OpenWeather Agro MCP. Get actionable field metrics in a single chat session.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
OpenWeather Agro accesses critical agricultural data—including NDVI trends, soil temperature, evapotranspiration rates, and frost risk—directly through your AI client. You get immediate access to metrics like Growing Degree Days (GDD) and Enhanced Vegetation Index (EVI), allowing you to plan irrigation schedules or assess crop health without leaving the chat window.
What your AI agents can do
Get crop health index
Provides a single score to gauge the overall health of your crop field at a specific date.
Get current weather
Retrieves real-time weather data necessary for immediate farming operations like spraying or harvesting.
Get evapotranspiration
Calculates the total water loss from both soil and plants, which is key to setting accurate irrigation schedules.
The server provides a single Crop Health Index (CHI) metric, giving you a quick score of the field's current status for easy comparison.
You can run get_evapotranspiration to accurately measure how much water the crop is using, which dictates your watering schedule.
Use get_historical_ndvi or get_historical_evi to analyze if current growth patterns match previous years' performance on the same date.
Run get_frost_risk when you need to know if low temperatures are expected, allowing you time to deploy protective measures like wind machines.
The agent calculates Growing Degree Days (GDD) and provides multi-day weather forecasts (get_weather_forecast) to set precise operational windows.
Check get_current_weather for immediate conditions, or use get_soil_temperature to verify if the ground is ready for seed germination.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
OpenWeather Agro: 12 Tools for Field Data Analysis
These twelve tools let you gather every necessary environmental metric—from current weather to historical growth indices—to make data-backed decisions in the field.
019d75eaget crop health index
Provides a single score to gauge the overall health of your crop field at a specific date.
019d75eaget current weather
Retrieves real-time weather data necessary for immediate farming operations like spraying or harvesting.
019d75eaget evapotranspiration
Calculates the total water loss from both soil and plants, which is key to setting accurate irrigation schedules.
019d75eaget evi
Gets the Enhanced Vegetation Index, useful for monitoring extremely dense or high-biomass crops where NDVI might saturate.
019d75eaget frost risk
Assesses the risk of frost damage and provides recommended protective measures based on predicted low temperatures.
019d75eaget growing degree days
Calculates accumulated heat units (GDD) to predict key developmental stages for a specific crop type.
019d75eaget historical ndvi
Retrieves time-series data showing how vegetation health has changed across an entire growing season for trend analysis.
019d75eaget ndvi
Returns the Normalized Difference Vegetation Index, a standard metric to check general crop density and vigor on a given day.
019d75eaget satellite imagery
Accesses metadata and URLs for visual imagery, letting you inspect field boundaries or look for physical damage spots.
019d75eaget soil temperature
Gives the surface soil temperature reading, which determines if the ground is warm enough for seeds to germinate.
019d75eaget weather forecast
Provides a multi-day weather outlook needed to plan planting, spraying windows, and harvest logistics.
019d75eaget weather history
Retrieves past weather data using Unix timestamps, allowing comparison of current conditions against years of records.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with OpenWeather Agro, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
OpenWeather Agro MCP Server
Your AI client calls this server for specialized agricultural data, pulling metrics like soil temperature, NDVI trends, and evapotranspiration rates. You get immediate access to key farming numbers—like Growing Degree Days (GDD) and the Enhanced Vegetation Index (EVI)—without ever leaving your chat window.
Assessing Overall Crop Condition
get_crop_health_index gives you a single score that gauges the field's overall health on any specific date, making it simple to compare performance across different zones. get_ndvi returns the Normalized Difference Vegetation Index, which is your standard metric for checking general crop density and vigor right now. For monitoring extremely dense or high-biomass crops where NDVI might saturate, you use get_evi to get the Enhanced Vegetation Index.
To track how vegetation health has changed over an entire growing season, run get_historical_ndvi, which retrieves time-series data comparing current growth patterns against past years. You can also access visual metadata and URLs for imagery using get_satellite_imagery, letting you inspect field boundaries or spot physical damage spots immediately.
Water Management and Soil Conditions
get_evapotranspiration calculates the total water loss from both soil and plants, which dictates exactly how much you need to irrigate. You check get_soil_temperature for a surface reading that tells you if the ground is warm enough for seeds to germinate. For immediate operational checks, get_current_weather retrieves real-time conditions necessary for spraying or harvesting.
When you plan ahead, get_weather_forecast provides a multi-day outlook needed to set precise planting windows and harvest logistics. You can also pull deep historical data by using get_weather_history, which accesses past weather records via Unix timestamps, letting you compare current conditions against years of recorded history.
Predicting Risk and Timing
get_frost_risk assesses the chance of frost damage and provides concrete protective measures based on predicted low temperatures. To set optimal planting or harvest timing, your agent calculates Growing Degree Days (GDD), which are accumulated heat units predicting key developmental stages for any specific crop type. You use get_weather_forecast when you need a multi-day outlook to plan spraying windows; meanwhile, get_current_weather handles immediate operational decisions.
Your AI agent acts like your field meteorologist and data analyst rolled into one. Instead of jumping between multiple dashboards or running separate queries, the server pulls all these disparate action points—from soil heat readings to 5-day predictions—and gives you actionable data in natural language.
How OpenWeather Agro MCP Works
- 1 Subscribe to the OpenWeather Agro server and enter your unique API key.
- 2 Ask your AI client a natural language question, like 'What's my irrigation plan for next week?'
- 3 The agent calls multiple tools—for example, combining
get_evapotranspirationwithget_weather_forecast—and returns a cohesive recommendation.
The bottom line is that your AI client handles the complex data stitching; you just ask the question and get an actionable answer.
Who Is OpenWeather Agro MCP For?
This tool is for people who need to make critical, high-stakes decisions based on environmental variables. If you're a farmer tired of checking three different websites for weather, soil moisture, and NDVI trends, this is for you. It cuts through the noise so you know exactly when (and if) to apply water or fertilizer.
Analyzing long-term data sets by comparing get_historical_ndvi trends and tracking GDD accumulation across different years.
Generating client reports that combine current weather (get_current_weather) with risk assessments like get_frost_risk to recommend actionable mitigation strategies.
Scheduling daily tasks by checking get_soil_temperature before planting and using get_evapotranspiration for immediate irrigation adjustments.
What Changes When You Connect
- Automate irrigation scheduling. Instead of guessing, let the agent use
get_evapotranspirationand cross-reference it withget_weather_forecastto calculate precise water needs for your acreage. - Know when to panic (or not). Use
get_frost_riskdays ahead of time; if the prediction shows a high risk, you know exactly which protective measures—like wind machines—to activate. - Track growth over years. Don't just look at today's data. Running
get_historical_ndvilets you compare this season's progress to last year’s yield curve instantly. - Guide planting decisions accurately. Check
get_soil_temperaturebefore buying seed stock, ensuring the ground is warm enough for germination. It saves labor and money on failed starts. - Analyze canopy density with EVI. If your crop has a very dense leaf cover, use
get_eviinstead of standard NDVI to get accurate readings where the vegetation index usually flattens out.
Real-World Use Cases
Checking for drought stress
A farmer notices patchy growth. They ask their agent: 'What's my current water status?' The agent runs get_evapotranspiration and compares it to the 5-day forecast from get_weather_forecast. The result tells them they need immediate, targeted irrigation, solving a multi-day planning problem in one prompt.
Planning harvest timing
A consultant needs to advise on harvesting. They ask: 'When is the best window for my grain?' The agent runs get_growing_degree_days and cross-references it with a multi-day forecast from get_weather_forecast, giving a precise date range that minimizes spoilage risk.
Evaluating early season health
An agronomist needs to know if the field is ready. They ask: 'Is the soil warm enough for planting?' The agent runs get_soil_temperature and immediately advises on viability, preventing expensive delays waiting for warmer ground.
Comparing season performance
A researcher wants to see if a new variety performs better than the old one. They ask: 'Show me NDVI trends for both fields over the last three years.' The agent uses get_historical_ndvi and compares multiple seasonal time series, making data-driven comparisons impossible before.
The Tradeoffs
Only checking today's weather
A farmer only checks 'what is the current weather?' and plans a spray application. They fail to realize that rain is predicted in 48 hours, wasting product.
→
Always check get_weather_forecast first. If rain is coming, adjust your plan immediately; don't rely on just the get_current_weather reading.
Confusing NDVI vs EVI
Using standard NDVI on a tropical crop with very dense canopy coverage results in inaccurate, saturated readings that mislead decision-making.
→
If your crop is known for high biomass or dense foliage, use get_evi instead of get_ndvi. It handles those conditions better.
Ignoring historical context
A user sees a low NDVI reading and assumes the field is failing. They forget to check if this year's start date was significantly delayed due to late spring weather.
→
Always run get_historical_ndvi alongside the current reading. That trend data shows whether the low score is unusual or normal for this time of year.
When It Fits, When It Doesn't
Use this server if your decision requires merging multiple environmental variables into a single actionable plan—specifically, when you need to balance immediate needs (like today's water use from get_evapotranspiration) with future risks (like frost or rain from get_weather_forecast). This is for complex modeling. Don't use it if you just want to know the basic weather; that’s better handled by a simple, standalone forecast API. Similarly, if your only goal is visual damage assessment of large areas, get_satellite_imagery works well, but don't mistake it for soil health—you still need get_soil_temperature data for that.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by OpenWeather. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Dealing with siloed environmental data shouldn't require jumping between five different dashboards.
Today, if you want a full picture of your field, you have to open the weather site for temperature. Then you pull up a separate satellite view for NDVI. After that, you jump into an irrigation system dashboard just to see how much water was used yesterday. It's copy-pasting metrics from one tab to another until your eyes hurt.
With this MCP server, you ask the question—for example, 'Should I irrigate and what risks am I taking?' The agent pulls `get_evapotranspiration`, checks `get_soil_temperature` for root activity, runs a `get_frost_risk` assessment, and gives you one answer. It's all integrated.
OpenWeather Agro MCP Server: Get actionable field data in a single chat session.
Manual checks for soil readiness are tedious. You check the weather, then you find the ground temp API, and finally, you calculate if that temperature is above the minimum required for your seed type. This takes time, and time costs money when planting windows are small.
Now, asking 'Is the ground ready to plant?' triggers `get_soil_temperature` and gives you a definitive yes or no, complete with the necessary data points. You stop guessing based on general advice and start acting on verified metrics.
Common Questions About OpenWeather Agro MCP
How do I get current weather using get_current_weather? +
You ask for 'the current weather at my farm.' The agent calls get_current_weather and provides real-time conditions, which is useful immediately before spraying or harvesting.
What's the difference between get_ndvi and get_historical_ndvi? +
Use get_ndvi for a single snapshot of vegetation health today. Use get_historical_ndvi when you need to see how the NDVI has trended over months or years, which is better for detecting long-term stress.
Can I use get_evapotranspiration just for watering? +
Yes. It calculates total water loss (from soil and plants). You give the agent your location and date, and it provides the rate needed to plan precise irrigation schedules.
How do I check if there's frost risk for my crops? +
Ask 'Is there a frost risk tonight?' The agent uses get_frost_risk to return critical metrics like predicted low temperatures and whether protective measures are needed.
What is the best way to check growth stages? (Using get_growing_degree_days) +
You ask the agent to 'calculate GDD for my wheat field.' The tool tracks heat accumulation, giving you a quantifiable measure of crop development progress.
What date format does the `get_soil_temperature` tool require? +
It requires the YYYY-MM-DD format. You must provide the specific date to get accurate, satellite-derived soil thermal data for planting or root activity assessment.
When should I use `get_evi` instead of `get_ndvi`? +
Use EVI when monitoring dense canopies, high-biomass crops, or tropical areas. EVI is more sensitive than NDVI in these conditions and less affected by soil background.
How do I use `get_weather_forecast` for long-term planning? +
You pass a date range or relative timeframe to access the multi-day forecast. This helps plan activities like spraying, planting, and harvest timing weeks in advance.
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.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
More in this category
Open-Meteo Climate & Ensemble
Project the future of our planet: IPCC climate simulations to 2100, multi-model ensemble forecasts, and long-term temperature trends — the data backbone for ESG and climate policy AI.
ClinicalTrials.gov
Search the world's largest registry of clinical research studies — covering diseases, drugs, and experimental therapies across all phases.
Blockchain.com Data
Access real-time Bitcoin blockchain data via Blockchain.com — query blocks, transactions, and addresses directly from any AI agent.
You might also like
Linear
Streamline issue tracking and project management via Linear — list teams, query issues, create comments and inspect cycles directly from any AI agent.
Atlan
Search and discover data assets, business glossaries, classifications, policies, and personas directly via your AI agent.
Nager.Date
Manage public holidays worldwide — audit global events and calendars via AI.