# How to integrate Iqair airvisual MCP with CrewAI

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

## Introduction

This guide walks you through connecting Iqair airvisual to CrewAI 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 CrewAI 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)
- [LangChain](https://composio.dev/toolkits/iqair_airvisual/framework/langchain)
- [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)

## TL;DR

Here's what you'll learn:
- Get a Composio API key and configure your Iqair airvisual connection
- Set up CrewAI with an MCP enabled agent
- Create a Tool Router session or standalone MCP server for Iqair airvisual
- Build a conversational loop where your agent can execute Iqair airvisual operations

## What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.
Key features include:
- Agent Roles: Define specialized agents with specific goals and backstories
- Task Management: Create tasks with clear descriptions and expected outputs
- Crew Orchestration: Combine agents and tasks into collaborative workflows
- MCP Integration: Connect to external tools through Model Context Protocol

## 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

Before starting, make sure you have:
- Python 3.9 or higher
- A Composio account and API key
- A Iqair airvisual connection authorized in Composio
- An OpenAI API key for the CrewAI LLM
- Basic familiarity with Python

### 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

**What's happening:**
- composio connects your agent to Iqair airvisual via MCP
- crewai provides Agent, Task, Crew, and LLM primitives
- crewai-tools[mcp] includes MCP helpers
- python-dotenv loads environment variables from .env
```bash
pip install composio crewai crewai-tools[mcp] python-dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates with Composio
- USER_ID scopes the session to your account
- OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**What's happening:**
- CrewAI classes define agents and tasks, and run the workflow
- MCPServerHTTP connects the agent to an MCP endpoint
- Composio will give you a short lived Iqair airvisual MCP URL
```python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

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

### 5. Create a Composio Tool Router session for Iqair airvisual

**What's happening:**
- You create a Iqair airvisual only session through Composio
- Composio returns an MCP HTTP URL that exposes Iqair airvisual tools
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["iqair_airvisual"])

url = session.mcp.url
```

### 6. Initialize the MCP Server

**What's Happening:**
- Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
- MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
- Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
- Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
- Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
```python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**What's Happening:**
- Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
- Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
- Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
- Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
- Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
- Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.
```python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
```

## Complete Code

```python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["iqair_airvisual"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")
```

## Conclusion

You now have a CrewAI agent connected to Iqair airvisual through Composio's Tool Router. The agent can perform Iqair airvisual operations through natural language commands.
Next steps:
- Add role-specific instructions to customize agent behavior
- Plug in more toolkits for multi-app workflows
- Chain tasks for complex multi-step operations

## 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)
- [LangChain](https://composio.dev/toolkits/iqair_airvisual/framework/langchain)
- [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)

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- [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.
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## 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 CrewAI?

Yes, you can. CrewAI 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.

---
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