OneSoil MCP for AI. Track crop health and manage fields with simple chat commands.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
OneSoil manages farm data and field boundaries through your AI agent. It pulls together hyper-local weather forecasts, historical NDVI vegetation indices, and current satellite imagery for any specific plot of land.
You can plan scouting trips or check crop health status without leaving your chat window.
What AI agents can do with OneSoil Automation
Create field
Defines and adds a new field boundary to your account.
Get current weather
Retrieves the immediate weather conditions for specific coordinates.
Get weather history
Pulls detailed historical weather data using specified field coordinates.
You can list all existing field boundaries or define new ones within your account.
The tool retrieves historical Normalized Difference Vegetation Index (NDVI) scores to track plant growth over time.
It provides current conditions, 7-day forecasts, and historical records based on specific latitude and longitude coordinates.
The agent lists available Sentinel-2 imagery for a field so you can plan analysis or scouting trips.
Ask an AI about this
Waiting for input…
What AI agents can do with OneSoil: 9 Tools for Precision Farming
These tools let you manage field boundaries, pull environmental data, check crop health metrics, and track hyper-local weather conditions all through conversation.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using OneSoil on VinkiusCreate Field
Defines and adds a new field boundary to your account.
Get Current Weather
Retrieves the immediate weather conditions for specific coordinates.
Get Weather History
Pulls detailed historical weather data using specified field coordinates.
Delete Field
Removes an existing field boundary from your record.
Get Field
Retrieves all core metadata and details for a single, specified field.
List Images
Shows what Sentinel-2 satellite imagery is available for a given field.
Get Ndvi
Gathers historical NDVI values to chart the vegetation health of a specific area over time.
List Fields
Provides a complete list of all field boundaries registered in your account.
Get Weather Forecast
Predicts the weather conditions for the next seven days at specified coordinates.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with OneSoil, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by OneSoil. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 9 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The headache of juggling farm data apps, Solved with Vinkius AI Gateway
Today, checking on a single field means logging into five different platforms: one for boundary mapping (GIS), one for satellite views, another for historical weather, and two more just to check NDVI graphs. You spend twenty minutes copying coordinates from one dashboard and pasting them into another just to get the full picture.
With this MCP, all that manual switching disappears. You simply ask your agent for a composite report—'Give me the 7-day forecast and the latest satellite view for Plot Alpha.' And you get it instantly. It’s like having an expert agronomist sitting next to you who already knows where every piece of data lives.
OneSoil MCP: Instant access to farm intelligence
No more manually pulling NDVI reports and then searching for a corresponding rainfall chart. The agent combines the `get_ndvi` analysis with historical data from `get_weather_history`, giving you context immediately.
You don't just get data points; you get actionable answers. It drastically cuts down the research time needed to make planting or treatment decisions.
What your AI can actually do with this
This MCP lets you manage complex agricultural operations using natural conversation instead of jumping between dozen different software dashboards. Need to know if the cornfield needs water? Ask your agent directly. It handles fetching current weather, running a 7-day forecast for precise coordinates, and pulling historical NDVI data—all in one go.
It’s about getting actionable insights on crop health and resource management without ever switching apps. You can list all existing fields or create brand new boundaries using GeoJSON geometries. This MCP lives in the Vinkius catalog, making it easy for any compatible client to access this deep dataset. If you're working with large-scale farming data, this is your single source of truth.
019ea5fb-8e71-739a-9220-98eb7231c44f Here's how it actually works
The bottom line is you talk to your AI client using simple language instead of writing complex API calls or navigating menus.
First, subscribe to the MCP and enter your OneSoil API Key into your AI client.
Next, ask your agent for specific data points, like 'What is the NDVI history for field ID 123?' or 'Give me the weather forecast for coordinates X, Y.'
Finally, your agent processes the request against the OneSoil data and delivers a summary of findings right in your chat.
Who is this actually for?
Agronomists, Farm Managers, and AgTech Developers use this MCP daily. If you spend time comparing weather reports against crop growth maps, these tools save hours of manual data aggregation.
Provides clients with better recommendations by quickly checking historical NDVI trends and comparing them to past weather patterns.
Keeps track of field boundaries, monitors satellite image availability, and organizes all farm data without logging into multiple vendor portals.
Integrates precision agriculture data directly into analysis scripts or custom workflows via your coding agent.
What Changes When You Connect
Stop juggling separate weather services, satellite platforms, and GIS software. This MCP pulls all environmental data into one conversation, giving you a single view of your farm's status.
Get deep insights into plant growth using the get_ndvi tool. Instead of sifting through raw graphs, ask for historical trends and get an immediate assessment of vegetation health.
Plan fieldwork efficiently by listing available satellite images with list_images. You know exactly what data you have before you even step out in the truck.
Avoid guessing about conditions. Use get_weather_forecast or get_current_weather to get precise, hyper-local reports based on your field coordinates, not general regional forecasts.
Manage your assets cleanly by using list_fields and create_field. You can keep an accurate, conversational record of every boundary change without updating complex databases.
See it in action
Diagnosing a crop problem
A farmer notices yellowing in one corner of the field. They ask their agent to run get_ndvi for that area, compare it to the historical data, and then pull the surrounding week's weather using get_weather_history. The agent flags a drop in NDVI coinciding with low rainfall.
Planning next season's boundaries
A farm manager needs to map out new plots. They first run list_fields to see what exists, and then use the create_field tool to draw a new boundary using GeoJSON coordinates for a fallow area.
Preparing for equipment rental
A developer needs to know if they can plan spraying operations. They ask the agent to check both list_images and get_field details, ensuring the plot is correctly defined and that recent high-resolution imagery is available.
Checking for immediate risks
A technician arrives on site. They don't want to wait for a physical report; they ask for get_current_weather based on the GPS coordinates, getting instant information about wind speed or rain likelihood.
The honest tradeoffs
Analyzing data without boundaries
Asking 'What was the NDVI last month?' without telling the MCP which field. The agent fails because it doesn't know what area to analyze.
Always start by listing your assets with list_fields or retrieving a specific plot using get_field. Then, ask for data like 'What was the NDVI history for Field ID 456?'
Ignoring coordinates
Asking 'What's the weather right now?' without providing latitude and longitude. The system cannot pull hyper-local data.
For any weather query, you must provide precise location details. Use get_current_weather or get_weather_forecast followed by the required coordinates.
Confusing status with action
Thinking the agent can magically fix dry soil or predict harvest yields from one prompt. It only reports data.
The MCP provides information, not solutions. Use get_ndvi to assess health; then, consult an agronomist for recommendations on what actions to take.
When It Fits, When It Doesn't
Use this MCP if your job involves analyzing geo-spatial data, tracking crop cycles, or needing reliable environmental metrics like NDVI and hyper-local weather. It is perfect when you need a single, conversational interface for multiple specialized agricultural tools.
Don't use it if you only need basic inventory management (like counting supplies) or financial reporting. If your primary task involves payroll processing or managing employee records, stick to dedicated HR systems. This MCP handles the physical and environmental data of the field itself.
Questions you might have
How do I check my field boundaries with OneSoil MCP? +
You can list all your existing fields using list_fields to see a summary, or use get_field if you know the specific ID. If you need to add one, use create_field.
What does NDVI measure in OneSoil MCP? +
NDVI measures vegetation health. By calling get_ndvi, your agent retrieves historical scores that show how well the plants are growing over time relative to their environment.
Can I get weather data for a specific plot of land using OneSoil MCP? +
Yes, you can. You must provide coordinates and specify if you need current conditions (get_current_weather), a 7-day outlook (get_weather_forecast), or past records (get_weather_history).
Is OneSoil MCP better than using standalone mapping services? +
It's better because it integrates everything. Instead of opening a map service, then another weather API, this MCP combines both into one chat conversation.
What if I need to check satellite images for multiple fields? +
You first use list_fields to get the list, and then run list_images on each field ID. This keeps your analysis organized and efficient.
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