Regulatory Change Intelligence MCP Server

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Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf):

{
  "mcpServers": {
    "regulatory-change-intelligence-mcp": {
      "url": "https://ryanclinton--regulatory-change-intelligence-mcp.apify.actor/mcp"
    }
  }
}

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Regulatory change intelligence across 13 US federal data sources, delivered as an MCP server your AI agent can query directly. Built for compliance officers, GRC teams, and trade compliance operations who need forward-looking signals — not just a list of current rules. The server produces a composite Compliance Impact Score (0-100) backed by four scoring sub-models: Legislative Probability, Enforcement Trend, Tariff Impact, and Regulatory Domino Effect.

Rather than manually parsing the Federal Register, checking OSHA inspection databases, and cross-referencing CBP customs rulings every week, you send a single tool call and receive a scored, structured assessment. The server runs up to 13 Apify actors in parallel across congressional bill databases, agency enforcement records, trade tariff schedules, lobbying disclosure filings, and FEC campaign finance data — then applies weighted scoring models to surface what actually matters to your compliance program.

⬇️ What data can you access?

| Data Point | Source | Example |
|---|---|---|
| 📋 Proposed rules, final rules, executive orders | Federal Register | "EPA proposes new PFAS limits under SDWA" |
| 📜 Bill stage tracking, co-sponsors, committee activity | Congress Bills | HR 4821 — Advanced Manufacturing Act, Referred to Committee |
| 🛃 Tariff classification rulings | CBP Customs Rulings | HQ H321445 — classification of lithium battery modules |
| 📊 HTS duty rates, trade remedies, Section 301 lists | USITC HTS Tariff | HTS 8507.60.00 — 25% ad valorem duty |
| 🏦 SEC filings, 10-K risk disclosures, enforcement orders | SEC EDGAR | Form 8-K — material regulatory development disclosed |
| 🦺 Workplace safety inspections, citations, penalties | OSHA | Inspection 1234567 — $78,000 penalty, willful violation |
| 🌿 Environmental enforcement actions, permits, violations | EPA ECHO | Facility TXR000012 — NOV issued, penalty assessment pending |
| 👷 Wage-hour audits, back-wage findings, debarments | DOL WHD | Establishment: Pinnacle Staffing LLC — $142,000 back wages |
| 🍽️ Food and drug recall actions, voluntary/mandatory | FDA Recalls | Class I Recall — Allergen labeling violation, lot B-2291 |
| 🏥 Medical device enforcement, premarket notifications | FDA Devices | 510(k) K243018 — cleared with special controls |
| 🖥️ Agency website guidance changes, policy updates | Website Change Monitor | hhs.gov/guidance updated — new compliance Q&A posted |
| 🗣️ Lobbying registrations, issue areas, expenditures | Senate Lobbying | Acme Pharma Corp — $1.2M lobbying on drug pricing bills |
| 💰 Political contribution patterns by industry/sector | FEC Campaign Finance | PAC contributions correlated with pending trade legislation |

Why use the Regulatory Change Intelligence MCP Server?

Compliance teams at mid-market and enterprise companies spend 8-15 hours per week across analyst roles just scanning the Federal Register, checking agency enforcement feeds, and tracking bills through committee. That process misses cross-agency signals — an EPA enforcement surge often precedes OSHA inspections at the same facility type, and a cluster of lobbying filings around a regulatory topic frequently predicts rulemaking within 6-12 months. Manual scanning cannot detect those correlations.

This MCP server automates the entire intelligence gathering and correlation layer. Your AI agent calls a single tool — compliance_impact_report — and receives a scored assessment with sub-model breakdowns and a plain-language recommendation, drawn from simultaneous queries across all 13 data sources.

Beyond the intelligence itself, running this server on the Apify platform means:

- Scheduling — run weekly scans on your priority regulatory topics and receive fresh scores automatically
- API access — trigger assessments from Python, JavaScript, n8n, or any HTTP client that supports MCP
- Proxy rotation — Apify's built-in proxy infrastructure ensures reliable access to all 13 source APIs
- Monitoring — configure Slack or email alerts when a Compliance Impact Score crosses a threshold
- Integrations — connect to Zapier, Make, webhooks, or push results directly to your GRC platform

Features

- 4-model scoring engine producing a composite Compliance Impact Score (0-100) with per-model breakdowns and a letter-grade equivalent (LOW / MODERATE / HIGH / CRITICAL COMPLIANCE RISK)
- Legislative Probability Engine (0-100) classifies bills across 4 pipeline stages — introduced, committee, passed, enacted — and weights passage probability against Federal Register rulemaking volume and lobbying intensity
- Enforcement Trend Detector (0-100) aggregates active enforcement records from OSHA, EPA ECHO, DOL WHD, FDA, and SEC, identifying DORMANT / MODERATE / ACTIVE / INTENSIFYING enforcement directions
- Tariff Impact Analyzer (0-100) scores trade policy disruption from CBP customs rulings, USITC HTS duty rate data, and trade-related Federal Register entries, with labeling from MINIMAL IMPACT through HIGH DISRUPTION
- Regulatory Domino Effect model (-100 to +100) measures cross-agency cascade potential by detecting when 3+ agencies show correlated enforcement activity in the same sector — the strongest signal of a coordinated regulatory campaign
- Weighted composite formula: Legislative Probability (30%) + Enforcement Trend (30%) + Domino Effect normalized (25%) + Tariff Impact (15%)
- Parallel actor execution — up to 13 data source actors run simultaneously, reducing total wall-clock time versus serial queries
- 8 MCP tools covering the full regulatory intelligence stack from pipeline search through full compliance impact reporting
- Sub-regulatory guidance monitoring via website change detection on agency domains — catches guidance documents and advisory opinions that change compliance requirements without formal rulemaking
- Lobbying pressure mapping correlates Senate lobbying filings and FEC contribution patterns with specific regulatory topics to surface industry influence on pending rules

Use cases for regulatory change intelligence

Compliance officer early-warning monitoring

Compliance officers at publicly traded companies need 3-12 months of advance notice on rules that affect their regulated activities. The regulatory_pipeline_search tool scans the Federal Register for proposed rules during their comment period and correlates them with bill activity in Congress. You get actionable signals before rules take effect — not after.

GRC team resource prioritization

Governance, Risk, and Compliance teams cannot respond equally to every Federal Register entry. The compliance_impact_report produces a scored rank across regulatory topics so teams allocate attention proportionally. A topic scoring 78 (CRITICAL) gets immediate attention; one scoring 22 (LOW) gets a quarterly review.

Trade compliance and tariff risk management

Import/export operations monitor CBP customs ruling changes because a reclassification of an HTS code can double landed costs overnight. The tariff_trade_impact tool tracks CBP rulings, USITC HTS duty rate changes, and trade-related legislation simultaneously. Procurement and trade compliance teams use this to anticipate duty exposure before purchase orders are placed.

Cross-agency enforcement pattern analysis

The cross_agency_domino_forecast is designed for industries that operate under multiple simultaneous regulatory regimes — chemicals, food manufacturing, healthcare, financial services. When EPA enforcement in a sector accelerates, OSHA often follows within months. The domino model quantifies that cascade risk before the second agency acts.

Lobbying intelligence for public affairs teams

Government affairs and public affairs teams use the lobbying_pressure_map to understand who is spending on which regulatory topics, and whether that spending correlates with FEC contribution patterns targeting key committee members. This surfaces the political economy around a regulation — not just its text.

Sub-regulatory guidance tracking

Federal agencies change compliance requirements without formal notice-and-comment rulemaking through guidance documents, FAQs, and policy interpretations posted to their websites. The agency_guidance_monitor tool detects changes to federal agency web pages and correlates them with Federal Register activity — catching informal compliance shifts before they become enforcement actions.

How to use the Regulatory Change Intelligence MCP Server

1. Connect the MCP server — Add the server URL https://regulatory-change-intelligence-mcp.apify.actor/mcp to your MCP client (Claude Desktop, Cursor, Windsurf, or any MCP-compatible tool). Authenticate with your Apify API token.
2. Choose your tool — For a quick scan of a regulatory topic, start with regulatory_pipeline_search. For a full scored assessment across all 13 sources, use compliance_impact_report.
3. Provide a query — Pass a regulatory topic, industry, company name, HTS code, or agency name. Example: "PFAS water contamination", "pharmaceutical drug pricing", "Section 301 tariffs solar panels".
4. Review the scored output — The server returns a Compliance Impact Score, sub-model breakdowns, active agencies, legislative pipeline stage counts, and a plain-language recommendation. Most tools complete in 30-90 seconds.

MCP tools

| Tool | Price | Description |
|------|-------|-------------|
| regulatory_pipeline_search | $0.045 | Search Federal Register and Congress for pending regulatory changes and proposed rules |
| bill_impact_assessment | $0.045 | Assess legislative probability using lobbying pressure alignment and FEC contribution data |
| enforcement_trend_analysis | $0.045 | Detect enforcement acceleration across OSHA, EPA, DOL WHD, FDA, and SEC |
| tariff_trade_impact | $0.045 | Analyze tariff and trade policy impacts via CBP customs rulings and USITC HTS data |
| lobbying_pressure_map | $0.045 | Map lobbying pressure and political expenditure patterns by industry and regulatory topic |
| agency_guidance_monitor | $0.045 | Monitor agency website changes and Federal Register for sub-regulatory guidance updates |
| cross_agency_domino_forecast | $0.045 | Predict regulatory cascade effects when enforcement in one agency signals action from others |
| compliance_impact_report | $0.045 | Comprehensive compliance assessment across all 13 sources with composite Compliance Impact Score |

Connection examples

Claude Desktop — claude_desktop_config.json:

{

  "mcpServers": {

    "regulatory-change-intelligence": {

      "url": "https://regulatory-change-intelligence-mcp.apify.actor/mcp",

      "headers": {

        "Authorization": "Bearer YOUR_APIFY_TOKEN"

      }

    }

  }

}

Cursor / Windsurf / Cline — MCP config:

{

  "mcpServers": {

    "regulatory-change-intelligence": {

      "url": "https://regulatory-change-intelligence-mcp.apify.actor/mcp",

      "headers": {

        "Authorization": "Bearer YOUR_APIFY_TOKEN"

      }

    }

  }

}

cURL — direct tool call:

curl -X POST "https://regulatory-change-intelligence-mcp.apify.actor/mcp" \

  -H "Content-Type: application/json" \

  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \

  -d '{

    "jsonrpc": "2.0",

    "method": "tools/call",

    "params": {

      "name": "compliance_impact_report",

      "arguments": {

        "query": "PFAS water contamination regulation"

      }

    },

    "id": 1

  }'

⬆️ Output example

{
  "query": "pharmaceutical drug pricing regulation",
  "complianceImpactScore": {
    "total": 74,
    "grade": "HIGH COMPLIANCE RISK",
    "recommendation": "Active regulatory environment. Monitor legislative pipeline and enforcement trends. Update compliance programs proactively."
  },
  "legislativeProbability": {
    "score": 68,
    "label": "LIKELY",
    "billStages": {
      "introduced": 9,
      "committee": 5,
      "passed": 2,
      "enacted": 0
    },
    "findings": [
      "2 bill(s) passed at least one chamber — high probability of enactment",
      "5 bills in committee — significant legislative attention",
      "9 introduced bills — building legislative momentum",
      "18 proposed/final rules in Federal Register — active rulemaking",
      "24 lobbying filings — high industry engagement"
    ]
  },
  "enforcementTrend": {
    "score": 58,
    "direction": "INTENSIFYING",
    "agencyActivity": {
      "FDA": 22,
      "DOL-WHD": 4,
      "SEC": 7
    },
    "findings": [
      "22 FDA recall/enforcement actions — heavy product safety enforcement",
      "4 DOL WHD enforcement action(s)",
      "7 SEC filing(s) — financial regulatory activity",
      "12 enforcement-related Federal Register notice(s)",
      "3 agencies actively enforcing — multi-front regulatory pressure"
    ]
  },
  "tariffImpact": {
    "score": 18,
    "label": "LOW DISRUPTION",
    "findings": [
      "2 CBP customs ruling(s)",
      "6 trade-related Federal Register notice(s)",
      "3 trade-related bill(s) in Congress"
    ]
  },
  "dominoEffect": {
    "score": 42,
    "direction": "EXPANDING",
    "activeAgencies": ["FDA", "SEC", "DOL-WHD"],
    "findings": [
      "3 agencies with active enforcement — moderate cascade potential",
      "Active agencies: FDA, SEC, DOL-WHD",
      "18 Federal Register entries — regulatory momentum building",
      "16 congressional bills — legislative pressure amplifies regulatory cascade"
    ]
  },
  "sourceCounts": {
    "federalRegisterEntries": 18,
    "congressBills": 16,
    "cbpRulings": 2,
    "usitcTariffEntries": 0,
    "secFilings": 7,
    "oshaInspections": 0,
    "epaEnforcement": 0,
    "dolWhdActions": 4,
    "fdaRecalls": 14,
    "fdaDevices": 8,
    "websiteChanges": 3,
    "lobbyingFilings": 24,
    "fecContributions": 11
  }
}

Output fields

| Field | Type | Description |
|---|---|---|
| query | string | The regulatory topic queried |
| complianceImpactScore.total | number (0-100) | Weighted composite Compliance Impact Score |
| complianceImpactScore.grade | string | LOW / MODERATE / HIGH / CRITICAL COMPLIANCE RISK |
| complianceImpactScore.recommendation | string | Plain-language action recommendation |
| legislativeProbability.score | number (0-100) | Likelihood of legislative passage |
| legislativeProbability.label | string | UNLIKELY / POSSIBLE / LIKELY / NEAR CERTAIN |
| legislativeProbability.billStages | object | Count of bills at each pipeline stage |
| legislativeProbability.findings | string[] | Evidence statements supporting the score |
| enforcementTrend.score | number (0-100) | Current enforcement intensity score |
| enforcementTrend.direction | string | DORMANT / MODERATE / ACTIVE / INTENSIFYING |
| enforcementTrend.agencyActivity | object | Record count per active agency |
| enforcementTrend.findings | string[] | Evidence statements per agency |
| tariffImpact.score | number (0-100) | Trade policy disruption score |
| tariffImpact.label | string | MINIMAL IMPACT / LOW / MODERATE / HIGH DISRUPTION |
| tariffImpact.findings | string[] | CBP rulings, HTS entries, trade-related notices |
| dominoEffect.score | number (-100 to +100) | Cross-agency cascade potential |
| dominoEffect.direction | string | CONTRACTING / STABLE / EXPANDING / CASCADING EXPANSION |
| dominoEffect.activeAgencies | string[] | Agencies with active enforcement above threshold |
| dominoEffect.findings | string[] | Cross-agency correlation evidence |
| sourceCounts | object | Raw record count from each of the 13 data sources |

How much does it cost to run regulatory change intelligence?

This MCP uses pay-per-event pricing — you pay $0.045 per tool call. Platform compute costs are included.

| Scenario | Tool calls | Cost per call | Total cost |
|----------|-----------|---------------|------------|
| Quick test — single pipeline search | 1 | $0.045 | $0.045 |
| Weekly monitoring — 3 topics | 3 | $0.045 | $0.14 |
| Monthly GRC review — 5 topics, full reports | 5 | $0.045 | $0.23 |
| Quarterly compliance audit — 20 assessments | 20 | $0.045 | $0.90 |
| Enterprise — daily monitoring, 100 topics/month | 100 | $0.045 | $4.50 |

You can set a maximum spending limit per run to control costs. The actor stops when your budget is reached.

Apify's free tier includes $5 of monthly platform credits — enough for over 100 tool calls per month at no cost. Compare this to dedicated RegTech platforms (Lexis+ Regulatory Tracker, Compliance.ai, RegData) at $500-2,500/month — with this MCP, most compliance teams spend under $10/month with no subscription commitment.

How to use the Regulatory Change Intelligence MCP Server via the API

Python

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("ryanclinton/regulatory-change-intelligence-mcp").call(run_input={})