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How to integrate Ambee MCP with Autogen

Connect Autogen to Ambee MCP. Show today's air quality for paris, get wildfire risk forecast for california, and more using natural language, with authentication handled for you.

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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.

27 Tools

Introduction

This guide walks you through connecting Ambee to AutoGen using the Composio tool router. By the end, you'll have a working Ambee agent that can check air quality and pollen levels, fetch weather forecasts, track wildfires and natural disasters, and geocode places through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Ambee account through Composio's Ambee MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Ambee with

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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 Ambee
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Ambee tools
  • Run a live chat loop where you ask the agent to perform Ambee 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 Ambee MCP server, and what's possible with it?

The Ambee MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ambee account. It provides structured and secure access to environmental data, so your agent can check air quality history, monitor current weather, review pollen conditions, assess fire risk, and track natural disasters on your behalf.

  • Air quality history: Have your agent retrieve historical air quality data for any location using its latitude and longitude.
  • Weather conditions and forecasts: Let the agent check current temperature, pressure, humidity, and wind conditions, or retrieve forecasts for up to 72 hours by coordinates.
  • Pollen monitoring: Direct your agent to find current pollen conditions by place or coordinates and retrieve 48-hour pollen forecasts by place name.
  • Natural disaster tracking: Instruct your agent to retrieve recent or historical earthquake, flood, drought, and volcanic eruption data by country or coordinates.
  • Fire risk and location details: Have your agent assess forecast fire risk and Fire Weather Index conditions, or turn coordinates into a readable address, place name, and postal code.

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 Ambee 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 Ambee 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 Ambee 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 Ambee session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["ambee"]
    )
    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 Ambee 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 Ambee assistant agent with MCP tools
    agent = AssistantAgent(
        name="ambee_assistant",
        description="An AI assistant that helps with Ambee 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 Ambee 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 Ambee 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 Ambee 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 Ambee 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 Ambee session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["ambee"]
    )
    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 Ambee assistant agent with MCP tools
        agent = AssistantAgent(
            name="ambee_assistant",
            description="An AI assistant that helps with Ambee 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 Ambee 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 Ambee 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 Ambee, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Geocode by Place

Tool to transform a place name or address into geographic coordinates.

Get Air Quality by City

Tool to retrieve real-time air quality data for a specific city.

Get Air Quality by Country Code

Retrieve real-time air quality readings from monitoring stations in a country using a 3-letter ISO country code.

Get Air Quality by Latitude and Longitude

Tool to retrieve real-time air quality data for a specific latitude and longitude.

Get Air Quality by Postal Code

Retrieve real-time air quality data for a specific postal code and country.

Get Air Quality Forecast by Latitude and Longitude

Tool to retrieve air quality forecast for a specific latitude and longitude.

Get Air Quality History by Latitude and Longitude

Tool to retrieve historical air quality data for a specific latitude and longitude.

Retrieve latest natural disasters by continent

Tool to retrieve latest natural disaster data for a specific continent.

Get historical natural disasters by date range

Retrieve global historical natural disaster events from a specified starting date, optionally filtering by event type and paginating results.

Get historical natural disasters by country code

Tool to retrieve historical natural disaster data for a country by ISO country code.

Get historical natural disasters by coordinates

Tool to retrieve historical natural disaster data for a specific location by coordinates with date range.

Get latest disasters by country code

Tool to retrieve latest natural disaster data for a specific country using ISO country code.

Get latest natural disasters by coordinates

Tool to retrieve latest natural disaster data (earthquakes, floods, droughts, volcanic eruptions) for a specific location using geographic coordinates.

Get Elevation by Latitude and Longitude

Tool to retrieve elevation statistics (min, max, mean) for a specific latitude and longitude.

Get Elevation by Place

Retrieve elevation statistics (minimum, maximum, and mean) for a location by place name.

Get Fire Risk by Latitude and Longitude

Retrieve weekly fire risk forecasts and Fire Weather Index data for geographic coordinates in North America, covering the next four weeks.

Get ILI Forecast by Latitude and Longitude

Retrieve an influenza-like illness (ILI) risk forecast for latitude and longitude, optionally including pollen and weather details.

Get Pollen Forecast by Place

Tool to retrieve 48-hour pollen forecast for a specific location by place name.

Get Pollen History by Place

Tool to retrieve historical pollen data for a specific place name.

Get Latest Pollen Data by Latitude and Longitude

Tool to retrieve latest pollen data for a specific geographic location using latitude and longitude coordinates.

Get Latest Pollen by Place

Tool to retrieve latest pollen data for a specific place by name.

Get Weather Forecast by Latitude and Longitude

Tool to retrieve weather forecast for a specific latitude and longitude (up to 72 hours).

Get Current Weather by Latitude and Longitude

Tool to retrieve current weather data for a specific latitude and longitude, including temperature, pressure, humidity, and wind conditions.

Get Wildfire Data by Latitude and Longitude

Retrieves real-time wildfire data for a specific geographic location using latitude and longitude coordinates.

Get Wildfire Data by Place

Retrieve recent wildfire data by place name, optionally filtering for satellite-detected or officially reported fires.

Get Wildfire Risk Forecast by Place

Retrieve weekly wildfire risk forecasts for a place in North America over the next four weeks.

Reverse Geocode by Latitude and Longitude

Tool to convert geographic coordinates into human-readable location data (address, place name, postal code).

FRAMEWORKS

How to build Ambee MCP Agent with another framework

Claude Code logo

Claude Code

Use Ambee MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Ambee MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Ambee MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Ambee MCP with Claude Agent SDK

Codex logo

Codex

Use Ambee MCP with Codex

OpenClaw logo

OpenClaw

Use Ambee MCP with OpenClaw

Hermes logo

Hermes

Use Ambee MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Ambee MCP with Atomic Agent

Google ADK logo

Google ADK

Use Ambee MCP with Google ADK

LangChain logo

LangChain

Use Ambee MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Ambee MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Ambee MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Ambee MCP with LlamaIndex

CrewAI logo

CrewAI

Use Ambee MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Ambee MCP with Pydantic AI

FAQ

Frequently asked questions

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