How to Use the AerisWeather MCP in Mastra AI

Q: Can Mastra AI trigger workflows based on AerisWeather alerts?

Yes. You can set up a step that calls getalerts and uses conditional branching to trigger downstream actions like SMS notifications when warnings are active.

Build reliable weather workflows in Mastra AI using real-time AerisWeather triggers and automated retries.

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Connect AerisWeather MCP to Mastra AI

Create your Vinkius account to connect AerisWeather 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 AerisWeather with Mastra AI

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Build resilient storm-warning workflows

Mastra AI workflows require rock-solid data sources when executing automated decisions. This MCP Server exposes `get_alerts` to feed active storm warnings directly into your agent's decision loops. If the initial API call fails due to network hiccups, the framework automatically retries with exponential backoff. Your automated safety routines keep running without manual intervention.

Route complex weather queries with Mastra AI conditional steps

Sometimes a simple forecast isn't enough. You can build a workflow that calls `get_conditions` to check for rain, then branches based on the precipitation filter. The agent uses `get_places` to resolve the user's location, decides if a batch query is needed, and executes `get_batch` only when handling multiple properties.

Deploy automated weather monitoring agents to the cloud

Deploying agents that watch the skies shouldn't require complex infrastructure. This MCP integration lets your Mastra AI agents pull current observations via `get_observations` on a cron schedule. You can deploy the entire workflow to your cloud provider with a single command. The agent runs autonomously, checking atmospheric conditions and alerting your team when thresholds are crossed.

Setup guide

Set up AerisWeather 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 AerisWeather 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: "aerisweather-mcp-client",
  servers: {
    "aerisweather-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent AerisWeather 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 AerisWeather. 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 AerisWeather MCP in Mastra AI

Instantiate the MCP client using new MCPClient with the server URL. Then, list the tools and spread them directly into your agent's tool array.

Yes. You can set up a step that calls get_alerts and uses conditional branching to trigger downstream actions like SMS notifications when warnings are active.

The workflow engine uses built-in retry logic with exponential backoff. If get_forecasts times out, Mastra retries the call automatically before failing the step.

Yes. Mastra supports human-in-the-loop validation. You can pause the workflow after calling get_places and wait for approval before running expensive batch queries.

Every coordinate pair and city ID processed by the server is handled in a zero-trust, ephemeral V8 sandbox. Your geographic queries are never cached or exposed to third parties.

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