# How to integrate Iqair airvisual MCP with LangChain

```json
{
  "title": "How to integrate Iqair airvisual MCP with LangChain",
  "toolkit": "Iqair airvisual",
  "toolkit_slug": "iqair_airvisual",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/iqair_airvisual/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/iqair_airvisual/framework/langchain.md",
  "updated_at": "2026-05-12T10:16:23.019Z"
}
```

## Introduction

This guide walks you through connecting Iqair airvisual to LangChain using the Composio tool router. By the end, you'll have a working Iqair airvisual agent that can show today's air quality in los angeles, list cities in maharashtra, india with data, get historical aqi for paris last week through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Iqair airvisual account through Composio's Iqair airvisual MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Iqair airvisual with

- [OpenAI Agents SDK](https://composio.dev/toolkits/iqair_airvisual/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/iqair_airvisual/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/iqair_airvisual/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/iqair_airvisual/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/iqair_airvisual/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/iqair_airvisual/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/iqair_airvisual/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/iqair_airvisual/framework/cli)
- [Google ADK](https://composio.dev/toolkits/iqair_airvisual/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/iqair_airvisual/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/iqair_airvisual/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/iqair_airvisual/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/iqair_airvisual/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Iqair airvisual project to Composio
- Create a Tool Router MCP session for Iqair airvisual
- Initialize an MCP client and retrieve Iqair airvisual tools
- Build a LangChain agent that can interact with Iqair airvisual
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## What is the Iqair airvisual MCP server, and what's possible with it?

The Iqair airvisual MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Iqair airvisual account. It provides structured and secure access to rich global air quality data, so your agent can perform actions like retrieving real-time AQI, forecasting pollution, checking historical trends, and ranking cities worldwide by air quality on your behalf.
- Real-time city and station air quality: Instantly fetch current air quality and weather data for any supported city or monitoring station, based on precise location or station ID.
- Air quality forecasting: Ask your agent to provide air quality forecasts for specific cities, helping you plan activities based on pollution trends.
- Historical AQI analysis: Retrieve historical air quality index readings for cities to analyze patterns, spot trends, or track improvements over time.
- World AQI rankings: Get live rankings of cities worldwide based on current AQI data, or easily find the most and least polluted cities globally.
- Location-based discovery: Let your agent list supported countries, states, and cities, or pinpoint the nearest air quality stations and cities using GPS coordinates or IP address.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `IQAIR_AIRVISUAL_GET_AIR_QUALITY_FORECAST_DATA` | Get Air Quality Forecast Data | Tool to retrieve air quality forecast data for a specified city, state, and country. Use after confirming location details. |
| `IQAIR_AIRVISUAL_GET_CITIES` | Get Cities | Tool to list supported cities in a specified state and country. Use when you need to retrieve cities for a given state/country. |
| `IQAIR_AIRVISUAL_GET_CITY_AIR_QUALITY` | Get City Air Quality | Tool to retrieve air quality data for a specific city. Use when you need current pollution and weather data by specifying city, state, and country. |
| `IQAIR_AIRVISUAL_GET_COUNTRIES` | Get supported countries | Tool to list all supported countries. Use when you need to know which countries are supported by the AirVisual API. |
| `IQAIR_AIRVISUAL_GET_HISTORICAL_AQI_DATA` | Get Historical AQI Data | Tool to retrieve historical air quality data for a city. Use after confirming city, state, and country when you need AQI readings over time. |
| `IQAIR_AIRVISUAL_GET_NEAREST_CITY_AIR_QUALITY` | Get Nearest City Air Quality | Tool to retrieve air quality data for the nearest city based on latitude/longitude or IP. Use when you have precise location data or want to geolocate an IP for air quality. |
| `IQAIR_AIRVISUAL_GET_NEAREST_STATION_AIR_QUALITY` | Get Nearest Station Air Quality | Tool to get nearest station air quality. Use when you have GPS coordinates and need closest station’s AQI. |
| `IQAIR_AIRVISUAL_GET_STATES` | Get States | Tool to list supported states in a specified country. Use when you need to retrieve states/provinces for a given country. |
| `IQAIR_AIRVISUAL_GET_STATION_BY_ID` | Get Station by ID | Fetches current air quality and weather data for a specific location by station/city/state/country names. Falls back to city-level data if the Stations API requires premium access. Returns current AQI (US and China scales), weather conditions, and geographic location. Use Get Countries, Get States, and Get Cities actions to find valid location names. |
| `IQAIR_AIRVISUAL_GET_WORLD_RANKING` | Get World AQI Rankings | Retrieves air quality ranking data. With premium API access, returns a global ranking of cities by AQI. With standard (free) API access, automatically falls back to returning the nearest city's air quality as a single-item ranking list. Use lat/lon coordinates or an IP address to specify location for the fallback behavior. Returns city name, location, and current AQI values (US EPA and Chinese MEP standards). |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Iqair airvisual MCP server is an implementation of the Model Context Protocol that connects your AI agent to Iqair airvisual. It provides structured and secure access so your agent can perform Iqair airvisual operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Iqair airvisual tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Iqair airvisual tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Iqair airvisual tools as needed
```python
# Create Tool Router session for Iqair airvisual
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['iqair_airvisual']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['iqair_airvisual']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "iqair_airvisual-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "iqair_airvisual-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Iqair airvisual related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Iqair airvisual related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['iqair_airvisual']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "iqair_airvisual-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Iqair airvisual related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['iqair_airvisual']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "iqair_airvisual-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Iqair airvisual related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Iqair airvisual through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## How to build Iqair airvisual MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/iqair_airvisual/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/iqair_airvisual/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/iqair_airvisual/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/iqair_airvisual/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/iqair_airvisual/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/iqair_airvisual/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/iqair_airvisual/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/iqair_airvisual/framework/cli)
- [Google ADK](https://composio.dev/toolkits/iqair_airvisual/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/iqair_airvisual/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/iqair_airvisual/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/iqair_airvisual/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/iqair_airvisual/framework/crew-ai)

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Iqair airvisual MCP?

With a standalone Iqair airvisual MCP server, the agents and LLMs can only access a fixed set of Iqair airvisual tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Iqair airvisual and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Iqair airvisual tools.

### Can I manage the permissions and scopes for Iqair airvisual while using Tool Router?

Yes, absolutely. You can configure which Iqair airvisual scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Iqair airvisual data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)