# How to integrate Ambient weather MCP with Autogen ```json { "title": "How to integrate Ambient weather MCP with Autogen", "toolkit": "Ambient weather", "toolkit_slug": "ambient_weather", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/ambient_weather/framework/autogen", "markdown_url": "https://composio.dev/toolkits/ambient_weather/framework/autogen.md", "updated_at": "2026-05-12T10:01:05.605Z" } ``` ## Introduction This guide walks you through connecting Ambient weather to AutoGen using the Composio tool router. By the end, you'll have a working Ambient weather agent that can show latest readings from all your weather stations, list temperature and humidity from backyard sensor, get real-time weather data from main device through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Ambient weather account through Composio's Ambient weather MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Ambient weather with - [OpenAI Agents SDK](https://composio.dev/toolkits/ambient_weather/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ambient_weather/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ambient_weather/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ambient_weather/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ambient_weather/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ambient_weather/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ambient_weather/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ambient_weather/framework/cli) - [Google ADK](https://composio.dev/toolkits/ambient_weather/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ambient_weather/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ambient_weather/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ambient_weather/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ambient_weather/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ambient_weather/framework/crew-ai) ## 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 Ambient weather - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Ambient weather tools - Run a live chat loop where you ask the agent to perform Ambient weather 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 Ambient weather MCP server, and what's possible with it? The Ambient weather MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ambient Weather account. It provides structured and secure access to your weather station data, so your agent can perform actions like listing your stations, viewing live sensor readings, and retrieving device-level weather data on your behalf. - List all connected weather stations: Instantly retrieve an overview of every Ambient Weather device linked to your account. - Access real-time weather data: Ask your agent to fetch the latest readings from any of your stations, including temperature, humidity, and more. - Monitor device health and status: Let your agent check which stations are online, their last update time, and current operational status. - Summarize local weather conditions: Have your agent pull the most recent weather snapshot from selected stations for quick reporting or analysis. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `AMBIENT_WEATHER_GET_DEVICES` | Get Devices | Tool to retrieve a list of user's Ambient Weather devices with their most recent data. Use when you need to list your stations and view their latest readings. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Ambient weather MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Ambient weather. Instead of manually wiring Ambient weather APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Ambient weather account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 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 Install Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Ambient weather via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables 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 Ambient weather connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Ambient weather tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```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 Ambient weather session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ambient_weather"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen 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 ```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")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Ambient weather tools from the workbench ```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 Ambient weather assistant agent with MCP tools agent = AssistantAgent( name="ambient_weather_assistant", description="An AI assistant that helps with Ambient weather operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Ambient weather 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 ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Ambient weather 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") ``` ## Complete Code ```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 Ambient weather session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ambient_weather"] ) 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 Ambient weather assistant agent with MCP tools agent = AssistantAgent( name="ambient_weather_assistant", description="An AI assistant that helps with Ambient weather 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 Ambient weather 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 Ambient weather 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 Ambient weather, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Ambient weather MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/ambient_weather/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ambient_weather/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ambient_weather/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ambient_weather/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ambient_weather/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ambient_weather/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ambient_weather/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ambient_weather/framework/cli) - [Google ADK](https://composio.dev/toolkits/ambient_weather/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ambient_weather/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ambient_weather/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ambient_weather/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ambient_weather/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ambient_weather/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. - [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. 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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 Ambient weather MCP? With a standalone Ambient weather MCP server, the agents and LLMs can only access a fixed set of Ambient weather tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Ambient weather and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Autogen? 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 Ambient weather tools. ### Can I manage the permissions and scopes for Ambient weather while using Tool Router? Yes, absolutely. You can configure which Ambient weather 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 Ambient weather data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)