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Estimote MCP Server for Mastra AI 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Estimote through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.

Vinkius supports streamable HTTP and SSE.

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

async function main() {
  // Your Vinkius token. get it at cloud.vinkius.com
  const mcpClient = await createMCPClient({
    servers: {
      "estimote": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Estimote Agent",
    instructions:
      "You help users interact with Estimote " +
      "using 10 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with Estimote?"
  );
  console.log(result.text);
}

main();
Estimote
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High SecurityEnterprise-grade
IAMAccess control
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DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Estimote MCP Server

Connect your Estimote Cloud account to any AI agent and take full control of your beacon fleet management and proximity data workflows through natural conversation.

Mastra's agent abstraction provides a clean separation between LLM logic and Estimote tool infrastructure. Connect 10 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.

What you can do

  • Fleet Orchestration — List all Estimote beacons including Proximity, Location, and Stickers, returning identifiers, hardware types, and current battery levels natively
  • Device Shadow Management — Retrieve detailed configurations and status for specific beacons and update broadcasting parameters or transmission power through the shadow system
  • Proximity Analytics — Pull detection counts, unique visitor estimates, and dwell time distributions over specified periods to measure real-world engagement
  • Real-time Telemetry — Access live sensor data including temperature readings, ambient light levels, motion detection, and barometric pressure from supported hardware
  • Physical Location Auditing — Register and manage venues, buildings, or stores, providing geographic coordinates for beacon organization and analytics grouping
  • Taxonomy & Tagging — List fleet tags and assign organizational labels to devices for logical grouping and proximity campaign targeting
  • Decommissioning Oversight — Permanently remove beacon devices from your cloud account while maintaining physical broadcasting for legacy integrations

The Estimote MCP Server exposes 10 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Estimote to Mastra AI via MCP

Follow these steps to integrate the Estimote MCP Server with Mastra AI.

01

Install dependencies

Run npm install @mastra/core @mastra/mcp @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

Mastra discovers 10 tools from Estimote via MCP

Why Use Mastra AI with the Estimote MCP Server

Mastra AI provides unique advantages when paired with Estimote through the Model Context Protocol.

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Estimote without touching business code

02

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

03

TypeScript-native: full type inference for every Estimote tool response with IDE autocomplete and compile-time checks

04

One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure

Estimote + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the Estimote MCP Server delivers measurable value.

01

Automated workflows: build multi-step agents that query Estimote, process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed Estimote as a first-class tool in your product's AI features with Mastra's clean agent API

03

Background jobs: schedule Mastra agents to query Estimote on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using Estimote tools alongside other MCP servers

Estimote MCP Tools for Mastra AI (10)

These 10 tools become available when you connect Estimote to Mastra AI via MCP:

01

assign_tag_to_beacon

If the tag does not exist, it is created automatically. A device can have multiple tags. Use to organize beacons by floor, zone, store section, or campaign. Tags persist in the cloud and do not require physical beacon access. Assign an organizational tag to a specific Estimote beacon device, adding it to a logical group for fleet management, analytics filtering, and proximity campaign targeting

02

create_physical_location

After creating a location, assign beacon devices to it for organized fleet management and location-scoped analytics. Use when deploying beacons at a new site. Register a new physical location (store, office, venue) in Estimote Cloud, providing the site name, street address, and geographic coordinates for beacon fleet organization and analytics grouping

03

get_beacon_details

The identifier is the beacon MAC address or Estimote Cloud ID. Returns the full device shadow including pending settings changes. Use to diagnose beacon configuration issues or verify firmware update status. Retrieve detailed configuration and status for a specific Estimote beacon device, including its current broadcasting power, advertising interval, sensor readings, firmware version, and physical location assignment

04

get_beacon_telemetry

Returns the most recent sensor readings from the beacon. Not all sensors are available on all hardware models. Estimote Proximity Beacons support temperature and motion; Location Beacons add light and pressure sensors. Use for environmental monitoring and occupancy detection. Retrieve real-time sensor telemetry data from a specific Estimote beacon, including temperature readings, ambient light levels, accelerometer motion detection, magnetometer orientation, and barometric pressure where supported by hardware

05

get_device_analytics

Supports query parameters for date range (from, to), device identifier, and tag filtering. Returns aggregated metrics showing how many mobile devices detected each beacon. Use for foot traffic analysis, retail engagement measurement, and space utilization studies. Retrieve proximity analytics data for Estimote beacon devices, including detection counts, unique visitor estimates, dwell time distributions, and engagement metrics over a specified time period

06

list_beacon_devices

estimote.com. Returns a paginated array of beacon objects. Each beacon includes its MAC address (the most reliable identifier), iBeacon UUID/Major/Minor, Eddystone namespace/instance, and shadow settings. Use to inventory your deployed beacon fleet. List all Estimote beacon devices registered in your Estimote Cloud account, returning device identifiers, hardware types (Proximity/Location/Sticker), battery levels, firmware versions, and current configuration status

07

list_fleet_tags

Returns an array of tag objects with names and associated device counts. Tags are the primary organizational mechanism in Estimote Cloud. Use to understand your current fleet taxonomy before assigning or filtering devices. List all organizational tags defined in your Estimote Cloud account, which are used to group and categorize beacon devices by location, use case, department, or any custom classification scheme

08

list_physical_locations

Returns an array of location objects. Locations serve as containers for organizing beacons by physical site. Each location can have multiple beacon devices assigned to it. Use to audit your deployment footprint across multiple sites. List all physical locations (venues/buildings/stores) registered in your Estimote Cloud account, returning location names, addresses, geographic coordinates, and the number of beacons deployed at each site

09

remove_beacon_device

WARNING: This permanently removes the device from your fleet. The beacon will continue broadcasting but will no longer be managed by Estimote Cloud. Only use when decommissioning hardware. The device can be re-added later via the Estimote app. Permanently remove an Estimote beacon device from your Cloud account, deleting all associated configuration, analytics history, and location assignments. This action is irreversible

10

update_beacon_settings

Changes are queued in the cloud shadow and synchronized to the physical beacon when a device running the Estimote SDK connects to it. Common updates include name, tags, broadcasting power (dBm), and advertising interval (ms). Update the configuration of a specific Estimote beacon device by modifying its broadcasting parameters, advertising interval, transmission power, or attached metadata tags through the Estimote Cloud shadow system

Example Prompts for Estimote in Mastra AI

Ready-to-use prompts you can give your Mastra AI agent to start working with Estimote immediately.

01

"List all my beacons and their current battery status"

02

"What is the current temperature at 'Beacon-XYZ'?"

03

"Show me visitor analytics for the 'Main Store' tag from last month"

Troubleshooting Estimote MCP Server with Mastra AI

Common issues when connecting Estimote to Mastra AI through the Vinkius, and how to resolve them.

01

createMCPClient not exported

Install: npm install @mastra/mcp

Estimote + Mastra AI FAQ

Common questions about integrating Estimote MCP Server with Mastra AI.

01

How does Mastra AI connect to MCP servers?

Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
02

Can Mastra agents use tools from multiple servers?

Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
03

Does Mastra support workflow orchestration?

Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.

Connect Estimote to Mastra AI

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.