' which indicates when to use. However, it does not provide explicit when-not-to-use or compare to alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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