Integrate Farmonaut with Claude, Cursor, Chatbots & AI Agents MCP Server
GDPR Free for SubscribersCompatible with every major AI agent and IDE
GeminiAdd field on Farmonaut
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
Get crop advisory on Farmonaut
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
Get deforestation alerts on Farmonaut
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
Get evi on Farmonaut
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
Get fields on Farmonaut
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
Get ndvi on Farmonaut
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
Get ndwi on Farmonaut
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
Get sar analysis on Farmonaut
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
Get satellite images on Farmonaut
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
Get soil moisture on Farmonaut
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
Get weather on Farmonaut
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
Get weather forecast on Farmonaut
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
Security & Code Integrity Audit
Every tool in the Farmonaut MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
What happens if the underlying API rate limits my agent?
Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
Can I monitor my crops during cloudy season when optical satellites cannot see?
Yes! Use the get_sar_analysis tool 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.
Farmonaut Capabilities for AI Assistants
Connect your AI agents and chatbots (Claude, ChatGPT, Cursor) with the Farmonaut MCP server to manage operations across the following domains.
Intelligent satellite imagery Management
The Farmonaut server supports direct MCP connections for satellite imagery. This provides Claude with the required permissions to execute the unthinkable functions.
Streamlining crop monitoring
The Farmonaut connection gives ChatGPT direct access to crop monitoring tools. The integration handles the logic required for continuous the unthinkable operations.
Farmonaut. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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