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EOSDA MCP Server for Windsurf 12 tools — connect in under 2 minutes

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Windsurf brings agentic AI coding to a purpose-built IDE. Connect EOSDA through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.

Vinkius supports streamable HTTP and SSE.

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Classic Setup·json
{
  "mcpServers": {
    "eosda": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
EOSDA
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* 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

About EOSDA MCP Server

Connect your EOSDA Agriculture API to any AI agent and take full control of satellite-based crop monitoring, vegetation index analysis, weather tracking, and precision agriculture through natural conversation.

Windsurf's Cascade agent chains multiple EOSDA tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 12 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.

What you can do

  • Field Management — List and register agricultural fields with boundaries, crop types, and planting dates
  • Vegetation Indices — Calculate 17+ indices (NDVI, EVI, NDRE, MSAVI, NDMI, etc.) from Sentinel-2 and Landsat
  • NDVI Time Series — Track vegetation health trends across entire growing seasons
  • EVI Time Series — Monitor enhanced vegetation index for high-biomass and tropical crops
  • NDMI Time Series — Monitor crop water content and irrigation needs
  • Satellite Imagery — Retrieve raw satellite imagery bands from multiple satellite sources
  • Weather Data — Access 20+ years of historical weather data with 1800+ parameters
  • Weather Forecast — Get forecasts from 15 days to 7 months for agricultural planning
  • Soil Moisture — Monitor soil moisture levels at different depths for irrigation scheduling
  • Zoning Maps — Generate productivity and vegetation health zoning maps for precision agriculture
  • Index Map Rendering — Create visual vegetation index maps with customizable colormaps
  • Custom Field Registration — Add new fields with GeoJSON boundaries for satellite monitoring

The EOSDA MCP Server exposes 12 tools through the Vinkius. Connect it to Windsurf in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect EOSDA to Windsurf via MCP

Follow these steps to integrate the EOSDA MCP Server with Windsurf.

01

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"

02

Add the server

Paste the JSON configuration above into mcp_config.json

03

Save and reload

Windsurf will detect the new server automatically

04

Start using EOSDA

Open Cascade and ask: "Using EOSDA, help me...". 12 tools available

Why Use Windsurf with the EOSDA MCP Server

Windsurf provides unique advantages when paired with EOSDA through the Model Context Protocol.

01

Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention

02

Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively

03

JSON-based configuration means zero code changes: paste a URL, reload, and all 12 tools are immediately available

04

Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts

EOSDA + Windsurf Use Cases

Practical scenarios where Windsurf combined with the EOSDA MCP Server delivers measurable value.

01

Automated code generation: ask Cascade to fetch data from EOSDA and generate models, types, or handlers based on real API responses

02

Live debugging: query EOSDA tools mid-session to inspect production data while debugging without leaving the editor

03

Documentation generation: pull schema information from EOSDA and have Cascade generate comprehensive API docs automatically

04

Rapid prototyping: combine EOSDA data with Cascade's code generation to scaffold entire features in minutes

EOSDA MCP Tools for Windsurf (12)

These 12 tools become available when you connect EOSDA to Windsurf via MCP:

01

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

02

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

03

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

04

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

05

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

06

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

07

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

08

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

09

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

10

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

11

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

12

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

Example Prompts for EOSDA in Windsurf

Ready-to-use prompts you can give your Windsurf agent to start working with EOSDA immediately.

01

"Show me the NDVI trend for my corn field over the 2025 growing season."

02

"What is the 15-day weather forecast and current soil moisture for my soybean field?"

03

"Generate a productivity zoning map for my wheat field with 4 zones."

Troubleshooting EOSDA MCP Server with Windsurf

Common issues when connecting EOSDA to Windsurf through the Vinkius, and how to resolve them.

01

Server not connecting

Check Settings → MCP for the server status. Try toggling it off and on.

EOSDA + Windsurf FAQ

Common questions about integrating EOSDA MCP Server with Windsurf.

01

How does Windsurf discover MCP tools?

Windsurf reads the mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.
02

Can Cascade chain multiple MCP tool calls?

Yes. Cascade is an agentic system. it can plan and execute multi-step workflows, calling several tools in sequence to accomplish complex tasks without manual prompting between steps.
03

Does Windsurf support multiple MCP servers?

Yes. Add as many servers as needed in mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.

Connect EOSDA to Windsurf

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.