How to integrate Iqair airvisual MCP with Autogen

This guide walks you through connecting Iqair airvisual to AutoGen 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 AutoGen 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.

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Api Key

Iqair airvisual is an API service providing real-time and historical global air quality data. It helps users monitor pollution levels for healthier decision-making.

10 Tools

Introduction

This guide walks you through connecting Iqair airvisual to AutoGen 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 AutoGen 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 SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Iqair airvisual
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Iqair airvisual tools
  • Run a live chat loop where you ask the agent to perform Iqair airvisual operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Iqair airvisual account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Iqair airvisual via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Iqair airvisual connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Iqair airvisual session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["iqair_airvisual"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Iqair airvisual tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Iqair airvisual assistant agent with MCP tools
    agent = AssistantAgent(
        name="iqair_airvisual_assistant",
        description="An AI assistant that helps with Iqair airvisual operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Iqair airvisual tools from the workbench
8

Run the interactive chat loop

python
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")

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Iqair airvisual tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Iqair airvisual and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Iqair airvisual session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["iqair_airvisual"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Iqair airvisual assistant agent with MCP tools
        agent = AssistantAgent(
            name="iqair_airvisual_assistant",
            description="An AI assistant that helps with Iqair airvisual operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        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")

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Iqair airvisual through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Iqair airvisual, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Iqair airvisual action and event your agent gets out of the box.

Get Air Quality Forecast Data

Tool to retrieve air quality forecast data for a specified city, state, and country.

Get Cities

Tool to list supported cities in a specified state and country.

Get City Air Quality

Tool to retrieve air quality data for a specific city.

Get supported countries

Tool to list all supported countries.

Get Historical AQI Data

Tool to retrieve historical air quality data for a city.

Get Nearest City Air Quality

Tool to retrieve air quality data for the nearest city based on latitude/longitude or IP.

Get Nearest Station Air Quality

Tool to get nearest station air quality.

Get States

Tool to list supported states in a specified country.

Get Station by ID

Fetches current air quality and weather data for a specific location by station/city/state/country names.

Get World AQI Rankings

Retrieves air quality ranking data.

FRAMEWORKS

How to build Iqair airvisual MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Iqair airvisual MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Iqair airvisual MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Iqair airvisual MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Iqair airvisual MCP with Claude Cowork

Codex logo

Codex

Use Iqair airvisual MCP with Codex

OpenClaw logo

OpenClaw

Use Iqair airvisual MCP with OpenClaw

Hermes logo

Hermes

Use Iqair airvisual MCP with Hermes

CLI logo

CLI

Use Iqair airvisual MCP with CLI

Google ADK logo

Google ADK

Use Iqair airvisual MCP with Google ADK

LangChain logo

LangChain

Use Iqair airvisual MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Iqair airvisual MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Iqair airvisual MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Iqair airvisual MCP with LlamaIndex

CrewAI logo

CrewAI

Use Iqair airvisual MCP with CrewAI

FAQ

Frequently asked questions

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.

Yes, you can. Autogen 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.

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.

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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