2,500+ MCP servers ready to use
Vinkius

PurpleAir MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect PurpleAir through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
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 PurpleAir, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
PurpleAir
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
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 PurpleAir MCP Server

Access the world's largest hyperlocal air quality dataset through PurpleAir — a global network of over 50,000 low-cost air quality sensors measuring PM2.5, PM10.0, temperature, humidity, pressure, and more. Connect PurpleAir to your AI agent to monitor real-time air quality, track wildfire smoke, analyze pollution trends, and access historical data for any location — all through natural conversation.

The Vercel AI SDK gives every PurpleAir tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through 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

  • Real-Time Air Quality — Get current PM2.5 readings from sensors near any address or coordinate.
  • Historical Analysis — Retrieve time-series data for trend analysis, pollution events, and compliance reporting.
  • Geographic Mapping — Find all sensors within a bounding box for city-wide or regional air quality mapping.
  • Wildfire Smoke Tracking — Monitor PM2.5 spikes during wildfire events across affected areas.
  • Indoor Air Quality — Access indoor sensor data for workplace health and HVAC optimization.
  • CSV Export — Download historical data in CSV format for spreadsheet analysis.
  • Location-Based Queries — Find the closest sensor to any GPS coordinate.
  • Sensor Filtering — Filter sensors by type (indoor/outdoor), fields, and update recency.

The PurpleAir MCP Server exposes 10 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 PurpleAir to Vercel AI SDK via MCP

Follow these steps to integrate the PurpleAir MCP Server with Vercel AI SDK.

01

Install dependencies

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

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

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

04

Explore tools

The SDK discovers 10 tools from PurpleAir and passes them to the LLM

Why Use Vercel AI SDK with the PurpleAir MCP Server

Vercel AI SDK provides unique advantages when paired with PurpleAir through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same PurpleAir integration everywhere

03

Built-in streaming UI primitives let you display PurpleAir tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

PurpleAir + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the PurpleAir MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query PurpleAir in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate PurpleAir tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed PurpleAir capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with PurpleAir through natural language queries

PurpleAir MCP Tools for Vercel AI SDK (10)

These 10 tools become available when you connect PurpleAir to Vercel AI SDK via MCP:

01

get_indoor_sensors

These sensors measure air quality inside buildings, homes, and enclosed spaces. Useful for indoor air quality assessments, HVAC monitoring, and workspace health studies. Get all indoor PurpleAir sensors

02

get_outdoor_sensors

These are sensors measuring ambient outdoor air quality. Returns current PM2.5, temperature, humidity and other measurements for each sensor. Useful for regional air quality monitoring, wildfire smoke tracking, and urban pollution studies. Get all outdoor (outside) PurpleAir sensors

03

get_pm25_sensors

5 (fine particulate matter) measurements. PM2.5 is the most important air quality indicator — particles smaller than 2.5 micrometers that can penetrate deep into lungs and bloodstream. Returns current PM2.5 concentrations along with location data. Essential for health advisories, wildfire smoke tracking, and urban pollution monitoring. Get sensors with PM2.5 measurements

04

get_sensor_data

Returns PM2.5, PM1.0, PM10.0 particle concentrations, temperature, humidity, pressure, VOC levels, and other measurements depending on the sensor model. Use the fields parameter to specify which measurements to return. Essential for monitoring air quality at a specific location. Get real-time data from a specific PurpleAir sensor

05

get_sensor_history

Returns time-series data for the requested fields (PM2.5, temperature, humidity, etc.) at regular intervals. Use start_timestamp and end_timestamp (Unix timestamps) to define the time range. The average parameter controls data aggregation (e.g. 60 for 1-minute averages, 3600 for hourly). Essential for analyzing air quality trends, identifying pollution events, and compliance reporting. Get historical air quality data from a PurpleAir sensor

06

get_sensor_history_csv

Same functionality as get_sensor_history but returns data as CSV instead of JSON. Use for offline analysis, charting, or compliance reporting. Requires start_timestamp and end_timestamp parameters. Get historical sensor data in CSV format for analysis

07

get_sensors_by_bounding_box

Provide the northwest (nwlat, nwlng) and southeast (selat, selng) corner coordinates. Perfect for mapping air quality across a city, neighborhood, or region. Returns all sensors in the area with current readings. Use with fields parameter to customize returned data. Get all sensors within a geographic bounding box

08

get_sensors_by_index

Provide comma-separated sensor indices in the show_only parameter. Useful when you already know the sensor indices from a previous query and want to get fresh readings without fetching all sensors. Get data for specific sensor(s) by their indices

09

get_sensors_near_me

Internally uses a bounding box around the point to find nearby sensors. Useful for identifying the closest PurpleAir monitor to any address or coordinate. Returns sensors sorted by proximity with current air quality readings. Find PurpleAir sensors near a specific location

10

list_sensors

Use the location_type parameter to filter by sensor type (outside=0, inside=1). Use the fields parameter to specify which data fields to return (e.g. name,latitude,longitude,pm2.5_atm,temperature,humidity). By default returns basic sensor info. Use show_only to filter by specific sensor indices (comma-separated). Use modified_since (Unix timestamp) to get only sensors updated after a specific time. Results include sensor metadata and real-time air quality measurements. List PurpleAir air quality sensors with optional filters

Example Prompts for PurpleAir in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with PurpleAir immediately.

01

"What's the air quality near San Francisco right now?"

02

"Show me the PM2.5 trend for sensor 12345 over the last 24 hours."

03

"Find all outdoor sensors in Los Angeles and show me their PM2.5 readings."

Troubleshooting PurpleAir MCP Server with Vercel AI SDK

Common issues when connecting PurpleAir to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

PurpleAir + Vercel AI SDK FAQ

Common questions about integrating PurpleAir MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

Connect PurpleAir to Vercel AI SDK

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