Agricultural Commodity Climate

What is Agricultural Commodity Climate?

Agricultural Commodity Climate is an MCP server that provides live weather stress analysis, pest emergence monitoring, trade concentration scoring, and price shock probability for any crop or growing region. It orchestrates eight public data sources (NOAA, GDACS, UN COMTRADE, World Bank, GBIF, FRED, Nominatim, and a weather forecast service) into four quantified scoring models and a composite Commodity Risk Score (0–100) with actionable recommendations. No downstream API keys are required.

How to use Agricultural Commodity Climate?

Add the server to your MCP client by configuring the URL https://ryanclinton--agricultural-commodity-climate-mcp.apify.actor/mcp in your MCP settings JSON. Then invoke any of the seven available tools (e.g., crop_region_risk_assessment) via your AI agent or programmatically via the Apify API. Each tool call costs $0.045 and returns results in 30–90 seconds.

Key features of Agricultural Commodity Climate

• Weather Stress Index (0–100) from NOAA alerts, forecasts, and GDACS disasters
• Pest Emergence Score (0–100) using GBIF species observations and World Bank vulnerability
• Trade Disruption Score with Herfindahl-Hirschman Index (HHI) from UN COMTRADE
• Price Shock Probability (0–100) from FRED trends, weather/disaster supply shocks, and trade concentration
• Composite Commodity Risk Score (0–100) weighted across all four models with CRITICAL override
• Parallel data fetching via Promise.all and standby mode for low-latency agent workflows
• Per-tool spending limits and built-in proxy/retry infrastructure

Use cases of Agricultural Commodity Climate

• Commodity traders run price_shock_probability each morning for early supply disruption warnings
• Crop insurance underwriters use crop_region_risk_assessment for current Weather Stress Index per region
• Food company procurement teams call trade_dependency_analysis to detect concentrated supplier risk
• Portfolio managers use compare_commodity_risks for comparable risk metrics across different crops
• Government and NGO analysts run food_security_vulnerability for country-level food security assessments
• Pest control teams use pest_emergence_alert to detect emerging pest and disease pressure

FAQ from Agricultural Commodity Climate

What data sources does the server use?

NOAA weather alerts, multi-day forecasts, GDACS disaster events, UN COMTRADE trade flows, World Bank agricultural indicators, GBIF biodiversity occurrence records, FRED commodity price series, and Nominatim geocoding.

Are any API keys required for downstream sources?

No, the server handles all orchestration and does not require API keys for any downstream data source.

What is the cost per tool invocation?

Each tool call costs $0.045 (USD) and returns results in 30–90 seconds.

How is the Composite Commodity Risk Score calculated?

Weighted average: weather stress 30%, price shock 30%, trade disruption 25%, pest emergence 15%. It overrides to CRITICAL when crop failure risk and imminent price shock both present.

What verdict levels does the server output?

Five levels: LOW_RISK, MANAGEABLE, ELEVATED, HIGH_RISK, CRITICAL, each with auto-generated hedge recommendations.