How to Use the Particle IoT MCP in Vercel AI SDK
Stream real-time sensor data from Particle IoT directly into your AI SDK frontend. Build live dashboards that react to device state.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Particle IoT MCP to Vercel AI SDK
Create your Vinkius account to connect Particle IoT to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Gemini
Key Capabilities
Real-time device monitoring with AI SDK
Pipe live sensor readings straight to your UI components. When you trigger `read_variable`, the data streams immediately into your state management. Stop waiting for spinners. Your users see temperature or moisture updates the second the device reports them to the cloud.
Interactive hardware controls
Bind your UI buttons to `call_function` to toggle actuators or reset firmware modes. The connection is direct and handles the execution flow without extra middleware. Your frontend acts as a remote control for hardware. It's built for rapid feedback loops between the user and their physical devices.
Inventory management in code
Use `get_devices` to populate your application lists dynamically. You'll always know which hardware is online and ready for input. Checking device health via `ping_device` happens behind the scenes. Your interface stays clean while the logic handles the connectivity checks.
Set up Particle IoT MCP in Vercel AI SDK
Prerequisites
- Node.js 18+ and a TypeScript project
-
ai+@modelcontextprotocol/sdkpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install ai @modelcontextprotocol/sdkplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Create the Streamable HTTP transport
Use
StreamableHTTPClientTransportwith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Discover and use tools
Call
mcpClient.tools()to auto-discover all Particle IoT tools. Pass them directly togenerateText()orstreamText()— no manual schema definitions needed. - 4
Works with any model provider
Swap
openai("gpt-4o")for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.
import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
const transport = new StreamableHTTPClientTransport(
new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);
const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "List recent Particle IoT transactions",
});
console.log(text);
await mcpClient.close();Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Particle IoT. 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Particle IoT MCP in Vercel AI SDK
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