How to Use the Weatherbit MCP in AutoGen

Q: What kind of weather reports does AutoGen process?

AutoGen can analyze everything from hourly forecasts (getforecasthourly) to severe weather activity via getsevereweather. The agents discuss which report is most relevant for the current decision.

Run consensus decisions using Weatherbit and AutoGen agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Weatherbit MCP to AutoGen

Create your Vinkius account to connect Weatherbit to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Weatherbit with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Simulate decision-making with the MCP Server

Start by calling `get_current_weather` to get real-time temperature, humidity, and visibility. One agent might flag that the weather is too rough for an outdoor event. A second agent can then review this data point alongside historical trends gathered from `get_historical_weather` to propose a better alternative.

Evaluate air quality risks with AutoGen

Agents use the `get_air_quality` tool, which provides AQI scores and pollutant concentrations. A dedicated security agent can flag high NO2 or PM2.5 levels immediately. This forces deliberation: one agent might suggest postponing activity based on poor air quality metrics.

Check alerts before planning with MCP Server

The `get_weather_alerts` tool pulls active alerts, including severity and expiry times. You can set up agents to debate whether the risk level warrants canceling a plan. This consensus process makes sure decisions aren't based on incomplete or outdated alert data.

Setup guide

Set up Weatherbit MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Weatherbit tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Weatherbit_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Weatherbit data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

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

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Weatherbit_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Weatherbit data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Weatherbit. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Weatherbit now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Weatherbit MCP in AutoGen

Agents use the MCP Server to gather objective data. For example, they can call `get_forecast_daily` for temperature and precipitation probability. The agents then debate whether these metrics meet the required criteria.

AutoGen can analyze everything from hourly forecasts (`get_forecast_hourly`) to severe weather activity via `get_severe_weather`. The agents discuss which report is most relevant for the current decision.

Absolutely. You have access to real-time, historical (30 years), and predictive metrics—all of which allow agents to argue their case effectively.

The server handles diverse environmental metrics, including current temperature readings, UV index values, and air quality measurements (PM2.5, O3). This comprehensive set of data fuels agent debate.

While the MCP Server manages Weatherbit's data streams, you can build a system where different agents are responsible for querying different categories (e.g., one for air quality, one for wind).

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript