Open-Meteo Air Quality MCP Server for Vercel AI SDK 4 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Open-Meteo Air Quality 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 Open-Meteo Air Quality, 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 Open-Meteo Air Quality MCP Server
Give your AI the power to assess air safety with real-time pollutant data at 11km resolution.
The Vercel AI SDK gives every Open-Meteo Air Quality tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 4 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
- Pollutant Concentrations — PM2.5, PM10, O₃, NO₂, SO₂, CO, dust, and ammonia in μg/m³
- AQI Indexes — Both European (0-100+) and US (0-500) Air Quality Indexes with per-pollutant breakdowns
- Pollen Forecast — Birch, grass, alder, ragweed, olive, and mugwort pollen counts for allergy planning
- UV Index — Clear-sky and actual UV index for sun exposure safety
The Open-Meteo Air Quality MCP Server exposes 4 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 Open-Meteo Air Quality to Vercel AI SDK via MCP
Follow these steps to integrate the Open-Meteo Air Quality 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 4 tools from Open-Meteo Air Quality and passes them to the LLM
Why Use Vercel AI SDK with the Open-Meteo Air Quality MCP Server
Vercel AI SDK provides unique advantages when paired with Open-Meteo Air Quality 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 Open-Meteo Air Quality integration everywhere
Built-in streaming UI primitives let you display Open-Meteo Air Quality 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
Open-Meteo Air Quality + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Open-Meteo Air Quality MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Open-Meteo Air Quality in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Open-Meteo Air Quality tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Open-Meteo Air Quality capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Open-Meteo Air Quality through natural language queries
Open-Meteo Air Quality MCP Tools for Vercel AI SDK (4)
These 4 tools become available when you connect Open-Meteo Air Quality to Vercel AI SDK via MCP:
get_air_quality
5, PM10, ozone, nitrogen dioxide, sulphur dioxide, and carbon monoxide concentrations for any location. Get air quality pollutant concentrations
get_aqi_index
Get Air Quality Index (European and US standards)
get_pollen_forecast
Get pollen and allergen forecast
get_uv_index
Get UV index forecast
Example Prompts for Open-Meteo Air Quality in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Open-Meteo Air Quality immediately.
"Is the air quality in Beijing safe for outdoor exercise today?"
"What's the pollen forecast for Berlin this week?"
"What's the UV index in Sydney right now?"
Troubleshooting Open-Meteo Air Quality MCP Server with Vercel AI SDK
Common issues when connecting Open-Meteo Air Quality to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpOpen-Meteo Air Quality + Vercel AI SDK FAQ
Common questions about integrating Open-Meteo Air Quality 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 Open-Meteo Air Quality 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 Open-Meteo Air Quality to Vercel AI SDK
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.