CropProphEU

@DasClown

About CropProphEU

No overview available yet

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "CropProphEU": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "crop-mcp",
        "."
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is CropProphEU?

A free MCP server that provides yield forecasts, market values (€/ha), risk analysis, environmental risk scoring, and portfolio optimization for European agriculture. It covers 5 crops across 26 EU countries and 123 NUTS2 regions, built for AI agents using only free, public data sources.

How to use CropProphEU?

Install via pip install git+https://github.com/DasClown/CropProphEU.git, then run as an MCP server using the crop-mcp CLI command (stdio) or crop-mcp --http --port 8080 for HTTP/SSE. Integrate with Claude Desktop or Cursor by adding a JSON configuration with the command python3 -m crop_mcp.server. Alternatively, use the Python API directly for yield predictions.

Key features of CropProphEU

13 MCP tools for yield, value, risk, and optimization
Yield-at-Risk (P10/P50/P90) with NDVI satellite correction
Live market prices from CBOT/MATIF via Yahoo Finance
Portfolio optimizer for budget allocation across regions and crops
Environmental Risk Score (ERS) and wild boar damage risk (DE)
Zero API keys required – all data sources are free and public

Use cases of CropProphEU

Agri-trading desks: query crop value in specific regions at current market prices
Farm advisory: compare current season to historical years
Portfolio optimization: find best €/ha allocation across 100+ ha
Environmental risk assessment: evaluate forest, erosion, storm, hail, and wild boar risk
Climate scenario analysis: what-if simulations (+2°C, -20% rain, etc.)

FAQ from CropProphEU

What crops and regions are supported?

Five crops: wheat, corn, barley, rapeseed, sunflower – across 26 EU countries (including Ukraine and UK) and 123 NUTS2 regions.

Does CropProphEU require API keys?

No. All data sources (Eurostat, NASA POWER, Open-Meteo, SoilGrids, Sentinel-2 NDVI, Yahoo Finance) are free and public.

How accurate are the yield forecasts?

Leave-One-Year-Out MAE ranges from 10.8% (rapeseed) to 16.1% (sunflower), with R² values between 0.72 and 0.87. Forward validation (2023-24) shows MAE of 15.0% for wheat.

How can I run CropProphEU as an HTTP server?

Install with pip install crop-mcp[http] and run crop-mcp --http --port 8080. Connect via SSE at http://your-server:8080/sse.

What data sources are used for the predictions?

Eurostat verified crop codes, NASA POWER for weather, Open-Meteo for forecasts, SoilGrids v2 for soil properties, Sentinel-2 NDVI for vegetation correction, and Yahoo Finance for live commodity prices.

Frequently asked questions

What crops and regions are supported?

Five crops: wheat, corn, barley, rapeseed, sunflower – across 26 EU countries (including Ukraine and UK) and 123 NUTS2 regions.

Does CropProphEU require API keys?

No. All data sources (Eurostat, NASA POWER, Open-Meteo, SoilGrids, Sentinel-2 NDVI, Yahoo Finance) are free and public.

How accurate are the yield forecasts?

Leave-One-Year-Out MAE ranges from 10.8% (rapeseed) to 16.1% (sunflower), with R² values between 0.72 and 0.87. Forward validation (2023-24) shows MAE of 15.0% for wheat.

How can I run CropProphEU as an HTTP server?

Install with `pip install crop-mcp[http]` and run `crop-mcp --http --port 8080`. Connect via SSE at `http://your-server:8080/sse`.

What data sources are used for the predictions?

Comments

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