How to Use the Estimote MCP in Mastra AI

Q: How does Mastra AI query tag hierarchies from Estimote Cloud?

The agent executes listfleettags to retrieve all defined tags and their associated device counts. Mastra AI uses this taxonomy to filter analytics queries and route reports to the correct store operations teams.

Q: Can this setup fetch real-time sensor data from physical locations?

Yes, the pipeline calls getbeacontelemetry to check temperature, light, and pressure readings. Your agent uses this data to monitor environmental conditions in your physical stores and flag anomalies.

Automate Estimote beacon provisioning and fleet analytics workflows using this MCP server and Mastra AI.

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Connect Estimote MCP to Mastra AI

Create your Vinkius account to connect Estimote 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 Estimote with Mastra AI

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Automate Store Provisioning Workflows

`create_physical_location` instantiates a new physical deployment site within your Mastra AI workflow. The agent executes this step, then immediately runs `list_beacon_devices` to find unassigned hardware nearby. If the location setup fails, Mastra's built-in retry engine catches the error and executes another attempt. This keeps your physical deployment pipeline running smoothly without requiring a developer to manually restart the provisioning script.

Monitor Battery Life with MCP Server Alerts

`list_beacon_devices` fetches current battery levels and firmware versions for your entire hardware fleet. Your Mastra AI agent runs this tool on a cron schedule, filtering for devices that drop below critical thresholds. When low battery levels are detected, the workflow triggers an alert for your field maintenance crew. This prevents dead beacons from interrupting your physical location tracking before shoppers walk through the door.

Process Proximity Analytics Automatically

`get_device_analytics` pulls aggregated detection counts, dwell times, and unique visitor metrics directly into your agent's decision engine. Your Mastra AI pipeline analyzes this foot traffic data to determine which retail zones are performing best. The agent then uses `assign_tag_to_beacon` to dynamically re-tag hardware in high-traffic zones. This lets you adjust your physical marketing targets based on actual physical store engagement.

Setup guide

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

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

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

Mastra AI connects to the MCP server to automatically retry failed operations like `update_beacon_settings` with exponential backoff. If the cloud shadow sync fails, the agent schedules a retry without crashing your backend.

Yes, you can configure Mastra AI to pause the workflow before calling `update_beacon_settings` or `remove_beacon_device`. The agent requests manual sign-off before committing permanent changes to your hardware fleet.

The agent executes `list_fleet_tags` to retrieve all defined tags and their associated device counts. Mastra AI uses this taxonomy to filter analytics queries and route reports to the correct store operations teams.

Yes, the pipeline calls `get_beacon_telemetry` to check temperature, light, and pressure readings. Your agent uses this data to monitor environmental conditions in your physical stores and flag anomalies.

Vinkius manages your Estimote MCP server credentials using ephemeral, single-token authentication. Your raw MAC addresses and physical site coordinates are processed in memory and never stored on persistent disks, keeping your hardware topology private.

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