Taranis MCP Server

Returns detection locations (GPS coordinates), threat types (weeds, diseases, pests, nutrient deficiencies), severity levels, confidence scores, affected area estimates, and recommended actions. Detections are classified by AI models trained on millions of field images for sub-millimeter accuracy. Essential for early threat identification, targeted scouting, and precision treatment planning. AI agents should use this when users ask "show me all detections in my field", "what threats were detected in field X", or need comprehensive threat analysis before planning field operations. Optional threatType filters detections by specific threat category. Get all AI-detected crop threats (weeds, diseases, pests, nutrient deficiencies) in a field

Returns disease locations, pathogen identification where possible, severity levels (early, moderate, advanced), affected plant parts, and recommended fungicide treatments. Essential for early disease intervention, fungicide planning, and yield loss prevention. AI agents should reference this when users ask "what diseases are in my soybean field", "show disease progression over time", or need disease-specific analysis for crop protection decisions. Get crop disease detections and severity assessments for a field

Essential for understanding field context before analyzing detections, planning scouting missions, or generating management recommendations. AI agents should reference this when users ask "tell me about this field", "what crop is planted in field X", or need detailed field metadata for context-aware analysis. Get detailed information about a specific agricultural field

Returns field names, IDs, boundaries (GeoJSON polygons), area in hectares/acres, crop type, planting dates, and monitoring status. Essential for farm management overview, field inventory, and selecting target fields for threat detection and scouting analysis. AI agents should use this when users ask "show me all fields in my organization", "list monitored fields", or need to identify available fields for detection or flight queries. Optional orgId filters fields by specific organization. List all agricultural fields monitored by Taranis for an organization

Returns orthomosaic mosaics, digital surface models (DSM), digital terrain models (DTM), normalized difference vegetation index (NDVI) maps, and true-color RGB composites. Essential for visual crop assessment, change detection between flights, and downloading high-resolution imagery for GIS analysis. AI agents should reference this when users ask "show me the latest imagery from this flight", "get the NDVI map for flight X", or need specific imagery products for field analysis. Get ultra-high-resolution imagery products from a specific flight mission

Returns flight dates, times, aircraft type, imagery resolution, weather conditions during flight, coverage percentage, and processing status. Essential for understanding imagery acquisition history, assessing data quality, and selecting specific flights for detailed analysis. AI agents should use this when users ask "show me all flights over my corn field", "what imagery was captured last week", or need flight metadata before accessing specific imagery products. List all drone or aircraft flights that captured imagery for a specific field

Supports indices including NDVI (Normalized Difference Vegetation Index), NDRE (Normalized Difference Red Edge), GNDVI (Green NDVI), and custom band combinations. Returns imagery layers, statistical summaries (mean, min, max, std), and zone classifications. Essential for crop vigor assessment, variable rate application planning, and growth stage monitoring. AI agents should reference this when users ask "show me NDVI map for my field", "get multispectral analysis", or need vegetation index data for precision agriculture planning. Get multispectral imagery and vegetation indices (NDVI, NDRE, GNDVI) for a field

Returns deficiency locations, severity estimates, affected growth stages, and variable rate fertilization recommendations. Essential for precision nutrient management, yield optimization, and cost-efficient fertilization planning. AI agents should use this when users ask "does my field have nutrient deficiencies", "where do I need to apply nitrogen", or need nutrient-specific analysis for variable rate application planning. Get nutrient deficiency detections and fertilization recommendations for a field

Returns organization names, IDs, contact information, and field counts. Essential for multi-account management, selecting target organizations for field analysis, and understanding the scope of monitored agricultural operations. AI agents should use this when users ask "show me all my organizations", "list farms I have access to", or need to identify available organizations before querying fields or detections. List all organizations available to the user in Taranis platform

Returns specific action items including ground truth verification locations, recommended scouting patterns, treatment suggestions, timing recommendations, and priority levels. Essential for field team coordination, targeted scouting missions, and data-driven treatment decisions. AI agents should use this when users ask "what should I scout for in my field this week", "give me scouting recommendations", or need AI-generated action plans based on latest imagery analysis. Get AI-powered scouting recommendations and action plans for a field

Returns threat categories, overall severity ratings (low, medium, high, critical), affected area percentages, trend analysis (increasing, stable, decreasing), and priority rankings. Essential for quick field health assessment, prioritizing scouting missions, and making informed treatment decisions. AI agents should reference this when users ask "what is the overall threat level in my field", "summarize field health status", or need a high-level threat overview before diving into individual detections. Get consolidated threat summary and severity assessment for a field

Returns weed locations, estimated coverage area, species classification, growth stage, and herbicide resistance indicators. Essential for targeted spot spraying, herbicide selection, and resistance management. AI agents should use this when users ask "where are the weeds in my field", "what weed species were detected", or need weed-specific analysis for precision herbicide application. Get specific weed species detections and infestation maps for a field