How to Use the EOSDA Agriculture Satellite Data MCP in Mastra AI
Build resilient, self-healing crop monitoring workflows using Mastra AI and live satellite feeds.
Works with every AI agent you already use
…and any MCP-compatible client
Connect EOSDA Agriculture Satellite Data MCP to Mastra AI
Create your Vinkius account to connect EOSDA Agriculture Satellite Data 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.
Automated crop analysis workflows with Mastra AI
`create_vegetation_task` acts as the trigger for your automated agricultural monitoring pipelines powered by this MCP server. Your agent initiates the index calculation for a specific field and hands the task ID off to the workflow engine. If the external API experiences a temporary hiccup, Mastra's built-in retry logic keeps the pipeline alive. The system automatically backs off and retries until the calculation successfully registers.
Multi-dataset imagery search pipelines
`search_multi_dataset` allows your workflows to scan both Landsat and Sentinel databases in a single step. The tool outputs cloud cover metrics and scene IDs for your automated filters to evaluate. You can set up conditional branches that automatically reject scenes with more than twenty percent cloud cover. This ensures your downstream analysis only uses high-quality, clear imagery.
Dynamic index verification using MCP tools
`get_available_indices` provides your agent with a real-time list of supported vegetation calculations. Your workflow can query this list before launching a task to ensure the requested index is fully supported. This prevents runtime errors when agronomists request newer or specialized spectral analyses. The agent dynamically adjusts its parameters based on what the server currently supports.
Set up EOSDA Agriculture Satellite Data MCP in Mastra AI
Prerequisites
- Node.js 18+ and a TypeScript project
-
@mastra/mcp+@mastra/corepackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install @mastra/mcp @mastra/coreplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Configure the MCPClient
Create an
MCPClientwith your Vinkius endpoint as aURLobject. 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'stoolsobject. All EOSDA Agriculture Satellite Data tools become native Mastra tools. - 4
Run with any model
Swap
openai("gpt-4o")for any AI SDK-compatible provider. Callagent.generate()and the agent routes tool calls through MCP automatically.
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
const mcpClient = new MCPClient({
id: "eosda-agriculture-satellite-data-mcp-client",
servers: {
"eosda-agriculture-satellite-data-mcp": {
url: new URL(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
),
},
},
});
const agent = new Agent({
name: "EOSDA Agriculture Satellite Data Agent",
model: openai("gpt-4o"),
instructions: "You have access to EOSDA Agriculture Satellite Data tools.",
tools: {
...(await mcpClient.listTools()),
},
});
const result = await agent.generate(
"List recent EOSDA Agriculture Satellite Data transactions"
);
console.log(result.text); 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 Agriculture Satellite Data MCP in Mastra AI
Use it with your favorite AI tools
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