How to Use the EOSDA MCP in Mastra AI

Build resilient Mastra AI workflows that automate EOSDA satellite data processing and irrigation alerts.

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Connect EOSDA MCP to Mastra AI

Create your Vinkius account to connect EOSDA to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup EOSDA with Mastra AI

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Perplexity

Automated field onboarding workflows

`create_field` registers new agricultural boundaries and activates monitoring automatically. Your Mastra AI workflow accepts GeoJSON coordinates, calculates the hectare area, and sets up the initial crop season tracking without human input. The workflow then loops through `get_fields` to verify active monitoring status. If the API fails to register the boundary immediately, Mastra triggers an exponential backoff retry until the MCP Server confirms the field successfully synced.

Conditional irrigation scheduling

`get_soil_moisture` grabs surface and deep subsoil water levels to drive automated watering decisions. The workflow checks moisture anomalies against historical baselines to determine if the field needs attention. If root zone moisture drops below your threshold, the agent calls `get_weather_forecast`. If rain is expected within 48 hours, Mastra branches the logic to delay irrigation. If skies are clear, it approves the watering schedule.

Mastra AI index mapping and zoning

`get_zoning_map` generates productivity zones for variable rate fertilizer application. The MCP Server calculates average index values across different field sections and returns specific management recommendations for your equipment. Bad weather often ruins optical satellite reads. When `get_satellite_imagery` reports high cloud cover percentages, Mastra catches the failure and falls back to `get_ndmi_timeseries` for moisture-based stress detection instead.

Setup guide

Set up EOSDA MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All EOSDA tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "eosda-mcp-client",
  servers: {
    "eosda-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "EOSDA Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to EOSDA tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent EOSDA transactions"
);
console.log(result.text);

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by EOSDA. 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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Common questions about EOSDA MCP in Mastra AI

Install @mastra/mcp and initialize a new MCPClient with your Vinkius server URL. Call listTools() and spread them into your agent's toolset.

You configure requireToolApproval on the agent for specific tools. When the MCP Server returns variable rate application data, the workflow pauses for an agronomist to review it.

Optical satellites get blocked by clouds. You build conditional branches in Mastra that check the cloud cover percentage from the imagery tool and retry on the next overpass date.

The MCP protocol works over standard HTTP or SSE. You can run Mastra locally or deploy it to any cloud provider while connecting to the remote Vinkius endpoint.

Nobody. The MCP Server executes requests through zero-trust network endpoints. When you pull historical climate models for specific coordinates, the transaction occurs in a temporary sandbox that vanishes after execution.

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