# Farmonaut MCP MCP

> Farmonaut provides immediate access to advanced satellite data for farming. Monitor crop health using NDVI and EVI indices, track soil moisture levels across different depths, and get long-range weather forecasts—all from any AI agent conversation. It also detects land use changes and offers AI-driven advice on everything from irrigation scheduling to pest control.

## Overview
- **Category:** the-unthinkable
- **Price:** Free
- **Tags:** satellite-imagery, crop-monitoring, ndvi-analysis, soil-moisture, precision-agriculture, deforestation-detection

## Description

Managing a farm used to mean juggling multiple platforms: one for weather reports, another for soil readings, and a third for satellite imagery analysis. Now, you connect Farmonaut via Vinkius and keep it all in one chat. Your AI agent acts like a dedicated agronomist on call. You can ask it to compare the current crop vigor against historical data, or check if recent deforestation alerts might threaten a section of your property. It doesn't just pull images; it analyzes them. Need to know how much water is in the roots? The MCP handles that. Want to plan for harvest six months out? Get the weather forecast and soil moisture readings needed to make that call, all without leaving your chat window.

## Tools

### get_soil_moisture
Provides current soil moisture levels at multiple depths (surface, root zone) to guide immediate irrigation decisions.

### get_weather_forecast
Delivers forward-looking forecasts spanning weeks or months, essential for seasonal planning and harvesting.

### get_weather
Retrieves historical weather data like temperature, precipitation, and wind for past season analysis.

### add_field
Registers a new farm field by accepting its boundary coordinates, crop type, and planting date for monitoring.

### get_crop_advisory
Generates specific recommendations on irrigation timing, fertilizer use, or pest control based on current field data.

### get_deforestation_alerts
Scans satellite imagery to detect any loss of tree cover or major land clearing in a specified area.

### get_evi
Calculates the enhanced vegetation index (EVI) for detailed monitoring, especially useful for dense tropical canopies.

### get_fields
Lists all monitored agricultural fields, providing their names, boundaries, and current crop type status.

### get_ndvi
Calculates the Normalized Difference Vegetation Index (NDVI) to assess general vegetation health against a scale of -1 to 1.

### get_ndwi
Measures the Normalized Difference Water Index (NDWI), helping determine current water content and irrigation needs.

### get_sar_analysis
Performs Synthetic Aperture Radar analysis, providing all-weather monitoring that penetrates cloud cover for structural data.

### get_satellite_images
Retrieves visual composites of the field using different spectral bands, including true-color and false-color overlays.

## Prompt Examples

**Prompt:** 
```
Show me the NDVI trend for my rice field over the last 3 months.
```

**Response:** 
```
Fetching NDVI data for rice field (field ID: R-2045)... Found 18 satellite observations from Sentinel-2 over the past 3 months. NDVI progression: Month 1 (0.32) — early vegetative stage, Month 2 (0.58) — active tillering, Month 3 (0.74) — peak vegetative vigor. Current average NDVI is 0.74 indicating healthy crop development. The highest NDVI of 0.79 was recorded on the latest clear-sky pass. Would you like crop advisory recommendations based on this trend?
```

**Prompt:** 
```
What is the 7-day weather forecast and current soil moisture for my wheat field?
```

**Response:** 
```
Fetching 7-day forecast and soil moisture for wheat field (field ID: W-1823)... Weather forecast: Next 2 days sunny 26-30°C no rain. Days 3-5: 70% chance of 20mm rainfall. Days 6-7: partly cloudy 24-28°C. Current soil moisture (root zone): 38% — adequate for current growth stage. With 20mm rain expected in 3-5 days irrigation can be delayed. AI advisory: Hold irrigation for now, reassess after rainfall event.
```

**Prompt:** 
```
Get AI crop advisory recommendations for my cotton field this week.
```

**Response:** 
```
Generating AI advisory for cotton field (field ID: C-3156)... Current growth stage: Boll development. Recommendations: 1) IRRIGATION: Apply 25mm this week — soil moisture at 42% with no significant rain forecast. 2) FERTILIZER: Top-dress with potassium (K2O 40kg/ha) to support boll filling. 3) PEST CONTROL: Monitor for bollworm — NDVI shows uniform canopy but scout field edges. 4) HARVEST: Expected harvest window in 4-6 weeks based on current development rate. Priority: Irrigation within 3 days.
```

## Capabilities

### Establish monitoring boundaries
You define new fields by providing their boundary coordinates or GeoJSON polygon for continuous tracking.

### Measure vegetation health indices
The system calculates specific indexes like NDVI and EVI to quantify crop vigor, identifying stress before it's visible to the naked eye.

### Forecast water availability
It provides detailed soil moisture readings at various depths and offers multi-month weather forecasts for irrigation planning.

### Detect land change and risk
You receive alerts identifying areas of deforestation or significant land use changes over time, vital for compliance checks.

### Generate actionable farming advice
The MCP pulls together all data—weather, soil, spectral analysis—to recommend specific actions for fertilizer, pest control, and harvesting.

## Use Cases

### Diagnosing early crop stress
An agronomist needs to know if a field is stressed. They prompt the agent: 'What's wrong with Field 4?' The MCP uses get_ndvi and get_ndwi, cross-referencing them against current soil moisture (get_soil_moisture) to pinpoint water scarcity as the primary issue.

### Planning for a bumper harvest
A farm manager needs to know when to plant. They ask the agent: 'When is the best time to start planting Field 7?' The MCP checks get_weather_forecast and get_soil_moisture, advising on optimal temperature ranges and soil readiness.

### Addressing environmental compliance
A consultant needs to prove no illegal logging occurred. They prompt: 'Check for land use changes in Sector B.' The MCP runs the get_deforestation_alerts tool, providing time-stamped evidence of any unauthorized tree cover loss.

### Optimizing resource usage
A farmer needs to reduce fertilizer waste. They ask: 'Based on my field's current health, what should I apply?' The MCP runs get_crop_advisory, which synthesizes NDVI data and local weather predictions for a precise recommendation.

## Benefits

- Instead of checking 10 different dashboards, you ask your AI agent to combine multiple tools like get_ndvi and get_soil_moisture into one report, making diagnosis immediate.
- The MCP allows for all-weather monitoring using the get_sar_analysis tool. You don't need clear skies; it penetrates clouds to give structural data on crops.
- You can track seasonal changes by combining historical weather (get_weather) with long-term forecasts (get_weather_forecast), letting you predict yield risks months out.
- The system calculates various spectral indices, like get_ndwi and get_evi. This gives deeper insight into water stress or canopy density than basic visuals alone.
- It centralizes the entire workflow—from registering a new plot (add_field) to getting final instructions (get_crop_advisory)—into one conversation flow.

## How It Works

The bottom line is that you talk to your AI agent like you're talking to an expert agronomist; it handles all the complex data retrieval and analysis behind the scenes.

1. First, connect your API key to the Farmonaut MCP via Vinkius. This grants your AI agent access to all satellite data feeds.
2. Next, ask your AI client a question—for instance, 'What is the soil moisture and expected rainfall for my wheat field?'
3. The system runs multiple analyses (weather forecast, get_soil_moisture) and compiles the results into a single, actionable report ready in conversation.

## Frequently Asked Questions

**How do I get historical weather data using get_weather?**
Use the get_weather tool by specifying the field ID and date range. It pulls records for temperature, precipitation, wind speed, and solar radiation from that period.

**Can I use get_ndwi to check my irrigation status?**
Yes. The get_ndwi tool measures water content in crops, which is essential for determining if you need to irrigate right now or wait out a storm.

**Does get_deforestation_alerts require clear skies?**
No. Because it uses satellite imagery and focuses on land cover change detection, it's designed to detect changes regardless of cloud cover.

**What is the difference between NDVI and EVI using get_ndvi and get_evi?**
NDVI measures general vigor. EVI (get_evi) is better for high-biomass crops and dense canopies, offering a more refined analysis when atmospheric interference is a factor.

**How do I start monitoring a new field with add_field?**
Use the add_field tool by providing its boundaries (GeoJSON or coordinates), the crop type, and the planting date. The MCP then activates all necessary monitoring protocols for that plot.

**When I use get_fields, how do I ensure that all my boundaries are recognized for analysis?**
The tool returns field boundaries as GeoJSON polygons. This standardized format ensures every subsequent monitoring request—whether it's calculating NDVI or checking soil moisture—can map accurately and reliably to your defined agricultural area.

**If my location has heavy cloud cover, can I still get reliable data using get_sar_analysis?**
Yes. SAR technology sends radio waves that penetrate clouds and operates day or night. This capability lets you monitor crop structure and detect soil moisture even when standard optical satellites are blocked by weather.

**To get the most accurate recommendations from get_crop_advisory, what data points should I provide?**
The advisory works best with multiple inputs. Pairing it with current soil moisture levels and recent historical weather data helps the AI generate precise, actionable advice for irrigation scheduling and fertilizer use.

**Can my AI calculate NDVI for my rice field and show me the crop health trend?**
Yes! Use the `get_ndvi` tool with your field ID and date range (e.g., date_from=2025-04-01, date_to=2025-10-31). This returns NDVI values for each satellite overpass from Sentinel-2, Landsat, or PlanetScope, showing vegetation health progression. You can also use `get_crop_advisory` for AI-powered recommendations based on the NDVI trends and current growth stage.

**How do I get soil moisture and weather forecast data to plan irrigation?**
Use `get_soil_moisture` with your field ID and date range to check current soil moisture levels at root zone depth. Combine with `get_weather_forecast` (forecast_range=7_days or 15_days) to see upcoming precipitation. Together these tools help determine if and when irrigation is needed. For AI-powered irrigation recommendations, use `get_crop_advisory` with advisory_type=irrigation.

**Can I monitor my crops during cloudy season when optical satellites cannot see?**
Yes! Use the `get_sar_analysis` tool which uses Synthetic Aperture Radar (SAR) data that penetrates clouds and works day/night. SAR provides backscatter values, soil moisture estimates, and crop structure information regardless of weather conditions. This is essential for monitoring in tropical regions, monsoon seasons, or any cloudy conditions where optical satellites like Sentinel-2 cannot provide clear imagery.