OpenWeather Agro MCP Server
Access agricultural weather and satellite data via OpenWeather — monitor NDVI, soil temperature, evapotranspiration, frost risk, and GDD from any AI agent.
Ask AI about this MCP Server
Vinkius supports streamable HTTP and SSE.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
What is the OpenWeather MCP Server?
The OpenWeather MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to OpenWeather via 12 tools. Access agricultural weather and satellite data via OpenWeather — monitor NDVI, soil temperature, evapotranspiration, frost risk, and GDD from any AI agent. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (12)
Tools for your AI Agents to operate OpenWeather
Ask your AI agent "What is the NDVI for my corn field at coordinates 41.8780, -93.0977 on April 1st?" and get the answer without opening a single dashboard. With 12 tools connected to real OpenWeather data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
OpenWeather Agro MCP Server capabilities
12 toolsCHI provides a single metric for overall crop health, making it easier to track field conditions over time and compare across fields. Essential for quick field health assessment, prioritizing scouting missions, and communicating crop status to stakeholders. AI agents should use this when users ask "what is the overall crop health score for my field", "get a quick health assessment", or need a simplified crop condition metric. Date format: YYYY-MM-DD. Get Crop Health Index (CHI) for comprehensive crop condition assessment
Essential for daily farming decisions, spray application timing, harvest planning, and frost protection. AI agents should use this when users ask "what is the weather like at my farm right now", "should I spray pesticides today", or need current weather data for agricultural operations. Get current weather conditions for agricultural decision making
ET combines soil evaporation and plant transpiration, providing the most accurate measure of crop water use. Essential for precision irrigation scheduling, water resource management, and drought assessment. AI agents should reference this when users ask "what is the evapotranspiration rate for my field", "calculate irrigation needs", or need crop water use data for irrigation planning. Date format: YYYY-MM-DD. Get evapotranspiration rates for irrigation scheduling and water management
EVI is more sensitive than NDVI in high-biomass regions and less affected by atmospheric conditions and soil background. Essential for monitoring dense canopies, tropical crops, and areas with high vegetation cover. AI agents should reference this when users ask "what is the EVI for my dense crop area", "monitor high-biomass vegetation", or need enhanced vegetation index for areas where NDVI saturates. Date format: YYYY-MM-DD. Get EVI (Enhanced Vegetation Index) for high-biomass crop monitoring
Returns risk levels (low, moderate, high, critical), predicted frost timing, and recommended protection measures. Essential for frost-sensitive crops (fruits, vegetables, vineyards), irrigation-based frost protection, and crop insurance documentation. AI agents should reference this when users ask "is there frost risk for my orchard tonight", "assess frost danger for my crops", or need frost warning data for crop protection planning. Get frost risk assessment for crop protection planning
GDD measures heat accumulation used to predict crop development stages, pest emergence, and harvest timing. Essential for phenology tracking, variety selection, and timing agricultural operations. AI agents should reference this when users ask "calculate GDD for my corn field this season", "track crop development stages", or need heat unit accumulation data for agricultural planning. Date format: YYYY-MM-DD. Calculate Growing Degree Days (GDD) for crop development tracking
Returns time-series NDVI values showing vegetation health progression, stress detection, and recovery patterns. Essential for seasonal crop performance comparison, drought impact assessment, and long-term field health monitoring. AI agents should reference this when users ask "show me NDVI trends for my field over the growing season", "compare vegetation health between seasons", or need historical vegetation index data for agricultural trend analysis. Date format: YYYY-MM-DD. Get historical NDVI trends for seasonal vegetation health analysis
NDVI ranges from -1 to 1, with higher values (0.6-0.9) indicating healthy dense vegetation and lower values (0.2-0.5) indicating stressed or sparse vegetation. Essential for crop health monitoring, growth stage assessment, and yield prediction. AI agents should use this when users ask "what is the NDVI for my field on this date", "check crop vegetation health", or need satellite-based vegetation index data for agricultural analysis. Date format: YYYY-MM-DD. Get NDVI (Normalized Difference Vegetation Index) for crop health assessment
Returns imagery metadata and access URLs for visual crop assessment, field boundary verification, and change detection analysis. Essential for remote field monitoring, damage assessment, and visual crop health evaluation. AI agents should use this when users ask "get satellite imagery for my field", "show me the latest satellite view of my farm", or need visual imagery for agricultural monitoring. Date format: YYYY-MM-DD. Zoom: 1-16. Get satellite imagery for visual crop assessment and field monitoring
Soil temperature is critical for seed germination timing, root activity assessment, and nutrient uptake optimization. Essential for planting decisions, irrigation scheduling, and soil health monitoring. AI agents should use this when users ask "what is the soil temperature for planting", "check if soil is warm enough for germination", or need soil thermal data for agricultural planning. Date format: YYYY-MM-DD. Get satellite-derived soil temperature for seed germination and root activity assessment
Essential for planting schedules, harvest timing, spray application windows, and irrigation planning. AI agents should reference this when users ask "what is the weather forecast for my farm this week", "will it rain in the next 5 days", or need forward-looking weather data for agricultural planning. Get multi-day weather forecast for agricultural planning
Essential for comparing current conditions with historical patterns, analyzing crop performance under past weather conditions, and validating crop models. AI agents should use this when users ask "what was the weather like on this date last year", "show me historical weather for my field", or need past weather data for agricultural analysis. Date format: Unix timestamp (seconds since 1970). Get historical weather data for crop analysis and trend assessment
What the OpenWeather Agro MCP Server unlocks
Connect your OpenWeather Agro API to any AI agent and take full control of satellite-based vegetation monitoring, weather-driven agricultural insights, and precision farming data through natural conversation.
What you can do
- NDVI Analysis — Monitor crop vegetation health with satellite-derived NDVI values
- EVI Monitoring — Track enhanced vegetation index for high-biomass and dense canopy areas
- Soil Temperature — Check soil thermal conditions for seed germination and root activity
- Evapotranspiration — Calculate crop water use for precision irrigation scheduling
- Current Weather — Get real-time weather conditions for daily farming decisions
- Weather Forecast — Access 5-day forecasts for planting and harvest planning
- Historical Weather — Retrieve past weather data for crop performance analysis
- Growing Degree Days — Track heat accumulation for crop development staging
- Satellite Imagery — Access satellite imagery for visual field assessment
- Historical NDVI — Analyze vegetation health trends over growing seasons
- Crop Health Index — Get comprehensive crop condition scores
- Frost Risk — Assess frost danger for crop protection planning
How it works
1. Subscribe to this server
2. Enter your OpenWeather API key (appid from your dashboard)
3. Start analyzing agricultural conditions from Claude, Cursor, or any MCP-compatible client
No more manual weather checking or complex satellite data processing. Your AI acts as a dedicated agricultural meteorologist and crop health analyst.
Who is this for?
- Farmers — monitor crop health, plan irrigation, and assess frost risk with satellite and weather data
- Agronomists — analyze NDVI trends, track GDD accumulation, and advise on crop management
- Agricultural Consultants — provide data-driven recommendations based on satellite imagery and weather patterns
- Researchers — access historical vegetation indices and weather data for agricultural studies
Frequently asked questions about the OpenWeather Agro MCP Server
Can my AI check NDVI for my field to assess crop health?
Yes! Use the get_ndvi tool with your field coordinates and a date. NDVI values range from -1 to 1, with 0.6-0.9 indicating healthy dense vegetation and 0.2-0.5 indicating stressed or sparse vegetation. For trend analysis over a growing season, use get_historical_ndvi with a date range. The data comes from satellite imagery processed by OpenWeather algorithms.
How do I calculate irrigation needs using evapotranspiration data?
Use the get_evapotranspiration tool with your field coordinates and date. ET values show how much water your crops are losing through transpiration and soil evaporation. Compare ET with rainfall (from get_current_weather or get_weather_forecast) to determine irrigation deficits. If ET exceeds precipitation, irrigation is needed to replace the difference. For precise scheduling, track daily ET over time and accumulate deficits.
Can I get frost warnings to protect my crops?
Yes! Use the get_frost_risk tool with your field coordinates. It returns frost risk levels (low, moderate, high, critical) based on temperature forecasts and local conditions. For proactive planning, combine with get_weather_forecast to monitor approaching cold fronts. High or critical frost risk indicates you should activate frost protection measures like irrigation, wind machines, or covers.
More in this category
NASA Mars — Rover Photos from the Red Planet
4 toolsBrowse 800,000+ photos taken on the surface of Mars by NASA rovers Curiosity, Opportunity, and Spirit — filter by sol, Earth date, or camera. Access mission manifests and the latest images beamed directly from the Martian surface.
NASA DONKI — Space Weather Intelligence
7 toolsNASA's Space Weather Database: coronal mass ejections (CMEs), solar flares (C/M/X class), geomagnetic storms, interplanetary shocks, solar energetic particles, radiation belt events, and real-time notifications from the DONKI system.
World Bank Economy
4 toolsInstantly query GDP, inflation, economic growth, and financial sector indicators from the World Bank. Zero auth required.
You might also like
Doodle
10 toolsManage group scheduling via Doodle — create meeting polls, track participant votes, handle comments, and close polls directly from any AI agent.
HERE (Location & Maps)
10 toolsBuild with location data via HERE — geocode addresses, calculate routes, track traffic, and get weather.
PedidosYa
14 toolsAutomate restaurant operations on PedidosYa — manage orders, update menus, request couriers, and track deliveries across Latin America from any AI agent.
Connect OpenWeather Agro with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Give your AI agents the power of OpenWeather MCP Server
Production-grade OpenWeather Agro MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.