OpenWeather Agro MCP Server for Windsurf 12 tools — connect in under 2 minutes
Windsurf brings agentic AI coding to a purpose-built IDE. Connect OpenWeather Agro through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
Vinkius Desktop App
The modern way to manage MCP Servers — no config files, no terminal commands. Install OpenWeather Agro and 2,500+ MCP Servers from a single visual interface.
{
"mcpServers": {
"openweather-agro": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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 OpenWeather Agro MCP Server
Connect your OpenWeather Agro API to any AI agent and take full control of satellite-based vegetation monitoring, weather-driven agricultural insights, and precision farming data through natural conversation.
Windsurf's Cascade agent chains multiple OpenWeather Agro 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
- NDVI Analysis — Monitor crop vegetation health with satellite-derived NDVI values
- EVI Monitoring — Track enhanced vegetation index for high-biomass and dense canopy areas
- Soil Temperature — Check soil thermal conditions for seed germination and root activity
- Evapotranspiration — Calculate crop water use for precision irrigation scheduling
- Current Weather — Get real-time weather conditions for daily farming decisions
- Weather Forecast — Access 5-day forecasts for planting and harvest planning
- Historical Weather — Retrieve past weather data for crop performance analysis
- Growing Degree Days — Track heat accumulation for crop development staging
- Satellite Imagery — Access satellite imagery for visual field assessment
- Historical NDVI — Analyze vegetation health trends over growing seasons
- Crop Health Index — Get comprehensive crop condition scores
- Frost Risk — Assess frost danger for crop protection planning
The OpenWeather Agro 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 OpenWeather Agro to Windsurf via MCP
Follow these steps to integrate the OpenWeather Agro MCP Server with Windsurf.
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Add the server
Paste the JSON configuration above into mcp_config.json
Save and reload
Windsurf will detect the new server automatically
Start using OpenWeather Agro
Open Cascade and ask: "Using OpenWeather Agro, help me...". 12 tools available
Why Use Windsurf with the OpenWeather Agro MCP Server
Windsurf provides unique advantages when paired with OpenWeather Agro through the Model Context Protocol.
Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively
JSON-based configuration means zero code changes: paste a URL, reload, and all 12 tools are immediately available
Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
OpenWeather Agro + Windsurf Use Cases
Practical scenarios where Windsurf combined with the OpenWeather Agro MCP Server delivers measurable value.
Automated code generation: ask Cascade to fetch data from OpenWeather Agro and generate models, types, or handlers based on real API responses
Live debugging: query OpenWeather Agro tools mid-session to inspect production data while debugging without leaving the editor
Documentation generation: pull schema information from OpenWeather Agro and have Cascade generate comprehensive API docs automatically
Rapid prototyping: combine OpenWeather Agro data with Cascade's code generation to scaffold entire features in minutes
OpenWeather Agro MCP Tools for Windsurf (12)
These 12 tools become available when you connect OpenWeather Agro to Windsurf via MCP:
get_crop_health_index
CHI provides a single metric for overall crop health, making it easier to track field conditions over time and compare across fields. Essential for quick field health assessment, prioritizing scouting missions, and communicating crop status to stakeholders. AI agents should use this when users ask "what is the overall crop health score for my field", "get a quick health assessment", or need a simplified crop condition metric. Date format: YYYY-MM-DD. Get Crop Health Index (CHI) for comprehensive crop condition assessment
get_current_weather
Essential for daily farming decisions, spray application timing, harvest planning, and frost protection. AI agents should use this when users ask "what is the weather like at my farm right now", "should I spray pesticides today", or need current weather data for agricultural operations. Get current weather conditions for agricultural decision making
get_evapotranspiration
ET combines soil evaporation and plant transpiration, providing the most accurate measure of crop water use. Essential for precision irrigation scheduling, water resource management, and drought assessment. AI agents should reference this when users ask "what is the evapotranspiration rate for my field", "calculate irrigation needs", or need crop water use data for irrigation planning. Date format: YYYY-MM-DD. Get evapotranspiration rates for irrigation scheduling and water management
get_evi
EVI is more sensitive than NDVI in high-biomass regions and less affected by atmospheric conditions and soil background. Essential for monitoring dense canopies, tropical crops, and areas with high vegetation cover. AI agents should reference this when users ask "what is the EVI for my dense crop area", "monitor high-biomass vegetation", or need enhanced vegetation index for areas where NDVI saturates. Date format: YYYY-MM-DD. Get EVI (Enhanced Vegetation Index) for high-biomass crop monitoring
get_frost_risk
Returns risk levels (low, moderate, high, critical), predicted frost timing, and recommended protection measures. Essential for frost-sensitive crops (fruits, vegetables, vineyards), irrigation-based frost protection, and crop insurance documentation. AI agents should reference this when users ask "is there frost risk for my orchard tonight", "assess frost danger for my crops", or need frost warning data for crop protection planning. Get frost risk assessment for crop protection planning
get_growing_degree_days
GDD measures heat accumulation used to predict crop development stages, pest emergence, and harvest timing. Essential for phenology tracking, variety selection, and timing agricultural operations. AI agents should reference this when users ask "calculate GDD for my corn field this season", "track crop development stages", or need heat unit accumulation data for agricultural planning. Date format: YYYY-MM-DD. Calculate Growing Degree Days (GDD) for crop development tracking
get_historical_ndvi
Returns time-series NDVI values showing vegetation health progression, stress detection, and recovery patterns. Essential for seasonal crop performance comparison, drought impact assessment, and long-term field health monitoring. AI agents should reference this when users ask "show me NDVI trends for my field over the growing season", "compare vegetation health between seasons", or need historical vegetation index data for agricultural trend analysis. Date format: YYYY-MM-DD. Get historical NDVI trends for seasonal vegetation health analysis
get_ndvi
NDVI ranges from -1 to 1, with higher values (0.6-0.9) indicating healthy dense vegetation and lower values (0.2-0.5) indicating stressed or sparse vegetation. Essential for crop health monitoring, growth stage assessment, and yield prediction. AI agents should use this when users ask "what is the NDVI for my field on this date", "check crop vegetation health", or need satellite-based vegetation index data for agricultural analysis. Date format: YYYY-MM-DD. Get NDVI (Normalized Difference Vegetation Index) for crop health assessment
get_satellite_imagery
Returns imagery metadata and access URLs for visual crop assessment, field boundary verification, and change detection analysis. Essential for remote field monitoring, damage assessment, and visual crop health evaluation. AI agents should use this when users ask "get satellite imagery for my field", "show me the latest satellite view of my farm", or need visual imagery for agricultural monitoring. Date format: YYYY-MM-DD. Zoom: 1-16. Get satellite imagery for visual crop assessment and field monitoring
get_soil_temperature
Soil temperature is critical for seed germination timing, root activity assessment, and nutrient uptake optimization. Essential for planting decisions, irrigation scheduling, and soil health monitoring. AI agents should use this when users ask "what is the soil temperature for planting", "check if soil is warm enough for germination", or need soil thermal data for agricultural planning. Date format: YYYY-MM-DD. Get satellite-derived soil temperature for seed germination and root activity assessment
get_weather_forecast
Essential for planting schedules, harvest timing, spray application windows, and irrigation planning. AI agents should reference this when users ask "what is the weather forecast for my farm this week", "will it rain in the next 5 days", or need forward-looking weather data for agricultural planning. Get multi-day weather forecast for agricultural planning
get_weather_history
Essential for comparing current conditions with historical patterns, analyzing crop performance under past weather conditions, and validating crop models. AI agents should use this when users ask "what was the weather like on this date last year", "show me historical weather for my field", or need past weather data for agricultural analysis. Date format: Unix timestamp (seconds since 1970). Get historical weather data for crop analysis and trend assessment
Example Prompts for OpenWeather Agro in Windsurf
Ready-to-use prompts you can give your Windsurf agent to start working with OpenWeather Agro immediately.
"What is the NDVI for my corn field at coordinates 41.8780, -93.0977 on April 1st?"
"Calculate the growing degree days for my wheat field from March 1 to today."
"Is there frost risk for my vineyard tonight? I need to know if I should turn on the wind machines."
Troubleshooting OpenWeather Agro MCP Server with Windsurf
Common issues when connecting OpenWeather Agro to Windsurf through the Vinkius, and how to resolve them.
Server not connecting
OpenWeather Agro + Windsurf FAQ
Common questions about integrating OpenWeather Agro MCP Server with Windsurf.
How does Windsurf discover MCP tools?
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.Can Cascade chain multiple MCP tool calls?
Does Windsurf support multiple MCP servers?
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 OpenWeather Agro with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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.
Connect OpenWeather Agro to Windsurf
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.