io.github.SupplyMaven-SCR/supply-chain-intelligence
REMOTE · SUPPLYMAVEN.COM · SCANNED AUG 3
Real-time supply chain risk intelligence — 24 tools, proprietary indices, predictive signals
Available components
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →
Endpoint Security63
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- Authorisation not fully verified: no authorisation is required to call this server, and 33 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe. See how to fix → View diagnostics → Unverified
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- The HSTS (Strict-Transport-Security) header is present. View diagnostics → Pass
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
Schema Quality & AI Usability77
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 3732 tokens (~113/item across 33 items; 33 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
- Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.
remote · supplymaven.com
claude mcp add --transport http supplymaven-scr-supply-chain-intelligence https://supplymaven.com/api/mcp
[mcp_servers.supplymaven-scr-supply-chain-intelligence] url = "https://supplymaven.com/api/mcp"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"supplymaven-scr-supply-chain-intelligence": {
"type": "remote",
"url": "https://supplymaven.com/api/mcp",
"enabled": true
}
}
} openclaw mcp add supplymaven-scr-supply-chain-intelligence --url https://supplymaven.com/api/mcp --transport streamable-http
mcp_servers:
supplymaven-scr-supply-chain-intelligence:
url: "https://supplymaven.com/api/mcp" {
"mcpServers": {
"supplymaven-scr-supply-chain-intelligence": {
"type": "http",
"url": "https://supplymaven.com/api/mcp"
}
}
} The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 3 Aug 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.
- 1 Aug 26 +1
- HSTS header: unverified → pass ▲ security
- Transport: fail → pass ▲ security
- Authorization: Authorisation not fully verified: no authorisation is required to call this server, and 33 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe. security
- Tool coverage: unverified → 100 ▲ functional
- Stability: unverified → 0.20 ▲ functional
- MCP protocol: unverified → pass ▲ functional
- 31 Jul 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 30 Jul 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.
- 29 Jul 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.
- 27 Jul 26 +1
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 26 Jul 26 65
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 3 Aug 2026 · Probed https://supplymaven.com/api/mcp
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=*.supplymaven.com | CN=YR1,O=Let's Encrypt,C=US | 9 Jul 2026 | 7 Oct 2026 | RSA 2048 | SHA256-RSA | 59fe3107b8b1c939955086f09df10c0a320 |
| SANs: *.supplymaven.com, supplymaven.com | ||||||
| CN=YR1,O=Let's Encrypt,C=US (CA) | CN=Root YR,O=ISRG,C=US | 3 Sept 2025 | 2 Sept 2028 | RSA 2048 | SHA256-RSA | a20253f15f2691c05dc1ce13b9bcca4e |
| CN=Root YR,O=ISRG,C=US (CA) | CN=ISRG Root X1,O=Internet Security Research Group,C=US | 13 May 2026 | 2 Sept 2032 | RSA 4096 | SHA256-RSA | f24b6d17f9d9ad7cb1c9fea78782699f |
DNSSEC insecure
Validation of supplymaven.com. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| com. | present | 19718 | 13 | Verified |
| supplymaven.com. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 200 |
| Header | Value |
|---|---|
| strict-transport-security | max-age=63072000 |
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://supplymaven.com/api/mcp | Verified | 200 | |
| http (plaintext) | http://supplymaven.com/api/mcp | HTTPS enforced | 308 | https://supplymaven.com/api/mcp |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
commodity_price_monitor ~137
Monitor real-time commodity prices and price volatility for supply chain cost management. Tracks 31 commodities across energy (WTI crude, Brent, natural gas, coal, ethanol), metals (copper, aluminum, nickel, zinc, lithium, cobalt, iron, titanium, uranium), agriculture (corn, wheat, soybeans, rice, cotton, lumber), industrial materials (rubber, polyethylene, PVC, polypropylene, soda ash), and semiconductor materials (germanium, gallium, indium, neodymium). Returns current price and 24-hour change percentage. Free tier covers 5 key commodities; paid tier covers all 31.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_action_signals ~67
Get statistically validated leading indicator signals evaluated against live GDI and SMI data. Each signal is a Granger-causal relationship (p≤0.01) with a specific lag time and directional accuracy. Returns ACTIVE, WATCH, or CLEAR status for each signal. Paid tier only.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_air_cargo_disruptions ~115
Get real-time air cargo disruption status at major US and international freight hub airports. Returns FAA ground delays, ground stops, arrival and departure delays with estimated minutes, closure status, disruption score, and traffic collapse detection. Covers major cargo hubs including Memphis (FedEx), Louisville (UPS), Anchorage, Chicago O'Hare, Los Angeles, Miami, New York JFK, and Dallas-Fort Worth. Used by air freight forwarders, express carriers, and logistics planners to reroute time-sensitive shipments around airport disruptions.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_border_delays ~111
Get real-time commercial border crossing wait times at US-Mexico and US-Canada ports of entry. Returns current delay in minutes for commercial vehicles, number of lanes open, and port status. Updated every 30 minutes from US Customs and Border Protection. Covers all major commercial crossings including Laredo, El Paso, Nogales, Otay Mesa, Detroit, Buffalo, and Blaine. Used by logistics companies, freight brokers, and trucking operations to route cross-border shipments through the fastest crossing points.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_chokepoint_traffic ~103
Monitor real-time vessel traffic and congestion at critical maritime chokepoints — Suez Canal, Panama Canal, Strait of Malacca, Strait of Hormuz, Bab el-Mandeb, and other strategic waterways. Returns total vessel count, average speed, count of slow or stationary vessels, and a congestion score with severity level. When chokepoints congest or close, global shipping routes reroute within days — this data detects that signal in real time.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_commodity_volatility_alerts ~106
Get alerts for commodities experiencing abnormal price volatility. Flags any commodity where the 24-hour price change exceeds normal ranges or where prices are at extreme levels. Returns the current price, 24-hour change percentage, trend direction, and risk assessment. Answers 'which commodities are behaving unusually right now?' — a question that takes procurement teams hours to answer manually. Used by procurement teams to time purchases, commodity traders to identify opportunities, and supply chain managers to anticipate cost changes.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_corridor_risk ~123
Monitor risk levels across 10 major ocean freight trade corridors (China-US West Coast, China-US East Coast, China-Mexico, Taiwan-US, India-US, China-Europe, Europe-US, Middle East-Europe, Brazil-US). Each corridor chains origin ports, chokepoints, and destination ports into a single lane scored by its weakest link (highest risk waypoint). Scores combine real-time port congestion data with active natural disaster proximity. Used by logistics planners for route risk comparison, procurement teams for supply chain exposure assessment, and freight forwarders for disruption early warning.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_customs_friction_baseline ~116
Get customs friction baseline scores by country. Returns a composite 0-100 score combining port congestion (55% weight) and customs/trade policy events (45% weight). Covers 21 countries across North America, East Asia, Southeast Asia, South Asia, Europe, Middle East, and South America. Higher score = more friction. Optional country parameter for single-country detail with component breakdown and 30-day history. Used by trade compliance teams, procurement managers, and logistics planners to assess customs clearance risk by country.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_customs_trade_events ~90
Get customs and trade policy events extracted from news intelligence. Covers tariff changes, sanctions, export controls, trade agreements, anti-dumping duties, and regulatory changes. Each event includes affected countries, products, direction (RESTRICTIVE/LIBERALIZING/NEUTRAL/MIXED), US impact assessment, and confidence score. Used by trade compliance teams and procurement managers to track policy risk.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_disaster_events ~121
Get active natural disaster events that may impact supply chain operations. Sources: USGS (earthquakes M5.0+), NOAA (storms/hurricanes, US), GDACS (global earthquakes, tropical cyclones, floods, volcanoes). Returns event type, severity, location, coordinates, and affected country. Events auto-expire based on source TTL. Supports filtering by event type, country, region, and lookback window. Complements get_natural_disaster_alerts with additional filtering options including multi-day lookback and region-based geographic filtering.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_economic_indicators ~95
Get key economic indicators affecting supply chain costs and conditions. Returns Federal Reserve data (industrial production, capacity utilization, manufacturing PMI, housing starts, imports), Producer Price Index by category, Global Supply Chain Pressure Index (GSCPI) from the New York Fed, and EIA Short-Term Energy Outlook forecasts. Used by supply chain strategists, procurement leaders, and economic analysts who need the macro backdrop for supply chain planning.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_energy_breakdown ~125
Get comprehensive US energy market status for supply chain cost analysis. Returns crude oil prices (WTI and Brent), natural gas spot prices (Henry Hub), retail fuel prices (gasoline, diesel), natural gas storage versus capacity, refinery utilization rates, petroleum stock levels with week-over-week changes, and import/export flows. This is the disaggregated view behind the GDI Energy pillar — instead of a single risk number, you get the full picture of energy costs affecting manufacturing, freight, and logistics. Used by supply chain cost analysts, transportation managers, and energy procurement teams.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_energy_forecast ~111
Get the US Energy Information Administration's Short-Term Energy Outlook (STEO) — official government forecasts for energy production, consumption, and pricing. Returns both historical actuals and forward-looking projections for crude oil prices, natural gas prices, electricity generation, renewable energy production, and petroleum consumption. The STEO is the most widely referenced energy forecast in the world. Distinguishes actual historical data from projected forecasts using the isActual flag. Used by energy traders, logistics companies budgeting fuel costs, and macro analysts.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_freight_rate_observations ~81
Get freight rate index observations extracted from news intelligence. Covers major ocean freight indexes (BDI, SCFI, WCI, CCFI, HARPEX) with direction, magnitude, trade lane, and rate values. Each observation includes confidence score and source URL. Used by logistics planners to track rate trends and identify cost pressure signals.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_freight_rate_pressure ~161
Returns freight rate pressure scores for major shipping and commodity indices (WCI, SCFI, BDI, CRB). Includes current values, week-over-week changes, z-score vs 52-week baseline, and mapping to trade corridors. WCI (Drewry World Container Index) tracks container rates in USD/FEU. SCFI (Shanghai Containerized Freight Index) tracks export rates from Shanghai. BDI (Baltic Dry Index) tracks dry bulk shipping rates. CRB (CRB Commodity Index) tracks broad commodity pressure. Pressure scoring: 0-35 STABLE, 36-55 ELEVATED, 56-69 VOLATILE, 70-84 SURGING, 85-100 EXTREME.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_freight_transportation_index ~98
Get the US freight transportation health index from the Bureau of Transportation Statistics. Returns the Transportation Services Index (TSI) for freight and passenger, truck tonnage, rail carloadings, rail intermodal volume, waterborne freight, inventory-to-sales ratio, and industrial production index. Declining freight volumes are a leading indicator of economic slowdown. Used by logistics companies, freight brokers, and economic analysts tracking US freight demand trends.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_gdi_trend_analysis ~115
Get trend analysis of the Global Disruption Index over time. Returns the current GDI score plus 7-day, 14-day, and 30-day comparisons with direction, velocity of change, and pillar-level momentum. Identifies which pillar is driving changes and whether risk is accelerating or decelerating. Answers: 'Is supply chain risk getting better or worse, how fast, and why?' Used by supply chain executives for weekly status briefings and by traders to time entry/exit decisions around supply chain volatility.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_intelligence_briefs ~103
Get AI-generated intelligence briefs for each supply chain dimension — energy, materials, transportation, macro, and manufacturing. Each brief provides a narrative analysis of current conditions, key drivers, emerging risks, and recommended watch items. These are not raw data — they are synthesized analytical summaries generated every hour from live data. Designed for decision-makers who need a quick read on each supply chain dimension. Returns structured briefs suitable for executive dashboards, email digests, or Slack channels.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_labor_actions ~75
Get labor actions affecting supply chains extracted from news intelligence. Covers strikes, lockouts, slowdowns, contract negotiations, and protests. Each event includes union, employer, location, worker count, affected ports, status, and impact description. Used by logistics planners and procurement teams to assess labor disruption risk at ports and manufacturing facilities.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_manufacturing_anomalies ~138
Detect unusual electricity demand patterns that signal manufacturing disruptions before they appear in official reports. Monitors 8 US power grid regions (PJM, MISO, ERCOT, CAISO, SPP, ISNE, NYISO, NW) for demand anomalies — sudden drops indicate factory shutdowns, surges indicate production ramp-ups. Returns current SMI score with regional breakdown plus anomalies from the past 7 days ranked by severity. The Supply Manufacturing Index (SMI) uses patent-pending weather normalization to isolate industrial demand from weather-driven consumption. Used by commodity traders for early manufacturing signals and procurement teams to anticipate supply changes.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_natural_disaster_alerts ~99
Get real-time natural disaster alerts from USGS (earthquakes M5.0+), NOAA (hurricanes, tropical storms), and GDACS (global earthquakes, cyclones, floods, volcanoes). Returns active and recent events with magnitude, severity, coordinates, and affected country. Used by logistics planners and procurement teams to reroute shipments and activate contingency plans around seismic events, hurricanes, and floods affecting supply chain infrastructure.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_port_congestion_trends ~87
Get port congestion trend analysis — not just current congestion, but direction and trajectory. Returns how congestion has changed relative to historical baselines, identifies ports where congestion is accelerating, and flags ports approaching critical thresholds. Answers: 'Which ports are getting worse and how fast?' Used by logistics planners to reroute shipments before congestion peaks, and by importers to anticipate lead time extensions.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_predictive_signals ~141
Statistically validated leading indicator signals evaluated against live supply chain data. Each signal is a Granger-causal relationship tested at p<=0.01 with directional accuracy >=55%. Signals predict commodity price movements, manufacturing shifts, and macroeconomic changes 1 week to 6 months ahead. Returns ACTIVE (threshold crossed — act now), WATCH (approaching threshold — prepare), or CLEAR status for each signal. 58 signals across 3 tiers organized by predictor group (GDI pillars, SMI regions, cross-index spreads). Used by commodity traders for forward-looking positioning, procurement teams for buy/defer timing, and hedge funds for alternative data signals.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_rail_freight_status ~115
Get US freight rail performance metrics including average train speed, terminal dwell time, cars on line, trains held per day, railcars not moved within 48 hours, total carloadings, intermodal units, and grain transport rates. Sourced from the Surface Transportation Board railroad service metrics, Association of American Railroads carloading data, and USDA grain transportation reports. When rail slows down, inland supply chains back up within days — this data provides early warning of freight bottlenecks across the US rail network.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_signal_narratives ~93
Get plain-language explanations of active predictive signals. Each narrative explains the mechanism behind a signal — why the predictor leads the target, what economic logic connects them, and what the current reading implies. Designed for non-quantitative users who want to understand the 'why' behind each signal without reading F-statistics. Returns trigger context, predictor value, direction, and a narrative paragraph suitable for reports and briefings.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_supply_chain_weekly_brief ~107
Comprehensive weekly supply chain situation report combining all SupplyMaven data sources into an executive-level brief. Includes GDI score with pillar breakdown and trend, top disruption events with risk scores, manufacturing output status across 8 regions, commodity price movements, port congestion highlights, and active predictive signals. Designed to answer 'what happened this week in supply chains?' in a single call. Used by executives, procurement leaders, and supply chain managers for weekly risk reviews and stakeholder briefings.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_trade_policy_impacts ~109
Get active trade policy actions currently impacting supply chain risk — tariffs, sanctions, export controls, import restrictions, and regulatory changes. Unlike news alerts that expire after 72 hours, policy adjustments persist as long as the policy is in effect and continue to modify GDI risk scores. Each policy includes the affected GDI pillar, score modifier, effective date, and source event. Used by procurement teams navigating tariff exposure, compliance officers tracking sanctions, and supply chain strategists adapting sourcing to policy shifts.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_weekly_content_package ~135
Get the weekly 'Signal of the Week' content package — a pre-written, data-verified marketing bundle generated every Monday from live SupplyMaven data. Returns a Substack article (~500 words), LinkedIn post (~200 words), and Twitter/X thread (4-5 tweets), all built from verified supply chain data. Every number in the content traces back to a live data source. Designed for automated content distribution via Claude Desktop + platform MCP servers. The content package includes the signal headline, full data context (GDI, SMI, commodities, ports, signals), and platform-specific formatted content ready for publishing.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
manufacturing_output_indicator ~184
Detect US manufacturing output changes up to 24 hours before official government reports. The patent-pending Supply Manufacturing Index (SMI) analyzes weather-normalized electricity demand across 8 US power grid regions (MISO/Midwest, ERCOT/Texas, PJM/Mid-Atlantic, CISO/California, ISNE/New England, NYIS/New York, SWPP/Central, NW/Pacific Northwest) to isolate real industrial activity from seasonal heating and cooling noise. Returns regional and national manufacturing activity scores, trend direction, and comparison to official Federal Reserve Industrial Production (INDPRO) data. INVERTED scale: lower = stronger manufacturing. 0-35 STRONG, 36-50 NORMAL, 51-65 BELOW TREND, 66+ WEAK. Used by commodity traders, economic analysts, and hedge funds as a leading manufacturing indicator.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
port_congestion_monitor ~133
Monitor real-time port congestion and vessel traffic at 26 major global ports. Returns vessel counts at berth and at anchor, congestion score versus historical baseline, and port status. Covers US ports (Los Angeles, Long Beach, Savannah, Houston, New York/New Jersey, Charleston, Oakland, Seattle, Tacoma), Asian ports (Shanghai, Singapore, Busan, Ningbo, Shenzhen, Hong Kong), and European ports (Rotterdam, Hamburg, Antwerp, Felixstowe, Piraeus). Used by freight forwarders, logistics teams, and importers to monitor delays, plan routing, and anticipate lead time changes.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
risk_pillar_breakdown ~110
Get detailed breakdown of supply chain disruption risk by category. Returns individual scores for each GDI pillar — Transportation (port congestion, border delays, freight weather), Energy (petroleum, natural gas, electricity, fuel prices), Materials (31 commodity prices with volatility), and Macro (Federal Reserve indicators, Producer Price Index). Each pillar includes its score, trend direction, and the specific data points driving the current reading. Essential for supply chain managers who need to diagnose which risk category is elevated and why.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
supply_chain_disruption_alerts ~96
Get real-time supply chain disruption alerts from global news intelligence and event detection. Returns categorized alerts for port closures, trade policy changes, tariff actions, natural disasters, labor strikes, sanctions, commodity shortages, and weather disruptions. Each alert includes severity level, affected supply chain stage (sourcing, manufacturing, logistics, distribution), and risk score. Free tier returns critical-severity alerts only; paid tier returns all severities.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
supply_chain_risk_assessment ~132
Assess current global supply chain disruption risk. Returns the Global Disruption Index (GDI) — a real-time composite score from 0-100 measuring disruption across transportation, energy, materials, and macroeconomic pillars. Higher scores indicate greater supply chain risk. Built from 200+ live data variables including port congestion at 26 global ports, commodity prices for 31 assets, US border crossing delays, manufacturing output from 8 power grid regions, and Federal Reserve economic indicators. Used by procurement teams, logistics planners, commodity traders, and supply chain managers for real-time supply chain visibility and risk monitoring.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.