Can my AI read sensor data from my Particle devices?

Yes! Use the `read_variable` tool with your device ID and the variable name (e.g., temperature, humidity, soilMoisture). Your device must expose this variable in its firmware using `Particle.variable()`. The AI will return the current sensor value in real-time. You can find available variables using `get_device_info`.

How do I remotely turn on a pump or actuator connected to a Particle device?

Use the `call_function` tool with your device ID and the function name (e.g., pumpOn, valveOpen). The function must be exposed in your device firmware using `Particle.function()`. You can pass an optional argument (like duration or intensity) to control the actuator behavior. Check available functions with `get_device_info`.

Can I check if my IoT device is online and responding?

Yes! Use the `ping_device` tool to instantly check the online status of any Particle device. You can also use `get_devices` to see the online status of all your devices at once. If a device shows as offline, it may be powered off, disconnected from Wi-Fi, or experiencing firmware issues.

Particle IoT MCP Server for Google ADK 8 tools — connect in under 2 minutes

Name: Particle IoT
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 8 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Particle IoT as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.

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Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="particle_iot_agent",
    instruction=(
        "You help users interact with Particle IoT "
        "using 8 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

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<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 Particle IoT MCP Server

Connect your Particle IoT API to any AI agent and take full control of your IoT device fleet, sensor monitoring, remote actuator control, and event management through natural conversation.

Google ADK natively supports Particle IoT as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 8 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Device Management — List all connected devices, check online status, rename devices, and manage ownership
Sensor Monitoring — Read real-time sensor data from cloud variables (temperature, humidity, soil moisture, etc.)
Remote Control — Execute cloud functions to control actuators, trigger calibrations, and change device modes
Event Publishing — Broadcast custom events to the cloud for logging, alerting, and webhook integration
Health Monitoring — Ping devices to verify connectivity and troubleshoot communication issues
Fleet Overview — Get comprehensive views of your entire IoT deployment and device status

The Particle IoT MCP Server exposes 8 tools through the Vinkius. Connect it to Google ADK 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 Particle IoT to Google ADK via MCP

Follow these steps to integrate the Particle IoT MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 8 tools from Particle IoT via MCP

Why Use Google ADK with the Particle IoT MCP Server

Google ADK provides unique advantages when paired with Particle IoT through the Model Context Protocol.

Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Particle IoT

Production-ready features like session management, evaluation, and deployment come built-in — not bolted on

Seamless integration with Google Cloud services means you can combine Particle IoT tools with BigQuery, Vertex AI, and Cloud Functions

Particle IoT + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Particle IoT MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Particle IoT and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Particle IoT tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Particle IoT regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Particle IoT

Particle IoT MCP Tools for Google ADK (8)

These 8 tools become available when you connect Particle IoT to Google ADK via MCP:

call_function

Functions are defined in the device firmware and can control actuators (turn on pump, open valve), trigger calibrations, change device modes, or perform system tasks. Accepts a single string argument (max 63 characters) to pass to the function. Returns the function execution result code. Essential for remote device control, automation, and actuator management. AI agents should use this when users ask "turn on the water pump on device X", "trigger calibration on sensor Y", or need to remotely control any function exposed by a device. Execute a cloud function on a specific Particle IoT device

get_device_info

Essential for understanding device capabilities before interacting with it. AI agents should reference this when users ask "what variables does device X expose", "what functions can I call on device Y", or need to understand the specific interface of a device. Get detailed information about a specific Particle IoT device

get_devices

Returns device IDs, names, online status, firmware versions, and last connection times. Essential for device inventory management, monitoring connection health, and selecting specific devices for interaction. AI agents should use this when users ask "show me all my devices", "list connected sensors", or need to identify available devices before reading variables or calling functions. List all Particle IoT devices connected to your account

ping_device

Returns current online/offline status and last heard time. Essential for connectivity diagnostics, health monitoring, and verifying device availability before attempting to read variables or call functions. AI agents should reference this when users ask "is device X online", "check connectivity for sensor Y", or need to troubleshoot device communication issues. Check if a specific Particle IoT device is online and responsive

publish_event

Events are broadcast to all subscribed listeners and can be used for inter-device communication, logging, alerting, or triggering external workflows via webhooks. Requires an event name and optional data string (max 255 bytes for data). Essential for sending alerts, logging custom data, and integrating with external systems like IFTTT or custom dashboards. AI agents should use this when users ask "send a low moisture alert", "publish a system status event", or need to broadcast data from the cloud to devices or webhooks. Publish a custom event to the Particle Cloud

read_variable

Variables are defined in the device firmware and can represent sensor readings (temperature, humidity, soil moisture), system status, or configuration values. Returns the variable name, data type, and current value. Essential for real-time sensor monitoring, data collection, and system state verification. AI agents should use this when users ask "what is the temperature from sensor X", "read soil moisture from device Y", or need to get the current value of any sensor or status variable. Read the current value of a cloud variable from a specific device

rename_device

This name appears in the console and API responses, making it easier to identify devices. Essential for device organization, fleet management, and improving readability of device lists. AI agents should use this when users ask "rename device X to Greenhouse Sensor 1", "change the name of device Y to Pump Controller", or need to update device naming for better organization. Rename a specific Particle IoT device

unclaim_device

This action is irreversible for the current account and should be used when transferring device ownership or decommissioning devices. Essential for device lifecycle management, transferring devices, and account cleanup. AI agents should use this when users ask "remove device X from my account", "unclaim sensor Y so I can sell it", or need to manage device ownership. WARNING: This requires confirmation as it removes access to the device. Remove a Particle IoT device from your account

Example Prompts for Particle IoT in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Particle IoT immediately.

"Show me all my connected Particle devices and their online status."

"Read the current soil moisture from my greenhouse sensor."

"Turn on the irrigation pump for 15 minutes."

Troubleshooting Particle IoT MCP Server with Google ADK

Common issues when connecting Particle IoT to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Particle IoT + Google ADK FAQ

Common questions about integrating Particle IoT MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.