AirVisual MCP for AI. Get Real-Time AQI and Weather Data Globally

Q: Can I list all available locations with listcountries?

Yes, running listcountries provides the full scope of nations supported. You can then follow up by using liststates to see the sub-regions within that country.

Q: Is getcitydata better than getting station data?

It depends on your need. Use getcitydata for a quick, general read of an entire urban area. Use getstationdata when you need the exact metrics from one physical monitoring equipment.

Q: What if I don't know the state abbreviation?

Run listcountries first to narrow down the nation, and then use liststates. This gives you a clear list of supported states for that country.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

AirVisual monitors global air quality and weather conditions instantly. It gives your agent real-time data on AQI, pollution levels, and meteorology for any location worldwide.

You can check current readings for a specific city, find the nearest station using coordinates or IP address, or map out supported locations by country/state.

What your AI can do

List cities

Lists all supported cities within a specified state or region.

Get city data

Retrieves real-time AQI and weather data for a specific city you name.

List countries

Returns a list of every country the service monitors for air quality data.

+ 4 more capabilities included

Get City Readings

Retrieve current air quality index and weather metrics for any specified city.

Find Location by Coordinates

Pull data for the closest monitoring site using precise GPS latitude/longitude inputs.

Find Location by IP Address

Determine and retrieve environmental metrics based on your current network IP address.

Check Specific Stations

Access granular, detailed data from an individual monitoring station location.

List Supported Locations

Browse the hierarchy to list all supported countries, states, or cities for future queries.

Ask an AI about this

Included with Plan

Waiting for input…

AI Agent

AirVisual with 7 Tools

These tools let your agent perform specific lookups: listing supported regions, finding the nearest city via IP or coordinates, or pulling granular data from individual monitoring stations.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using AirVisual on Vinkius

List Cities

Lists all supported cities within a specified state or region.

Get City Data

Retrieves real-time AQI and weather data for a specific city you name.

List Countries

Returns a list of every country the service monitors for air quality data.

Get Nearest City By Coords

Gets the air quality and weather metrics for the closest city using GPS coordinates.

Get Nearest City By Ip

Finds and retrieves data for the nearest monitored city based on your IP address.

List States

Provides a list of supported states within a specific country.

Get Station Data

Pulls granular environmental readings directly from a specific, named monitoring station.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The AirVisual integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "airvisual": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the AirVisual tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"airvisual": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with AirVisual, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AirVisual. 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.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 7 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Getting Global Environmental Data Used To Be a Pain.

Before this MCP, getting current air quality data meant opening multiple tabs: one for the national weather service, another for a local pollution index (AQI), and maybe a third to check historical records. You'd have to copy-paste city names or coordinates repeatedly across these different services just to build a single picture of environmental health.

Now you ask your agent once. It handles the geo-lookup—whether by IP or GPS—and pulls all current data points together. You get everything in one structured response, ready for your script or report.

Accessing Air Quality Data with `get_station_data`

The old way forced you to rely on city-level averages, which are useless if the pollution source is only one block away. You had to physically drive to a monitoring office or use an outdated map service just to find the ID for a granular data pull.

Now, `get_station_data` lets your agent read specific environmental metrics from individual stations. It's hyper-local detail that changes what you can do with the information.

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What your AI can actually do with this

Need to know what's really going on with the air? This MCP connects environmental monitoring data—AQI and weather—directly into your workflow. Instead of opening three different websites for pollution, climate forecasts, and local maps, you ask your agent once. It handles all that heavy lifting. You can drill down from a global overview to hyper-local readings from specific monitoring stations.

The Vinkius catalog makes this connection simple; just subscribe and grant access. Your agent uses these tools to pull current AQI for major cities or pinpoint the exact environmental data nearest your IP address, letting you plan outdoor activities or run research without leaving your client app.

Built · Hosted · Managed by Vinkius AirVisual MCP - Monitor Air Quality & Weather Data

Server ID 019e5cf9-15d4-7027-82e8-99c3ab9b1a16

Vinkius Inspector

Compliance Grade F

Score 11.43/100

Report View Report ↗

What Changes When You Connect

You stop guessing about air quality. Instead of checking multiple websites, using get_city_data provides immediate, single-source metrics for any city.

Need data right now? Use get_nearest_city_by_ip. You just need to ask your agent what's nearby, and it uses your IP address to pull the air quality report.

Drill down past general readings. If you know a specific monitoring spot matters, use get_station_data for hyper-local insights.

Building a script? First, run list_countries, then list_states, and finally list_cities to validate the full scope of supported locations before querying data.

The system automatically handles location resolution. If you give it coordinates, use get_nearest_city_by_coords instead of trying to guess the city name.

See it in action

01 01

Planning a Field Site Inspection

An environmental consultant needs to assess air quality risk for an industrial park. The agent first uses list_states and list_cities to confirm the region, then uses get_nearest_city_by_coords with the site's GPS markers to generate a full pollution report.

02 02

Emergency Response Team Dispatch

A dispatcher needs immediate local data. They simply ask 'What is the air quality here?' The agent uses get_nearest_city_by_ip and returns the current AQI, temperature, and wind speed instantly.

03 03

Developing a Global Health Alert System

A developer needs to build alerts for multiple regions. They use list_countries to iterate through all available markets, then call get_city_data sequentially to check AQI in major urban centers.

04 04

IoT Air Quality Triggering

A smart building manager wants the HVAC system to adjust when pollution hits a high mark. The agent monitors the specific station data using get_station_data and triggers the automation if AQI exceeds 100.

The honest tradeoffs

Using only country names

Anti-pattern

Asking your agent, 'Give me pollution data for India.' This is too broad. The agent can't guess the city or state you mean.

The Fix

You must narrow it down. First, use list_states to get the states in India. Then, provide a specific city name and run get_city_data. If you prefer coordinates, use get_nearest_city_by_coords.

Assuming IP data is enough

Anti-pattern

Relying only on get_nearest_city_by_ip when the site moves. The IP might resolve to a cell tower, not the actual location.

The Fix

If you need high precision, always use GPS coordinates with get_nearest_city_by_coords. This bypasses network limitations and targets the physical spot.

Asking for all data at once

Anti-pattern

A single prompt asking to 'List countries, check nearest IP city, and get station data.' The agent will fail or only run one tool.

The Fix

Break it into steps. First, use list_countries to verify the region scope. Then, execute a targeted query like get_nearest_city_by_ip.

When It Fits, When It Doesn't

Use this MCP if your primary need is real-time, location-specific environmental metrics (AQI and weather). Use it when you require the data to be pulled into an automated workflow or client application. Don't use this if you just want a general overview; checking Google Maps for 'weather in Tokyo' works fine then. You only need AirVisual if your process requires structured, programmatic access: check specific cities with get_city_data when you know the name; use get_nearest_city_by_coords or get_nearest_city_by_ip when location is dynamic or unknown; and use listing tools (list_countries, etc.) only to map out possible parameters before running a query.

Questions you might have

How does get_nearest_city_by_ip work? +

It determines the nearest monitored city using your current IP address. It's fast, but remember this only gives a general area reading; for precision, use get_nearest_city_by_coords.

Can I list all available locations with list_countries? +

Yes, running list_countries provides the full scope of nations supported. You can then follow up by using list_states to see the sub-regions within that country.

Is get_city_data better than getting station data? +

It depends on your need. Use get_city_data for a quick, general read of an entire urban area. Use get_station_data when you need the exact metrics from one physical monitoring equipment.

What if I don't know the state abbreviation? +

Run list_countries first to narrow down the nation, and then use list_states. This gives you a clear list of supported states for that country.

What happens if I use an incorrect API key when calling get_city_data? +

The call fails with a 401 Unauthorized error. Always confirm your AirVisual API Key is active and properly entered into the Vinkius setup. You can verify credentials through the dedicated support portal.

How frequently does get_station_data update its readings? +

The data freshness depends on the physical sensor at that station. While AirVisual provides real-time indexing, the actual reporting interval varies by location and pollutant type. Always check the reported timestamp for accuracy.

If I use get_nearest_city_by_coords with coordinates outside a monitored area, what error do I receive? +

You will likely receive a 'No Data Available' or similar geographic boundary error. Make sure your GPS coordinates fall within the service coverage map provided by AirVisual to guarantee results.

Are there rate limits when using list_cities repeatedly for many states? +

Yes, repeated bulk calls can trigger temporary rate limiting. Implement exponential backoff or use batch processing methods in your agent's code to avoid hitting API caps and ensure consistent performance.

Can I get air quality data for my current location without entering coordinates? +

Yes! You can use the get_nearest_city_by_ip tool. The agent will use your requester IP address to find and return the AQI and weather data for the closest supported city automatically.

How do I find out which cities are supported in a specific region? +

You can browse the hierarchy using list_countries, then list_states for a specific country, and finally list_cities for a specific state. This allows you to discover exactly which locations have active monitoring.

Does this server provide data from specific monitoring stations? +

Yes, the get_station_data tool allows you to retrieve real-time data from a specific named monitoring station if you know its name and location details (city, state, country).

Connect to your AI in seconds.

List cities

Get city data

List countries

AirVisual with 7 Tools

Make your AI actually useful.

List Cities

Get City Data

List Countries

Get Nearest City By Coords

Get Nearest City By Ip

List States

Get Station Data

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

Getting Global Environmental Data Used To Be a Pain.

Accessing Air Quality Data with `get_station_data`

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

Planning a Field Site Inspection

Emergency Response Team Dispatch

Developing a Global Health Alert System

IoT Air Quality Triggering

The honest tradeoffs

Using only country names

Assuming IP data is enough

Asking for all data at once

When It Fits, When It Doesn't

Questions you might have