Space Industry Intelligence MCP Server

Space industry intelligence for launch risk, orbital debris, spectrum interference, and regulatory compliance — delivered as an MCP server your AI assistant can call directly. Connect it to Claude, Cursor, or any MCP-compatible client and ask questions like "What is the launch risk for Falcon 9 this window?" or "Compare SpaceX and Rocket Lab on regulatory standing." You get a structured Composite Space Industry Score (0–100) with per-dimension breakdowns, actionable signals, and recommendations — all from live public data.

The server orchestrates 8 parallel data sources: NASA NEO tracking, Spaceflight News, Federal Register FAA/FCC filings, Congressional legislation, USPTO patents, Data.gov orbital catalogs, OFAC sanctions, and OpenCorporates corporate registries. Eight tools cover every major space industry risk dimension, from pre-launch window assessment to ITAR/EAR export control screening. Pricing is pay-per-tool-call at $0.045 — no subscription, no monthly commitment.

What data can you extract?

Why use the Space Industry Intelligence MCP Server?

Manual space industry due diligence means tabbing between NASA's CNEOS portal, FCC ECFS dockets, EDGAR, Federal Register search, USPTO PatFT, and OFAC's SDN list — then synthesizing conflicting signals across all of them. A single pre-launch risk assessment typically takes an analyst 4-6 hours. A launch provider comparison across three operators can consume a full day.

This MCP server automates the entire process. One tool call queries up to 8 sources in parallel, applies sector-specific scoring models, and returns a structured intelligence report in under 2 minutes. It runs as an always-on standby server — meaning zero cold-start wait time when your AI assistant calls it.

• Scheduling — configure recurring orbital environment monitoring via Apify Scheduler to catch debris events and regulatory changes as they happen
• API access — call any tool programmatically from Python, JavaScript, or any HTTP client with an Apify token
• Parallel data retrieval — all 8 upstream sources are queried simultaneously, not sequentially, keeping latency under 2 minutes
• Monitoring — receive Slack or email alerts when space weather scores cross thresholds or sanctions results change
• Integrations — connect outputs to Zapier, Make, Google Sheets, or downstream AI workflows via webhooks

Features

• 5 independent scoring models covering launch risk, orbital debris, spectrum interference, regulatory approval timeline, and space weather — each returning a 0–100 score with labeled severity level
• Composite Space Industry Score — weighted formula: launch risk 25% + regulatory approval 25% + spectrum interference 20% + orbital debris 15% + space weather 15%
• NEO proximity risk scoring — counts potentially hazardous objects and close approaches within 7.5 million km, contributing up to 25 points to the launch risk score
• Regulatory barrier detection — scans Federal Register filings for "restrict", "prohibit", "moratorium", and "suspend" keywords; scans Congressional bills for "ban", "restrict", and "limit" signals
• Spectrum contention analysis — identifies active interference, reallocation, and auction proceedings across Ku-band, Ka-band, C-band, L-band, and S-band frequency allocations
• OFAC sanctions screening with confidence threshold — flags OFAC SDN matches at ≥70% match score; scores above 60 produce BLOCKED verdict; 30–59 requires REVIEW_REQUIRED
• ITAR/EAR export control flagging — detects "ITAR", "EAR", "export control", and "munitions" signals in Federal Register entries alongside sanctions screening
• Enabling legislation detection — regulatory approval scoring rewards streamlining bills ("authorization", "modernization", "streamline") by subtracting from the timeline risk score
• Entity verification — OpenCorporates company status check raises approval risk score when entity shows as dissolved or struck off, or when no corporate records are found
• Launch provider comparison — accepts 2–5 providers in a single call, runs full parallel intelligence per provider, and returns a ranked comparison sorted by composite score
• Compound risk bonuses — scoring models apply additional compound penalties when multiple risk factors co-occur (e.g., NEO threats + restrictive regulations in the same assessment window)
• Automatic actionable recommendations — the composite report generates specific guidance when any dimension reaches CRITICAL or BLOCKED threshold
• Standby mode deployment — runs as a persistent HTTP server on the Apify platform with zero cold-start latency for interactive AI assistant use

Use cases for space industry intelligence

Pre-launch risk assessment

Launch directors and mission planners need to assess whether the current orbital environment, regulatory climate, and industry incident frequency justify proceeding with a launch window. This tool consolidates NEO proximity data, FAA rulemaking activity, and spaceflight news sentiment into a single launch risk score with a labeled severity level from LOW_RISK to CRITICAL — enabling go/no-go decisions backed by live data rather than analyst gut feel.

Space insurance underwriting

Satellite insurers calculating risk premiums need multi-dimensional risk data across orbital debris probability, space weather impact, and launch provider operational history. The orbital_debris_analysis, space_weather_impact, and compare_launch_providers tools provide the quantitative inputs needed to differentiate risk tiers across satellite constellations and launch vehicles — without licensing proprietary underwriting data feeds.

Spectrum allocation and interference monitoring

Constellation operators and telecom regulators need to track FCC spectrum proceedings, Ka-band and Ku-band reallocation activity, and satellite patent claims that could constrain future frequency use. The spectrum_interference_check tool queries Federal Register proceedings, USPTO filings, and Congressional spectrum legislation to score interference risk and flag active contention actions before they affect operations.

Space investor and acquirer due diligence

Venture capital firms and strategic acquirers evaluating space technology companies need rapid regulatory risk scans, patent landscape assessments, and export control compliance reviews. The space_industry_report tool assembles a full 8-source intelligence dossier in one call — covering corporate entity verification, ITAR/EAR compliance signals, patent positioning, and regulatory approval risk — in the time it takes to read a press release.

ITAR/EAR export control compliance screening

Defense contractors, government agencies, and international partners transacting with space companies must screen entities for OFAC sanctions and export control compliance before contracts are signed. The satellite_sanctions_screen tool combines OFAC SDN list matching with ITAR/EAR Federal Register flag detection and OpenCorporates corporate verification to deliver a CLEAR, REVIEW_REQUIRED, or BLOCKED verdict with a supporting evidence trail.

Launch provider procurement benchmarking

Satellite operators selecting a launch vehicle need structured, comparable risk data across launch providers — not marketing materials. The compare_launch_providers tool runs parallel intelligence across 2–5 providers and returns a ranked table covering composite score, launch risk level, debris level, spectrum interference, regulatory timeline, and space weather impact — structured for direct integration into procurement scoring models.

How to use the Space Industry Intelligence MCP Server

1. Add the MCP server to your AI client — copy the standby URL https://space-industry-intelligence-mcp.apify.actor/mcp and add it to your Claude Desktop, Cursor, or Windsurf configuration with your Apify token in the Authorization header. No installation or configuration beyond that.

2. Choose your tool — ask your AI assistant in natural language ("assess the launch risk for Falcon 9"), or call a specific tool by name if you are building a pipeline. The space_industry_report tool is the best starting point for a complete overview.

3. Review the score and signals — each response returns a 0–100 score, a labeled verdict, a list of specific signals detected across the 8 data sources, and recommendations when critical thresholds are crossed.

4. Export or integrate results — the structured JSON output can be forwarded to a Google Sheet, pushed to a Slack webhook, or piped into a downstream AI workflow. Use Apify Scheduler to run recurring assessments on a daily or weekly cadence.

MCP tools

Tool input examples

Single entity launch risk assessment:

{
  "name": "launch_risk_assessment",
  "arguments": {
    "entity": "SpaceX Falcon 9"
  }
}

Spectrum interference check for a specific band and operator:

{
  "name": "spectrum_interference_check",
  "arguments": {
    "band": "Ka-band",
    "operator": "ViaSat"
  }
}

Compare multiple launch providers:

{
  "name": "compare_launch_providers",
  "arguments": {
    "providers": ["SpaceX", "Rocket Lab", "ULA", "Arianespace"]
  }
}

Full intelligence report on a satellite constellation:

{
  "name": "space_industry_report",
  "arguments": {
    "entity": "Starlink constellation"
  }
}

Input tips

• Use specific entity names — "SpaceX Falcon 9" returns more targeted Federal Register and patent results than "SpaceX" alone
• Specify the orbital regime for debris analysis — passing orbit: "LEO" focuses the Data.gov and news queries on low Earth orbit events rather than generic orbital content
• Run space_industry_report first — it covers all 8 sources and all 5 dimensions; use the individual tools only when you need to re-query a specific dimension after reviewing the full report
• Batch provider comparisons — comparing 4 providers in one compare_launch_providers call is more cost-efficient than 4 separate launch_risk_assessment calls, and returns a pre-sorted ranking

Output example

{
  "entity": "Rocket Lab Electron",
  "compositeScore": 28,
  "verdict": "MANAGEABLE",
  "launchRisk": {
    "score": 22,
    "neoThreats": 1,
    "regulatoryBarriers": 3,
    "riskLevel": "MODERATE",
    "signals": [
      "1 potentially hazardous asteroid — launch window risk assessment needed"
    ]
  },
  "orbitalDebris": {
    "score": 18,
    "trackedObjects": 7,
    "hazardousNEOs": 1,
    "debrisLevel": "LOW",
    "signals": []
  },
  "spectrumInterference": {
    "score": 31,
    "regulatoryActions": 4,
    "patentActivity": 6,
    "interferenceLevel": "MODERATE",
    "signals": [
      "6 spectrum/satellite patents — crowded technology landscape"
    ]
  },
  "regulatoryApproval": {
    "score": 24,
    "activeRulemakings": 5,
    "pendingBills": 2,
    "timelineLevel": "STANDARD",
    "signals": [
      "1 enabling space bills — potential regulatory streamlining"
    ]
  },
  "spaceWeather": {
    "score": 14,
    "neoActivity": 7,
    "solarIndicators": 1,
    "impactLevel": "MINOR",
    "signals": []
  },
  "allSignals": [
    "1 potentially hazardous asteroid — launch window risk assessment needed",
    "6 spectrum/satellite patents — crowded technology landscape",
    "1 enabling space bills — potential regulatory streamlining"
  ],
  "recommendations": []
}

Output fields

How much does it cost to use the Space Industry Intelligence MCP?

This 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 MCP stops when your budget is reached.

Compare this to commercial space intelligence data subscriptions at $500–2,000/month — with this MCP, most analyst teams spend under $5/month with no subscription commitment and no minimum seat requirements.

Connecting the Space Industry Intelligence MCP using the API

Claude Desktop

Add to your claude_desktop_config.json:

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

Python

import httpx
import json

response = httpx.post(
    "https://space-industry-intelligence-mcp.apify.actor/mcp",
    headers={
        "Content-Type": "application/json",
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
    },
    json={
        "jsonrpc": "2.0",
        "method": "tools/call",
        "params": {
            "name": "space_industry_report",
            "arguments": {"entity": "Starlink constellation"}
        },
        "id": 1
    }
)

data = response.json()
result = json.loads(data["result"]["content"][0]["text"])
print(f"Composite Score: {result['compositeScore']}/100 — {result['verdict']}")
for signal in result["allSignals"]:
    print(f"  Signal: {signal}")
for rec in result["recommendations"]:
    print(f"  Recommendation: {rec}")

JavaScript

const response = await fetch("https://space-industry-intelligence-mcp.apify.actor/mcp", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_APIFY_TOKEN"
  },
  body: JSON.stringify({
    jsonrpc: "2.0",
    method: "tools/call",
    params: {
      name: "launch_risk_assessment",
      arguments: { entity: "Falcon 9 Block 5" }
    },
    id: 1
  })
});

const data = await response.json();
const result = JSON.parse(data.result.content[0].text);
console.log(`Launch Risk: ${result.score}/100 — ${result.riskLevel}`);
console.log(`Regulatory Barriers: ${result.regulatoryBarriers}`);
console.log(`NEO Threats: ${result.neoThreats}`);

cURL

# Call the space industry report tool
curl -X POST "https://space-industry-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": "satellite_sanctions_screen",
      "arguments": {"entity": "Starsem SA"}
    },
    "id": 1
  }'

# Compare launch providers
curl -X POST "https://space-industry-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": "compare_launch_providers",
      "arguments": {"providers": ["SpaceX", "Rocket Lab", "ULA"]}
    },
    "id": 2
  }'

How Space Industry Intelligence MCP works

Phase 1: parallel data retrieval

Each tool call triggers runActorsParallel(), which fans out to between 3 and 8 upstream Apify actors simultaneously using Promise.all(). All actors run with 512 MB memory and a 120-second timeout. The actors queried depend on the tool: space_industry_report calls all 8 sources (nasa-neo-tracker, spaceflight-news-search, federal-register-search, congress-bill-search, patent-search, datagov-dataset-search, ofac-sanctions-search, opencorporates-search); focused tools query only the 3–4 sources relevant to their dimension. Individual actor failures are caught and return empty arrays — the scoring continues with the available data.

Phase 2: dimension scoring

Five independent scoring functions process the combined data payload. Each function applies keyword matching against domain-specific keyword lists: LAUNCH_KEYWORDS (launch, rocket, spacecraft, payload, orbit, reentry, booster, mission, liftoff, countdown), DEBRIS_KEYWORDS (debris, collision, avoidance, conjunction, deorbit, kessler, fragment), SPECTRUM_KEYWORDS (spectrum, frequency, band, interference, itu, ku-band, ka-band, transponder), and SPACE_WEATHER_KEYWORDS (solar, geomagnetic, radiation, solar flare, cme, coronal mass, solar wind, magnetosphere). Each dimension score is capped at 100 and includes a compound bonus of up to 10–20 points when multiple risk factors co-occur in the same assessment window.

Phase 3: composite scoring and verdict generation

The composite score applies fixed weights: launch risk (25%) + regulatory approval (25%) + spectrum interference (20%) + orbital debris (15%) + space weather (15%). The weighted sum is rounded to the nearest integer. Verdicts are assigned at thresholds: LOW_RISK (0–19), MANAGEABLE (20–39), ELEVATED (40–59), HIGH_RISK (60–79), CRITICAL (80–100). The report aggregates all signals from all 5 dimensions and generates specific recommendations only when a dimension reaches its top severity level.

Phase 4: sanctions scoring (satellite_sanctions_screen tool)

The sanctions tool applies a separate scoring model independent of the 5-dimension composite. OFAC SDN matches at ≥70% confidence score contribute 25 points each. ITAR/EAR-related Federal Register entries ("itar", "ear", "export control", "munitions") contribute 10 points each. The sanctions score is capped at 100: BLOCKED ≥60, REVIEW_REQUIRED 30–59, CLEAR below 30. Corporate record count from OpenCorporates is returned as supporting evidence.

Tips for best results

1. Start with space_industry_report — it queries all 8 sources and returns all 5 dimensions. Use individual dimension tools only for follow-up queries or real-time monitoring of a single risk factor.

2. Be specific with entity names — "SpaceX Falcon 9 Block 5" produces better Federal Register, patent, and news matching than "SpaceX". For spectrum checks, specifying both band ("Ku-band") and operator narrows the FCC proceedings query significantly.

3. Use compare_launch_providers for procurement decisions — comparing 4 providers in one call costs $0.045 and returns a pre-sorted ranking. Running 4 separate launch_risk_assessment calls costs $0.18 and requires manual comparison.

4. Set spending limits for recurring workflows — if you run weekly monitoring across 20 entities, configure a per-run spending cap in your Apify account to prevent runaway costs if a query expands unexpectedly.

5. Combine with export control tools — the satellite_sanctions_screen tool covers OFAC and ITAR/EAR signals, but for comprehensive dual-use export control screening, chain this with Export Control Screening MCP for broader commodity jurisdiction analysis.

6. Treat LOW_RISK as a baseline, not a guarantee — scores reflect the density of public signals in government databases. A LOW_RISK score means few adverse signals were found in public data, not that no risks exist. For mission-critical launch decisions, supplement with dedicated SSA providers.

7. Use orbital regime filtering for debris analysis — passing orbit: "GEO" to orbital_debris_analysis focuses the Data.gov and news queries on geostationary orbit events, which have a very different risk profile from LEO.

Combine with other Apify actors and MCP servers

Limitations

• No real-time orbital tracking — the orbital debris and space weather assessments use NASA NEO data and public Data.gov catalogs, not live satellite tracking feeds. For real-time conjunction analysis, dedicated Space Situational Awareness providers (LeoLabs, 18th Space Defense Squadron) are required.
• No formal compliance certification — the satellite_sanctions_screen tool identifies risk signals from public data. It does not constitute a formal ITAR compliance review, legal opinion, or regulatory clearance. Use the output as a screening layer, not a compliance decision.
• Federal Register coverage is US-centric — regulatory tracking covers FAA, FCC, and US Congressional activity only. Non-US regulators (ESA, ITU filings, national space agencies) are not included in the current data source set.
• Patent search returns recent USPTO filings — the patent landscape component reflects recently indexed USPTO records. Pending applications that have not yet published, or international PCT filings, are not captured.
• Spaceflight news coverage depends on source availability — the news sentiment scoring for launch incidents and space weather events reflects coverage in the Spaceflight News API. Events not covered by that outlet may not score.
• OFAC screening uses name-matching at ≥70% confidence — partial or transliterated names may not match. For ultimate beneficial ownership analysis involving complex corporate structures, supplement with a dedicated KYC/AML tool.
• Compare tool processes providers sequentially internally — while the tool accepts 2–5 providers in one call, each provider's data retrieval runs as a separate sequential pass, not truly in parallel. For 5 providers, expect up to 3–4 minutes of response time.
• Input_schema.json contains no user-configurable parameters — all tool inputs are passed through the MCP protocol; there is no Apify-native form interface for this actor. It must be accessed through an MCP client or direct HTTP calls.

Integrations

• Apify API — call any tool directly via HTTP POST without an MCP client; integrate space intelligence into custom dashboards or risk platforms
• Webhooks — trigger downstream alerts in Slack, PagerDuty, or email when orbital debris or space weather scores cross defined thresholds
• Zapier — route weekly space_industry_report outputs to Google Sheets for tracked constellation monitoring
• Make — build multi-step automation that runs sanctions screening on new entity additions to a CRM before outreach
• Google Sheets — export compare_launch_providers results to a shared procurement scoring matrix updated on a scheduled cadence
• LangChain / LlamaIndex — use this MCP as a tool node in a LangGraph or LlamaIndex agent that conducts autonomous space industry research workflows

Troubleshooting

• Response returns mostly zero scores — this typically means the entity name produced few matching results across the upstream sources. Try a more specific name (include the launch vehicle model or mission designation) or broaden to a company name. Some very new entities may not yet appear in Federal Register or USPTO indexes.

• compare_launch_providers times out for 5 providers — each provider triggers a separate parallel data retrieval across 6 actors. For 5 providers, the total upstream query time can approach the 120-second actor timeout. Reduce to 3–4 providers per call, or split into two separate comparison calls.

• Sanctions screen returns REVIEW_REQUIRED for a known clear entity — the OFAC matcher uses name-similarity scoring and may flag partial matches against similar-sounding SDN entries. Review the sanctionHits count in the response: if it is 0, the REVIEW_REQUIRED verdict is driven by exportControlFlags from Federal Register entries mentioning ITAR or EAR in a related context, not an SDN match.

• Space weather scores are always low — space weather scoring depends on solar activity data present in Data.gov datasets and news coverage. During periods of low solar activity, scores will legitimately be low. If you suspect a solar event is not being captured, check NOAA's Space Weather Prediction Center directly for independent verification.

• MCP client cannot connect — ensure your Apify token has active credits and the token is passed in the Authorization: Bearer header, not as a query parameter. The server runs in standby mode and is always available; connection failures are almost always token or network issues, not server-side.

Responsible use

• This MCP accesses only publicly available government data: NASA, Federal Register, Congress.gov, USPTO, Data.gov, OFAC SDN list, and OpenCorporates.
• OFAC sanctions screening outputs are informational only and do not constitute a legal compliance determination. Consult qualified legal counsel for formal compliance decisions.
• Do not use sanctions screen outputs as the sole basis for blocking transactions involving individuals or entities. False positives occur; human review is required for REVIEW_REQUIRED and BLOCKED verdicts.
• Respect all applicable export control regulations (ITAR, EAR) when handling space technology data and intelligence outputs.
• For guidance on web scraping legality, see Apify's guide.

FAQ

What is the Space Industry Intelligence MCP Server and who is it for?

The Space Industry Intelligence MCP Server is an always-on AI tool that provides structured risk intelligence across five space industry dimensions: launch risk, orbital debris, spectrum interference, regulatory approval, and space weather. It is designed for satellite operators, launch service providers, space insurers, investors, defense contractors, and legal teams that need rapid, data-backed space industry assessments without manual database research.

How accurate is the Composite Space Industry Score?

The score reflects the density and severity of public signals in US government databases at the time of the query. It is a relative risk indicator, not an absolute safety rating. A score of 20 (MANAGEABLE) means fewer adverse public signals were found than a score of 60 (HIGH_RISK). Scores should be interpreted as a screening tool that directs analyst attention, not as a standalone decision engine.

How is the space industry intelligence score different from commercial SSA providers?

Commercial Space Situational Awareness providers like LeoLabs or ExoAnalytic offer real-time radar tracking of individual objects. This MCP scores the broader regulatory, environmental, and industry risk landscape using public data sources. The two are complementary: use this MCP for regulatory and business intelligence, and dedicated SSA services for real-time conjunction analysis.

How many tool calls does a typical analysis session use?

A single space_industry_report covers all 5 dimensions in one call at $0.045. Most users run 3–8 tool calls per analysis session (a full report plus 2–3 follow-up dimension-specific queries), spending $0.14–$0.36 per session. Weekly monitoring of 10 entities using space_industry_report costs approximately $0.45/week.

Can I run space industry intelligence assessments on a schedule?

Yes. Use the Apify Scheduler to trigger this MCP on a daily, weekly, or custom interval. Combine with webhooks to receive alerts when a composite score exceeds a threshold you define. This is the recommended approach for constellation operators monitoring ongoing debris and spectrum conditions.

Does the space industry intelligence MCP cover non-US launch providers?

The regulatory tracking is US-centric (FAA, FCC, Congress). However, entity names for non-US providers (Arianespace, Mitsubishi, ISRO) are valid inputs for NASA NEO, spaceflight news, OFAC screening, and OpenCorporates queries, which have international coverage. The regulatory dimension scores will be lower for non-US entities due to the US-centric data sources.

Is it legal to use government data for space industry intelligence?

All data sources used by this MCP — NASA, Federal Register, Congress.gov, USPTO, Data.gov, OFAC, and OpenCorporates — are public-access databases. Accessing and analyzing public government data for intelligence purposes is legal. For guidance on data use, see Apify's guide on web scraping legality.

What happens when the OFAC sanctions screening returns BLOCKED?

A BLOCKED verdict means the entity scored ≥60 on the sanctions model: either two or more OFAC SDN matches at ≥70% confidence, or a combination of SDN matches and ITAR/EAR Federal Register flags. This is a screening signal, not a legal determination. A qualified sanctions compliance officer should review the underlying sanctionHits and exportControlFlags counts before taking action on the result.

Can I compare more than 5 launch providers?

The compare_launch_providers tool accepts 2–5 providers per call. For larger comparisons, make multiple calls and combine the results. The output is pre-sorted by composite score, making manual merging straightforward.

How long does a space_industry_report take to complete?

A typical space_industry_report call completes in 60–120 seconds, depending on how many upstream actors return results quickly. Each upstream actor has a 120-second individual timeout. The overall call will return as soon as all parallel queries complete or time out.

Can I use this MCP with Cursor, Windsurf, or other AI coding assistants?

Yes. Any MCP-compatible client that supports HTTP-based MCP connections (Claude Desktop, Cursor, Windsurf, Cline, and others) can connect using the standby URL and an Apify Bearer token. The server implements the standard MCP protocol via @modelcontextprotocol/sdk.

How is space weather impact assessed without a real-time solar data feed?

The space weather scoring uses two proxies: Data.gov datasets matching solar and geomagnetic keywords (solar, geomagnetic, radiation, solar flare, CME, coronal mass, solar wind, magnetosphere, ionosphere, aurora), and spaceflight news coverage of space weather events. During active solar events, these sources typically publish within hours. For real-time solar conditions, supplement with NOAA Space Weather Prediction Center data.

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Support

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