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Use Farmonaut with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Access satellite agriculture data via Farmonaut. monitor crop health with NDVI, weather, soil moisture, crop advisory, and deforestation alerts from any AI age

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 12 capabilities

The complete Farmonaut capability set.

These are the exact actions your AI can choose when you ask it to work with Farmonaut.

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 12 available through Farmonaut.

  1. 01

    Add field

    Accepts field boundary as GeoJSON polygon or coordinates, field name, crop type, and planting date. Returns the created field with ID, calculated area, and monitoring activation status. Essential for onboarding new fields into the monitoring system, expanding farm coverage, and setting up new crop seasons. AI agents should use this when users ask "add a new field for monitoring", "register this field boundary", or need to set up satellite monitoring for a new agricultural area. Register a new agricultural field for satellite monitoring

  2. 02

    Get deforestation alerts

    Uses satellite imagery to detect tree cover loss, land clearing, and vegetation changes over time. Essential for conservation compliance, environmental monitoring, carbon credit verification, and land use change detection. AI agents should reference this when users ask "show deforestation alerts in my area", "detect land use changes", or need environmental compliance monitoring. Get deforestation and land change detection alerts

  3. 03

    Get ndvi

    NDVI measures vegetation health and vigor on a scale of -1 to 1, with higher values indicating healthier vegetation. Returns NDVI values, statistics (mean, min, max, std), satellite source, acquisition date, and cloud cover percentage. Essential for crop health assessment, growth stage monitoring, stress detection, and yield prediction. AI agents should use this when users ask "what is the NDVI for my rice field this month", "calculate vegetation health for field X", or need NDVI-based crop health analysis. Calculate NDVI vegetation index for crop health monitoring

  4. 04

    Get ndwi

    NDWI is sensitive to vegetation water content and soil moisture, making it essential for irrigation scheduling, drought monitoring, and water stress detection. Returns NDWI values, statistics, satellite source, and acquisition dates. AI agents should reference this when users ask "what is the water content in my crops", "do I need to irrigate", or need water stress analysis for irrigation planning. Calculate NDWI water index for crop water stress and irrigation monitoring

Capability set02 / 03

05-08

4 capabilities in this set.

Part of 12 available through Farmonaut.

  1. 05

    Get satellite images

    Returns true-color and false-color composites, NDVI overlays, and raw spectral bands. Essential for visual crop assessment, change detection, damage assessment, and downloading imagery for further processing. AI agents should reference this when users ask "show me satellite images of my field from last week", "get latest Sentinel-2 imagery", or need satellite imagery for visual assessment. Retrieve satellite imagery for agricultural fields from multiple sources

  2. 06

    Get soil moisture

    Returns soil moisture levels at different depths (surface, root zone, deep soil), moisture anomalies, and irrigation recommendations. Essential for irrigation scheduling, drought monitoring, water stress detection, and water resource optimization. AI agents should use this when users ask "what is the soil moisture level in my field", "do I need to irrigate", or need soil moisture data for irrigation planning. Get soil moisture data for irrigation scheduling and drought monitoring

  3. 07

    Get evi

    EVI is more sensitive in high-biomass regions and less affected by atmospheric conditions and soil background than NDVI. Essential for monitoring dense canopies, tropical crops, and areas with high atmospheric interference. Returns EVI values, statistics, satellite source, and acquisition dates. AI agents should use this when users ask "show me EVI trends for this field", "how is the canopy developing in high-biomass areas", or need enhanced vegetation index analysis for dense vegetation. Calculate EVI enhanced vegetation index for high-biomass crop monitoring

  4. 08

    Get fields

    Returns field names, boundaries (GeoJSON polygons), area in hectares/acres, crop type, planting dates, and current monitoring status. Essential for farm management overview, field inventory, and selecting target fields for satellite analysis. AI agents should use this when users ask "show me all my fields", "list monitored fields", or need to identify available fields for vegetation index or weather queries. List all agricultural fields monitored in your Farmonaut account

Capability set03 / 03

09-12

4 capabilities in this set.

Part of 12 available through Farmonaut.

  1. 09

    Get sar analysis

    SAR penetrates clouds and works day/night, making it essential for monitoring in cloudy or rainy conditions. Returns backscatter values, soil moisture estimates, crop structure information, and change detection analysis. Essential for all-weather monitoring, flood detection, soil moisture mapping, and crop structure analysis. AI agents should use this when users ask "get SAR analysis for my field during cloudy season", "monitor crops through cloud cover", or need all-weather satellite analysis. Get Synthetic Aperture Radar (SAR) analysis for all-weather crop monitoring

  2. 10

    Get weather

    Includes temperature (air, soil), precipitation, humidity, wind speed/direction, solar radiation, evapotranspiration, and growing degree days. Essential for irrigation planning, frost risk assessment, disease/pest pressure modeling, and yield prediction. AI agents should use this when users ask "what was the weather like on my field last month", "get temperature and rainfall data", or need historical weather analysis for crop management decisions. Get historical and current weather data for agricultural fields

  3. 11

    Get crop advisory

    Returns recommendations for irrigation, fertilization, pest control, harvest timing, and field operations. Essential for data-driven farm management, precision agriculture, and optimizing crop inputs. AI agents should use this when users ask "what should I do in my field this week", "get irrigation and fertilizer recommendations", or need AI-powered crop management advice. Get AI-powered crop management advisories and recommendations

  4. 12

    Get weather forecast

    Includes temperature, precipitation, humidity, wind, and solar radiation forecasts. Essential for planting schedule optimization, harvest timing, irrigation planning, frost protection, and seasonal crop management. AI agents should reference this when users ask "what is the weather forecast for my field next week", "get seasonal precipitation forecast", or need forward-looking weather data for agricultural planning. Get weather forecasts for agricultural planning and irrigation scheduling

Observed, not estimated

979ms average. Fast in production.

Farmonaut is checked daily against the live service.

Daily averagePeak 1232ms
Aug 20Today
Fastest day
776ms
Slowest day
1232ms
14-day trend
Slowing+18%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 12 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Farmonaut, so you can see the experience inside your AI.

It does not authenticate your account with Farmonaut. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Farmonaut Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_feXVkwBoQ7HbICusf0WF8Hr7rtEYe6aJtynJgguc/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Farmonaut capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "farmonaut-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_feXVkwBoQ7HbICusf0WF8Hr7rtEYe6aJtynJgguc/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions Farmonaut owners ask.

  • 01

    Can my AI calculate NDVI for my rice field and show me the crop health trend?

    Yes! Use the get_ndvi capability 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.

  • 02

    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 capabilities help determine if and when irrigation is needed. For AI-powered irrigation recommendations, use get_crop_advisory with advisory_type=irrigation.

  • 03

    Can I monitor my crops during cloudy season when optical satellites cannot see?

    Yes! Use the get_sar_analysis capability 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.

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