Nuclear Regulatory Intelligence MCP Server

Nuclear regulatory intelligence for plant operators, insurers, decommissioning firms, and environmental analysts — delivered as a Model Context Protocol server your AI agent can call directly. This MCP server queries 8 live government data sources in parallel, scores every dimension of nuclear risk, and returns a Composite Nuclear Risk Score (0-100) with supporting signals and recommendations.

The server exposes 8 tools covering plant risk assessment, seismic vulnerability, NRC compliance tracking, decommissioning timelines, environmental contamination, waste facility screening, plant benchmarking, and regional exposure analysis. Data is fetched live from Federal Register, USGS, FEMA, NOAA, OpenAQ, Data.gov, OpenCorporates, and the Congress bill tracker — no stale databases, no subscriptions.

What data can you access?

Why use Nuclear Regulatory Intelligence MCP?

Assembling a nuclear risk picture manually means searching Federal Register for NRC enforcement orders, querying USGS for regional seismic history, pulling FEMA disaster declarations, checking OpenAQ air quality readings, and verifying operator corporate structures — each from a separate interface, none of them connected. Analysts at nuclear insurers and environmental law firms report spending 6-10 hours per facility on basic due diligence this way.

This MCP server wires all 8 sources into a single API call. Your AI agent asks one question; 8 actors run in parallel; a multi-model scoring engine weighs the results and returns a structured risk assessment in seconds.

• Scheduling — run daily seismic or regulatory monitoring on recurring schedules without manual intervention
• API access — trigger assessments from any MCP-compatible client, Python script, or CI/CD pipeline
• Parallel execution — all 8 data sources are queried simultaneously, not sequentially
• Spending controls — per-run budget limits prevent runaway costs during automated monitoring
• Integrations — connect results to Slack alerts, Google Sheets dashboards, or CRM systems via Apify webhooks

Features

• Composite Nuclear Risk Score (0-100) — weighted combination of seismic vulnerability (30%), regulatory compliance (30%), environmental contamination (25%), and operator transparency (15%)
• Plant Proximity Risk Index — seismic scoring awards up to 15 points per M6.0+ event, 6 points per M4.0+ event, with compound hazard bonuses when earthquake + flood events converge (Fukushima-type scenario detection)
• Regulatory Compliance Score — scans Federal Register for 15 nuclear-specific keywords including reactor, criticality, coolant, containment, and decommission; emergency NRC actions score 12 points each
• Environmental Contamination model — monitors 10 nuclear waste keywords (spent fuel, high-level, transuranic, Yucca, dry cask) against Federal Register and Data.gov records; emergency waste/contamination actions score 12 points each
• Operator Transparency Rating — maps corporate structure via OpenCorporates, penalising multi-jurisdiction holding chains, dissolved entities, and operators with no verifiable registry presence
• 8 tools for targeted queries — run the full plant_risk_assessment or call focused tools like seismic_vulnerability_check and waste_facility_screening to minimise cost
• Named signal generation — every score elevation produces a human-readable signal string (e.g., "M6.2 earthquake — exceeds design basis for many reactors") not just a number
• Actionable recommendations — five recommendation rules fire when threshold combinations are breached, from design basis reassessment to emergency response triggers
• Standby mode deployment — MCP server stays live between requests on Apify's standby infrastructure with no cold-start latency for interactive AI sessions
• Spending limit enforcement — each tool call checks against the configured spend cap before executing, returning a structured error if the limit is reached

Use cases for nuclear regulatory intelligence

Nuclear insurance underwriting

Insurers and reinsurers pricing nuclear facilities need a single risk metric across seismic exposure, regulatory history, and operator quality. The plant_risk_assessment tool returns a Composite Nuclear Risk Score with dimensional breakdowns that map directly to underwriting criteria. A score of 67 (HIGH_RISK) with seismic signals near Diablo Canyon feeds directly into premium calculations without manual data assembly.

NRC compliance monitoring for plant operators

Regulatory affairs teams at nuclear utilities track Federal Register enforcement orders, license amendments, and safety evaluations on a rolling basis. The regulatory_compliance_tracker tool surfaces NRC actions alongside congressional nuclear bills, giving compliance officers early warning of legislative pressure before formal enforcement escalates. Emergency NRC actions are flagged immediately with a 12-point score uplift.

Decommissioning project planning

Decommissioning contractors and waste management firms tracking regulatory milestones for facilities like Indian Point or Pilgrim need a consolidated view of regulatory progress, waste management activity, and site remediation status. The decommissioning_timeline tool queries Federal Register for decommission-specific actions and Data.gov for spent fuel and waste management datasets, returning both a compliance level (EXEMPLARY through ENFORCEMENT) and a contamination level (CLEAN through HAZARDOUS).

Environmental impact assessment and litigation support

Environmental attorneys and NGOs conducting impact assessments near nuclear facilities combine air quality data, waste regulatory actions, and contamination indicators from Data.gov. The environmental_contamination_risk tool runs OpenAQ, Federal Register waste searches, and radiation dataset queries in a single call, returning an EnvironmentalContaminationResult with AQI-derived scores and waste indicator counts suitable for filing in regulatory proceedings.

State energy and emergency management planning

State agencies assessing their regional nuclear exposure need a view across all plants, seismic zones, and the regulatory landscape simultaneously. The regional_nuclear_exposure tool runs all 8 data sources against a state or region name, returning the same full NuclearIntelResult structure used for individual plants — applicable to statewide emergency planning, grid reliability reviews, or public comment on new reactor licensing.

Seismic hazard re-evaluation

Following a significant earthquake or in response to updated USGS probabilistic seismic hazard maps, site engineers need rapid assessments of recent seismic history. The seismic_vulnerability_check tool queries USGS, FEMA, and NOAA in parallel, scoring M4.0+ events (significantQuakes threshold), M6.0+ events (majorQuakes threshold), and compound hazards involving both seismic and weather events at the same location.

How to use the Nuclear Regulatory Intelligence MCP

1. Connect your MCP client — Add the server URL to Claude Desktop, Cursor, Windsurf, or any MCP-compatible client. No API key is required for the connection endpoint itself; billing is handled by your Apify token.
2. Configure your Apify token — Pass Authorization: Bearer YOUR_APIFY_TOKEN in the request header so the server can charge tool events to your account and call sub-actors on your behalf.
3. Call a tool — Ask your AI agent "Assess nuclear risk for Diablo Canyon, California" or call plant_risk_assessment directly with plant: "Diablo Canyon" and region: "California".
4. Read the structured result — The server returns a JSON object with compositeScore, verdict, four dimensional sub-scores, allSignals, and recommendations. A verdict of ELEVATED or above includes specific action signals.

MCP tools

Connection configuration

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "nuclear-regulatory-intelligence": {
      "url": "https://nuclear-regulatory-intelligence-mcp.apify.actor/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
      }
    }
  }
}

Cursor / Windsurf / Cline — point your MCP client to:

https://nuclear-regulatory-intelligence-mcp.apify.actor/mcp

Direct HTTP call:

curl -X POST https://nuclear-regulatory-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":"plant_risk_assessment","arguments":{"plant":"Diablo Canyon","region":"California"}},"id":1}'

Output example

A plant_risk_assessment call for "Diablo Canyon, California" returns:

{
  "entity": "Diablo Canyon",
  "compositeScore": 71,
  "verdict": "HIGH_RISK",
  "plantProximity": {
    "score": 78,
    "seismicEvents": 14,
    "significantQuakes": 6,
    "disasterExposure": 3,
    "riskLevel": "HIGH",
    "signals": [
      "M6.1 earthquake — exceeds design basis for many reactors",
      "6 M4.0+ earthquakes — seismic hazard reassessment needed",
      "3 flood events — cooling water intake/discharge vulnerability",
      "Combined seismic + flood risk — Fukushima-type compound hazard"
    ]
  },
  "regulatoryCompliance": {
    "score": 52,
    "nuclearRules": 11,
    "emergencyActions": 1,
    "legislativePressure": 4,
    "complianceLevel": "WATCH",
    "signals": [
      "1 emergency NRC actions — immediate safety concern",
      "4 nuclear-related bills — active legislative attention"
    ]
  },
  "environmentalContamination": {
    "score": 38,
    "airQualityImpact": 12,
    "wasteIndicators": 4,
    "contaminationLevel": "DETECTED",
    "signals": [
      "4 waste management regulatory actions"
    ]
  },
  "operatorTransparency": {
    "score": 18,
    "corporateEntities": 3,
    "complexStructure": false,
    "transparencyLevel": "ADEQUATE",
    "signals": []
  },
  "allSignals": [
    "M6.1 earthquake — exceeds design basis for many reactors",
    "6 M4.0+ earthquakes — seismic hazard reassessment needed",
    "3 flood events — cooling water intake/discharge vulnerability",
    "Combined seismic + flood risk — Fukushima-type compound hazard",
    "1 emergency NRC actions — immediate safety concern",
    "4 nuclear-related bills — active legislative attention",
    "4 waste management regulatory actions"
  ],
  "recommendations": [
    "Seismic zone — probabilistic seismic hazard analysis update recommended"
  ]
}

Output fields

How much does it cost to run nuclear risk assessments?

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

You can set a maximum spending limit per run to control costs. The server stops charging when your budget is reached and returns a structured error so your agent can handle it gracefully.

Compare this to nuclear risk data vendors at $500-2,500/month for plant-level intelligence subscriptions. Most users of this MCP spend under $5/month with no subscription commitment. Apify's free tier includes $5 of monthly platform credits, enough for approximately 111 tool calls.

How Nuclear Regulatory Intelligence MCP works

Phase 1: Parallel data collection

When a tool is called, the server dispatches up to 8 sub-actor calls simultaneously using Promise.all via runActorsParallel. Each sub-actor runs with 512 MB memory and a 120-second timeout. The actors called depend on the tool: plant_risk_assessment and regional_nuclear_exposure run all 8 sources; focused tools like seismic_vulnerability_check and environmental_contamination_risk run only 3 sources, reducing cost and latency. Results are keyed by actor name (usgs-earthquake-search, federal-register-search, etc.) and passed to the scoring engine.

Phase 2: Dimensional risk scoring

Four independent scoring models process the collected data:

Plant Proximity Risk Index (max 100, 30% composite weight): Seismic scoring awards 15 points per M6.0+ earthquake, 6 points per M4.0+ event, and 2 points per any seismic event, capped at 40 total. Disaster exposure from FEMA awards 10 points per hurricane, 6 per flood event, 2 per any declaration, capped at 30. NOAA weather extremes contribute up to 20 points (8 per tornado). A compound bonus of 8 points fires when both majorQuakes and floodEvents are non-zero — the Fukushima-type combined hazard signal.

Regulatory Compliance Score (max 100, 30% weight): Federal Register entries are scanned against 15 NUCLEAR_KEYWORDS (nuclear, reactor, nrc, atomic, radiation, radioactive, uranium, plutonium, spent fuel, decommission, coolant, containment, meltdown, fission, criticality). Emergency or immediately-effective NRC actions score 12 points each. Enforcement, penalty, or violation entries score 6 points each. Congressional bills with restrictive terms (ban, moratorium, phase out, restrict) score 8 points each.

Environmental Contamination Probability (max 100, 25% weight): Air quality readings from OpenAQ score 3 points per day above AQI 100 and 10 points per extreme (AQI > 200) event, capped at 30. Federal Register entries are scanned against 10 WASTE_KEYWORDS (waste, spent fuel, high-level, low-level, transuranic, repository, dry cask, storage, disposal, Yucca). Emergency waste actions (leak, contamination, release) score 12 points each. Data.gov dataset presence for contamination, cleanup, superfund, radiation, or radioactive topics adds up to 20 points.

Operator Transparency Rating (max 100, 15% weight): OpenCorporates results are analysed for jurisdiction count, dissolved entities, and holding company structures. Operators with no corporate records receive 25 points immediately. Each additional jurisdiction adds 3 points, each holding/LLC/trust entity adds 4 points, each dissolved entity adds 5 points. The complexStructure flag fires when 3+ jurisdictions or 2+ holding entities are found.

Phase 3: Composite scoring and signal generation

The generateNuclearIntel function applies fixed weights to the four sub-scores: compositeScore = round(proximity × 0.30 + compliance × 0.30 + contamination × 0.25 + transparency × 0.15). Signals from all four models are aggregated into allSignals. Five recommendation rules fire when specific threshold combinations are breached, including the design basis reassessment rule for EXTREME proximity and the emergency response rule for HAZARDOUS contamination.

Tips for best results

1. Provide both plant name and region for the highest accuracy. The plant_risk_assessment tool constructs USGS and FEMA queries from the combined plant + region string. "Diablo Canyon California" returns tighter geographic results than "Diablo Canyon" alone.

2. Use focused tools for cost efficiency. If you only need seismic data, call seismic_vulnerability_check ($0.045, 3 sources) rather than plant_risk_assessment ($0.045, 8 sources). The price is identical per event, but focused tools return faster and their signals are easier to parse programmatically.

3. Run compare_plant_risks across multiple plants for benchmarking. Call it for 5-10 plants in a single AI session, then ask your AI agent to rank them by seismicScore or regulatoryScore. The dimensional scorecard format was designed for cross-plant comparison tables.

4. Set a spending limit when automating. If you're scheduling daily monitoring for a portfolio of plants, set maxTotalChargeUsd on the Apify run to cap monthly spend. The tool returns a structured { error: true, message: "Spending limit reached" } response your agent can handle.

5. Combine with the regulatory_compliance_tracker for event-driven monitoring. Schedule regulatory_compliance_tracker daily for your key plants. When emergencyActions > 0, trigger a full plant_risk_assessment for that plant. This minimises cost while ensuring you never miss an NRC emergency action.

6. Use regional_nuclear_exposure for portfolio onboarding. When adding a new region to your monitoring programme, start with regional_nuclear_exposure to understand the overall landscape before drilling down to individual plants with plant_risk_assessment.

7. Interpret operatorTransparency.score carefully. A high transparency score means the operator is hard to verify — not that they are necessarily bad actors. Single-site operators may have sparse corporate registry presence for legitimate reasons. Combine with the decommissioning_timeline tool to check regulatory filing history.

Combine with other Apify actors

Limitations

• US-focused regulatory data. The Federal Register, FEMA, NOAA, and Congress bill sources cover US nuclear facilities. International facilities can be assessed for seismic risk (USGS has global coverage) and operator transparency (OpenCorporates covers many jurisdictions), but regulatory compliance scoring is primarily calibrated to NRC actions.
• No access to NRC ADAMS. The Agencywide Documents Access and Management System contains the full text of NRC inspection reports, safety evaluation reports, and license amendment requests. This MCP accesses Federal Register summaries, not individual ADAMS documents. For document-level review, use the NRC ADAMS public search directly.
• Keyword-based signal detection. The scoring models scan text for keyword matches from fixed lists. A Federal Register action that discusses nuclear safety without using the exact monitored keywords will not be scored. Regulatory language changes can affect signal detection accuracy.
• Air quality is an environmental indicator, not a radiation monitor. OpenAQ provides PM2.5, PM10, and ozone data. It does not measure radioactive contamination or tritium release. High AQI readings near a nuclear plant are not direct evidence of radiological release.
• Corporate registry coverage varies. OpenCorporates coverage is strongest for US, UK, and EU entities. Nuclear operators in jurisdictions with limited public registry data will score higher on the opacity model regardless of actual transparency.
• Data freshness depends on source update frequency. Federal Register data is current to the previous business day. USGS earthquake data is near-real-time. FEMA disaster declarations can lag 24-72 hours after an event. Congress bill status updates on a congressional session schedule.
• Seismic scoring does not account for fault proximity. The model uses earthquake event counts near the query location, not fault line proximity or probabilistic seismic hazard analysis. A plant near a major fault with no recent earthquake history would score low despite elevated long-term risk.
• This server does not store results. Each tool call fetches data live and returns a single response. If you need a historical record of assessments, write results to your own database or use the Apify Dataset API.

Integrations

• Apify API — Call the MCP endpoint programmatically from Python, JavaScript, or any HTTP client with Bearer token authentication
• Zapier — Trigger plant risk assessments on a schedule and push HIGH_RISK results to email, Slack, or a Google Sheet
• Make — Build automated nuclear monitoring workflows that chain regulatory_compliance_tracker with downstream alerting and CRM updates
• Webhooks — Configure webhooks to fire when a monitoring run produces CRITICAL or HIGH_RISK verdicts for any plant in your portfolio
• Google Sheets — Pipe dimensional scores from compare_plant_risks into a shared spreadsheet for portfolio-level risk dashboards
• LangChain / LlamaIndex — Connect this MCP server to LangChain agent pipelines for multi-step nuclear due diligence workflows that combine risk scoring with document retrieval

Troubleshooting

Tool returns empty signals despite known regulatory activity. The scoring models use keyword matching against Federal Register titles and abstracts. If a specific NRC action uses docket-specific language rather than general nuclear keywords, it may not score. Use the regulatory_compliance_tracker with a specific keyword parameter (e.g., keyword: "license amendment") to narrow the Federal Register query and surface more targeted results.

Seismic score is 0 for a known seismically active area. USGS queries use the location string you provide. Vague location names may return no results if they do not match USGS geographic identifiers. Try the plant's nearest city or county name, or use coordinates in the location parameter.

Operator transparency score is unexpectedly high for a large utility. OpenCorporates may return multiple subsidiary entities across jurisdictions for major utilities, which increases the complexity score. Review corporateEntities count and signals to understand which specific structure characteristics triggered the score uplift. A high score reflects structural complexity, not necessarily risk.

Spending limit reached error on the first call. If you have a very low maxTotalChargeUsd configured on your Apify run (e.g., $0.01), the first tool charge of $0.045 will exceed it. Increase your run spend limit to at least $0.50 for normal testing.

regional_nuclear_exposure takes longer than other tools. This tool runs all 8 sub-actors in parallel, each with a 120-second timeout. For regions with extensive regulatory history (e.g., "California"), Federal Register and Congress queries return large result sets. Expect 15-30 seconds for regional assessments versus 5-10 seconds for focused tools.

Responsible use

• This server accesses publicly available government data from Federal Register, USGS, FEMA, NOAA, Data.gov, OpenAQ, OpenCorporates, and Congress.gov.
• Nuclear risk scores are derived from public data signals and are indicators, not certified safety assessments. Do not use them as the sole basis for engineering or emergency management decisions.
• Comply with applicable regulations when using risk assessments in financial, insurance, or legal contexts.
• For guidance on data use legality, see Apify's guide.

FAQ

How does nuclear regulatory intelligence scoring work for a specific plant? The server queries 8 data sources with the plant name and region, then applies four scoring models. Plant Proximity Risk (30% weight) uses USGS earthquake magnitude history and FEMA disaster counts. Regulatory Compliance (30%) uses Federal Register keyword density and congressional bill activity. Environmental Contamination (25%) uses OpenAQ AQI readings and Federal Register waste actions. Operator Transparency (15%) uses OpenCorporates corporate structure complexity. The four sub-scores combine into a Composite Nuclear Risk Score from 0 to 100.

How many nuclear plants can I assess in a single AI session? Each tool call is independent and costs $0.045. You can assess as many plants as your account balance allows. For bulk portfolio screening, run compare_plant_risks for each plant and ask your AI agent to aggregate the dimensional scores into a comparison table.

Does this MCP cover international nuclear facilities? The regulatory compliance model is calibrated to US NRC actions (Federal Register and Congress). Seismic risk assessments work globally because USGS covers worldwide earthquake data. Operator transparency assessments work for any country where OpenCorporates has registry coverage. Air quality assessments via OpenAQ work for any location with monitoring stations.

How current is the data used for nuclear risk scores? Federal Register data is current to the previous business day. USGS earthquake data is near-real-time. FEMA disaster declarations may lag 24-72 hours. OpenAQ readings depend on monitoring station update frequency, typically 1-24 hours. Congress bill status reflects the most recent congressional session data available.

Is it legal to use nuclear facility data this way? All data sources are publicly available US government databases. Federal Register, USGS, FEMA, NOAA, Data.gov, and Congress.gov data are in the public domain. OpenCorporates aggregates public corporate registry filings. There are no legal restrictions on accessing or analysing this public data. See Apify's guide on web scraping legality.

How is this different from NRC ADAMS or commercial nuclear data vendors? NRC ADAMS provides full-text access to individual inspection reports and license documents — deeper but requires manual document review. Commercial vendors like Wood Mackenzie or S&P Global Platts provide curated nuclear data at $500-2,500/month. This MCP aggregates 8 public sources into scored, structured outputs your AI agent can reason over directly, at $0.045 per assessment with no subscription.

Can I schedule automatic nuclear regulatory monitoring? Yes. Configure a daily or weekly Apify schedule calling regulatory_compliance_tracker for each plant in your portfolio. When emergencyActions > 0 or complianceLevel reaches NON_COMPLIANT, trigger a full plant_risk_assessment automatically via webhook. The structured JSON output makes conditional logic straightforward.

What does a CRITICAL verdict mean, and how often does it occur? A CRITICAL verdict (compositeScore 80+) requires severe compound risk across multiple dimensions simultaneously — typically a major seismic zone plant with active NRC enforcement orders, elevated contamination indicators, and an opaque operator structure. This combination is uncommon for compliant operating plants and would typically reflect a facility in active regulatory crisis.

Can I use this MCP with Cursor or Windsurf for code-assisted nuclear research? Yes. Point your Cursor or Windsurf MCP configuration to https://nuclear-regulatory-intelligence-mcp.apify.actor/mcp. The server is fully compatible with any MCP client that supports HTTP transport. You can then ask your IDE's AI assistant to pull seismic data, check compliance status, or generate risk comparison tables within your development workflow.

What happens if a data source is unavailable during a tool call? The runActorsParallel function catches individual sub-actor failures gracefully. If one source (e.g., OpenAQ) is temporarily unavailable, its result set is returned as an empty array and scoring continues with the remaining sources. The composite score will be lower than if all sources responded, but the tool will not error out entirely.

How do I interpret the operatorTransparency score for large utilities? Large utilities like Exelon or Duke Energy operate through multiple subsidiaries across many jurisdictions, which increases the transparency score's complexity component. A score of 30-50 for a major utility is expected and does not indicate opacity. Focus on the signals array — if it contains "No corporate records found" or "5 jurisdictions — complex corporate structure", those are meaningful flags. Absent those specific signals, moderate operator scores for large utilities are structurally expected.

Help us improve

If you encounter issues, you can help us debug faster by enabling run sharing in your Apify account:

1. Go to Account Settings > Privacy
2. Enable Share runs with public Actor creators

This lets us see your run details when something goes wrong, so we can fix issues faster. Your data is only visible to the actor developer, not publicly.

Support

Found a bug or have a feature request? Open an issue in the Issues tab on this actor's page. For custom nuclear risk workflows or enterprise integrations, reach out through the Apify platform.