July 2026 Release (AI Assistant with custom Knowledge base, AB-Line Grids, Trials, Exports, Mobile app)
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GeoPard MCP Capabilities

Full capability reference for GeoPard MCP: what an AI assistant can read, analyze, create, and export in your GeoPard account.

GeoPard MCP Capabilities

GeoPard MCP gives compatible AI assistants permissioned access to your GeoPard account. It works with your real farm data. It can analyze field variability, create operational outputs, and send them to machinery.

Use it to create zones maps, prescription maps, sampling plans, and machine-ready files. This reduces manual preparation time while keeping review and approval in your hands.

For setup, see Connect GeoPard MCP and Verify GeoPard MCP Connection.

Every data tool runs under your OAuth session. The assistant accesses only farms, fields, and datasets available to your GeoPard user.

Capability map

Group
What it does

Discovery

Find farms, fields, and field data layers, including topography

Analytics

Calculate vegetation statistics, terrain context, and agronomic equations

Zones and VRA

Create zones maps and assign product rates

Yield data quality

Clean, calibrate, and generate yield datasets

Sampling

Create grid and zone-based sampling plans with routing

Export and machinery

Export files, push to John Deere, and create WorkPlans

Navigation

Open precise GeoPard views for visual review

Discovery and context

The assistant first resolves your farm and field context. This grounds every answer in your data.

Tool
Purpose

searchFarms

List and filter farms

searchFields

Find fields by farm, name, or filters

searchSatelliteImages

Find field imagery within a date range

searchSoilDatasets

Find soil lab and sensor datasets

searchTopographyDatasets

Find topography maps: DEM, slope, aspect, hillshade, TPI, TRI, and roughness

searchYieldDatasets

Find harvest datasets by field and season

searchAsAppliedDatasets

Find machinery application records

searchZonesMaps

Find zones maps, geometries, and assigned rates

searchEquationMaps

Find previously generated equation maps

searchSamplingPlans

Find plans by field, type, status, or zones map

searchTrials

Find rate and variety trials

searchProvider

Search organizations, farms, and fields and other data layers in John Deere, CNH, and AGCO.

Projection control. Searches support ids, summary, statistics, and full projections. Use compact results for listings. Request full details only when geometries or attribute statistics are needed. This reduces round trips on large accounts.

Analytics

Vegetation index statistics on any geometry

searchSatelliteImageryByGeometry calculates index statistics for a Point, MultiPoint, Polygon, or MultiPolygon over a date range. Use it to inspect a suspect area, compare zones, or assess trial strips.

  • Providers: Sentinel-2, Landsat 4, 5, 7, 8, 9, and Planet.

  • Indices: NDVI, EVI, EVI2, RVI, LAI, OSAVI, SAVI, GNDVI, IPVI, GCI, WDRVI, RCI, SBI, GFPI, NDMI, MSI, CCCI, MCARI, TCARI, MCARI_OSAVI, TCARI_OSAVI, MCARI1, NDWI, NIR, and NDYI.

Topography and terrain

searchTopographyDatasets finds the terrain layers available for a field. Use it to explain water movement, erosion risk, cold spots, and yield patterns that imagery alone does not show.

  • Layers: DEM, slope, aspect, hillshade, combined hillshade, TPI, TRI, and roughness.

  • Filters: farm, field, specific topography map UUIDs, and status SAVED, EXECUTED, ERROR, or EMPTY.

  • Projections: ids, summary, statistics, and full, as with other searches.

A farm or field filter is required, because topography maps belong to fields.

Terrain attributes feed straight into generateEquationMap. Combine slope with soil and imagery to place lime and drainage work, reduce seeding on eroded ridges, or set variable tillage depth. Topography maps can also be pushed to John Deere as Maps Layers for in-cab context.

Equation-based agronomy

generateEquationMap runs transparent formulas across multiple layers and saves the result as a map.

  • Input variables can use imagery indices, soil attributes, yield data, as-applied data, topography, zones maps, and equation maps.

  • Dry run defaults to true. It validates syntax with sample values before generation.

  • NumPy support enables conditional logic with functions such as np.where and np.isnan.

Choose a manual grid or an AB-line grid. AB-line grids use machine working width, headlands, sections, application length, and turning radius. This aligns prescriptions with actual field operations.

Supported purposes are GENERAL, SEEDING, FERTILIZING, SPRAYING, and IRRIGATION.

Geometry and raster access

Tool
Purpose

fetchGeoJson

Retrieve a GeoJSON FeatureCollection from a GeoPard WFS URL

getGeoMapUrls

Resolve rendered map URLs for visual review

Zones and variable rate

Tool
Purpose

saveZonesMap

Create zones from Polygon or MultiPolygon geometries, with optional rates and colors

assignZonesMapRates

Assign up to three products' rates to an existing map

Each product has a name, rate unit, and optional price per unit. One map can include MAP, urea, and seed rates. Supported units include metric and imperial mass, volume, seed counts, currency per area, and tillage depth.

assignZonesMapRates updates an existing map. The first call returns a rate comparison preview. GeoPard writes changes only after explicit confirmation.

Yield data quality

Tool
Purpose

cleanCalibrateYieldDataset

Clean and calibrate a yield dataset

generateSyntheticYieldDataset

Create a yield layer when measured harvest data is unavailable

Cleaning options include auto-cleaning, attribute min/max filters, sigma filters, and the USDA protocol. The USDA workflow supports crop-specific yield, moisture, velocity, timing, swath, and overlap settings.

Calibration options can target a field average or total. They can clamp values to a defined range. They can also calibrate by machine path with adjustable smoothing.

Synthetic yield supports corn, corn silage, soybeans, wheat, cotton, rice, barley, oats, sorghum, canola, sunflower, rapeseed, and rye. Set a target average or total, harvest year, and date.

Yield cleaning and calibration require a pre-flight check. Review dataset statistics and confirm ambiguous target attributes before corrections run.

Soil sampling plans

generateSamplingPlan creates or updates GRID and ZONE plans for a field.

  • Placement: GeoPard Core Line, Optimized Coverage, NZ, or W patterns.

  • Routing: Zone-by-zone routing or smart ordering across zones.

  • Sampling: Set points per zone, depth, and Core or Composite techniques.

Select analysis methods including Olsen, Bray, Mehlich, DTPA, soil carbon, soil profile nitrate, moisture, texture, plant tissue, grain sampling, scouting, irrigation water, and manure. Label templates keep plans and lab submissions consistent.

Plans are upserted. The assistant can adjust existing pins or routes without creating duplicates.

Export and machinery

Tool
Purpose

exportData

Export zones and equation maps as a downloadable archive

exportToJohnDeereAsFiles

Push an exported archive to John Deere Operations Center

exportToJohnDeereAsMapsLayers

Push a GeoPard entity as a Maps Layer

createJohnDeereWorkPlan

Create a seeding or application WorkPlan from a prescription

importJohnDeereData

Start an asynchronous John Deere import into GeoPard

Export as SHAPEFILE_MULTIPOLYGON, SHAPEFILE_POLYGON, or ISOXML. Trial plot geometries can be included without overlapping parent-zone rates.

Maps Layers support zones, equations, imagery, soil, yield, and topography. This gives operators useful visual context alongside prescriptions.

Navigation and session

Tool
Purpose

buildAppUrl

Build a deep link to a farm, field, asset group, or dataset

parseAppUrl

Extract context from a GeoPard app URL

clearSession

Clear session data

Deep links support the final review. Open the exact map in GeoPard before a field operation.

Typical workflow

  1. Resolve context. Find the farm and field. List available layers.

  2. Assess variability. Calculate index statistics. Review soil, topography, and yield statistics.

  3. Build the prescription. Validate an equation. Generate an equation map or zones with rates.

  4. Review and export. Inspect the prescription map, then export it or send it to John Deere.

  5. Learn after harvest. Clean yield data. Compare it with as-applied data. Refine next season's logic.

This workflow helps target inputs where they deliver the best return. It also reduces time between analysis and field execution.

Example prompts

  • For field X, give me Sentinel-2 NDVI statistics for the last 60 days. Show where variability is highest.

  • List the topography maps for field X. Use slope and TPI to explain the low-yield strips in the 2025 harvest.

  • Build a nitrogen equation using NDVI and soil organic matter. Validate it, then generate a 20 m grid.

  • Create a four-zone fertilizing map for field X. Use MAP rates of 120, 100, 85, and 70 kg/ha. Show the preview before saving.

  • Clean the 2025 corn yield dataset using the USDA protocol. Calibrate the total to 1,240 tonnes.

  • Build a zone-based sampling plan with three cores per zone, 20 cm depth, Mehlich3, and smart routing.

  • Push the prescription map to my John Deere organization as a WorkPlan.

Guardrails

  • Scoped access. OAuth-backed access respects each user's entitlements.

  • Confirmation gates. Destructive writes require a preview and explicit approval.

  • Dry runs. Equations are validated before map generation.

  • Pre-flight checks. Yield corrections require reviewed statistics and confirmed attributes.

  • Your data stays yours. GeoPard formats your data for reasoning. You retain ownership and control.

GeoPard MCP supports decisions. It does not replace local agronomic judgment. Validate rates, equations, and units against crop plans, soil tests, labels, and local regulations before application.

Related pages

PreviousVerify GeoPard MCP Connection
NextOptimal Tillage Depth

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