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Use EOSDA 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 EOSDA. monitor crop health, vegetation indices, weather, soil moisture, and generate zoning maps from any AI agent.

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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 EOSDA capability set.

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

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 12 available through EOSDA.

  1. 01

    Get evi timeseries

    EVI is more sensitive in high-biomass regions and less affected by atmospheric conditions than NDVI. Returns EVI values per satellite overpass date for trend analysis. Essential for monitoring dense canopies, tropical crops, and areas with high atmospheric interference. AI agents should reference this when users ask "show me EVI trends for this field", "how is the canopy developing", or need enhanced vegetation index analysis for high-biomass crops. Get EVI time series data for enhanced vegetation monitoring over a growing season

  2. 02

    Get ndmi timeseries

    NDMI is sensitive to vegetation water content and is used for drought monitoring, irrigation scheduling, and fire risk assessment. Returns NDMI values per satellite overpass date. Essential for water stress detection, irrigation optimization, drought impact assessment, and harvest timing. AI agents should use this when users ask "show me crop water stress trends", "how is the moisture content changing", or need moisture index analysis for irrigation planning. Get NDMI time series data for crop water stress monitoring

  3. 03

    Get ndvi timeseries

    Returns NDVI values per satellite overpass date, enabling trend analysis of crop health, growth stages, and stress detection. Essential for season-long crop monitoring, growth curve analysis, yield prediction, and identifying problematic periods. AI agents should use this when users ask "show me the NDVI trend for this season", "how has vegetation health changed over the growing season", or need time-series vegetation analysis. Get NDVI time series data showing vegetation health trends over a growing season

  4. 04

    Get satellite imagery

    ) for a specific field and date range. Supports Sentinel-2, Landsat 8/9, MODIS, NAIP, and CBERS-4 sources. Returns image metadata, acquisition dates, cloud cover percentages, band availability, and download URLs. Essential for visual crop assessment, custom band analysis, change detection, and downloading raw imagery for further processing. AI agents should reference this when users ask "show me satellite images of my field from last week", "get Sentinel-2 imagery for field X", or need raw satellite imagery download links. Retrieve raw satellite imagery for a specific field and date range

Capability set02 / 03

05-08

4 capabilities in this set.

Part of 12 available through EOSDA.

  1. 05

    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 reference 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 agricultural fields

  2. 06

    Get vegetation index

    Supports 17+ indices including NDVI (vegetation health), EVI (enhanced vegetation index), GNDVI (green NDVI), NDRE (red edge), MSAVI (soil adjusted), RECI (red edge chlorophyll), NDSI, NDWI (water), SAVI, ARVI, GCI (chlorophyll), SIPI, NBR (burn ratio), MSI (moisture), ISTACK, FIDET, and CCCI. Returns index values, statistics (mean, min, max, std), satellite source (Sentinel-2, Landsat), and cloud cover percentage. Essential for crop health assessment, stress detection, and growth monitoring. AI agents should use this when users ask "what is the NDVI for my corn field this month", "calculate vegetation health for field X", or need vegetation index analysis. Calculate vegetation indices (NDVI, EVI, NDRE, etc.) for a specific field and date range

  3. 07

    Get weather data

    Includes 1800+ weather parameters: temperature (air, soil), precipitation, humidity, wind speed/direction, solar radiation, evapotranspiration, dew point, pressure, and growing degree days. Historical data available since 1979. 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

  4. 08

    Get zoning map

    Returns zone boundaries, average index values per zone, area percentages, and management recommendations. Essential for variable rate application (VRA), precision fertilization, targeted irrigation, and yield optimization. AI agents should use this when users ask "create a zoning map for my field", "generate productivity zones", or need management zone maps for precision agriculture. Generate productivity and vegetation health zoning maps for fields

Capability set03 / 03

09-12

4 capabilities in this set.

Part of 12 available through EOSDA.

  1. 09

    Render index map

    Returns rendered raster images (JPEG, PNG, or GeoTIFF) with color-coded vegetation index values overlaid on field boundaries. Supports colormaps like NDVI (green-yellow-red), thermal, grayscale, and custom color schemes. Essential for field reports, stakeholder communication, visual crop assessment, and creating shareable vegetation maps. AI agents should reference this when users ask "create a color-coded NDVI map of my field", "generate a vegetation health visualization", or need shareable vegetation index images for reports. Generate visual vegetation index maps with customizable colormaps for field visualization

  2. 10

    Get fields

    Returns field names, boundaries (GeoJSON polygons), area in hectares/acres, crop type, planting dates, and current growth stage information. 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 EOSDA account

  3. 11

    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 (15 days to 7 months) for agricultural fields

  4. 12

    Create 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

Observed, not estimated

967ms average. Fast in production.

EOSDA is checked daily against the live service.

Daily averagePeak 1194ms
Aug 21Today
Fastest day
790ms
Slowest day
1194ms
14-day trend
Improving-17%

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 EOSDA, so you can see the experience inside your AI.

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

EOSDA Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_W1riYytnYABpHWpaWtxCVS18WzgQkjJnAYcVAx7d/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 — EOSDA capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "eosda-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_W1riYytnYABpHWpaWtxCVS18WzgQkjJnAYcVAx7d/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 EOSDA owners ask.

  • 01

    Can my AI calculate NDVI for my corn field and show me the vegetation health trend over the growing season?

    Yes! Use the get_ndvi_timeseries capability with your field ID and the growing season date range (e.g., date_from=2025-04-01, date_to=2025-10-31). This returns NDVI values for each satellite overpass, showing vegetation health progression from planting through harvest. You can also use get_vegetation_index with index=NDVI for point-in-time analysis, or render_index_map to generate a visual color-coded NDVI map of your field.

  • 02

    How do I get weather forecasts and soil moisture data to plan irrigation for my fields?

    Use get_weather_forecast with your field ID and forecast_range=15_days or 1_month to get upcoming precipitation and temperature forecasts. Combine this with get_soil_moisture to check current soil moisture levels at root zone depth. Together these capabilities help you determine if and when irrigation is needed. For historical context, use get_weather_data with past dates to understand rainfall patterns and evapotranspiration trends.

  • 03

    Can I generate a zoning map to identify low and high productivity areas within my field?

    Yes! Use the get_zoning_map capability with your field ID. You can specify the vegetation index (NDVI is most common), number of zones (3-5 recommended), and date for analysis. The API returns zone boundaries, average index values per zone, area percentages, and management recommendations. This is essential for variable rate application (VRA), precision fertilization, and targeted irrigation planning.

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