Particle IoT MCP Server for Vercel AI SDK 8 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Particle IoT through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Particle IoT, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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.
The Vercel AI SDK gives every Particle IoT tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 8 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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 Vercel AI SDK 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 Vercel AI SDK via MCP
Follow these steps to integrate the Particle IoT MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 8 tools from Particle IoT and passes them to the LLM
Why Use Vercel AI SDK with the Particle IoT MCP Server
Vercel AI SDK provides unique advantages when paired with Particle IoT through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same Particle IoT integration everywhere
Built-in streaming UI primitives let you display Particle IoT tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Particle IoT + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Particle IoT MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Particle IoT in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Particle IoT tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Particle IoT capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Particle IoT through natural language queries
Particle IoT MCP Tools for Vercel AI SDK (8)
These 8 tools become available when you connect Particle IoT to Vercel AI SDK 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 Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK 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 Vercel AI SDK
Common issues when connecting Particle IoT to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpParticle IoT + Vercel AI SDK FAQ
Common questions about integrating Particle IoT MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Particle IoT with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Particle IoT to Vercel AI SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.