How to Use the INMET (Apitempo - Meteorologia) MCP in AutoGen

Let your AutoGen agents debate and analyze Brazilian weather data using the INMET MCP Server.

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Connect INMET (Apitempo - Meteorologia) MCP to AutoGen

Create your Vinkius account to connect INMET (Apitempo - Meteorologia) 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.

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Setup INMET (Apitempo - Meteorologia) with AutoGen

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Run multi-agent debates on weather forecasts

The `get_all_forecasts` tool delivers regional forecasts to your coordinator agent, which then shares the data with specialized worker agents. A logistics agent and an agricultural agent can debate the impact of the forecast on shipping schedules. This consensus-driven approach ensures that decisions are not based on raw numbers alone. The agents challenge each other's interpretations of the incoming weather data before outputs are finalized.

Resolve regional climate discrepancies

The `get_meteorological_data_by_region` tool scans entire regions for sensor data. If one station reports extreme heat while neighbors are cool, a verification agent calls `get_station_data_hourly` to check the specific station's health. The debate loop continues until the agents agree on whether the reading is a genuine microclimate event or a broken sensor. This prevents automated systems from triggering false alarms based on bad station telemetry.

Analyze satellite imagery using AutoGen

The `get_satellite_images` tool provides real-time GOES-16 visual feeds that your agents analyze. An image-parser agent extracts cloud patterns while a data-analyst agent compares them against `get_station_data_daily` reports. They combine their findings to build a detailed regional report. This collaborative analysis reduces errors by cross-referencing visual telemetry with ground-level station readings.

Setup guide

Set up INMET (Apitempo - Meteorologia) 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 INMET (Apitempo - Meteorologia) 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="INMET (Apitempo - Meteorologia)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="INMET (Apitempo - Meteorologia)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent INMET (Apitempo - Meteorologia) 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 INMET. 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.

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Common questions about INMET (Apitempo - Meteorologia) MCP in AutoGen

Use the MCP tool adapter to configure the server. Pass the resulting tool list to your `AssistantAgent` constructor using `mcp_server_tools` from `autogen-ext[mcp]`.

Yes, the server handles concurrent requests. Your agents can query different station IDs simultaneously to speed up regional weather debates.

The tools are exposed as standard Python functions that agents can invoke during their turns. An agent can call `get_forecast_by_city` to answer another agent's question during a discussion.

It uses the Streamable HTTP transport. This ensures stable connections and fast response times during complex multi-agent conversations.

Yes, all data transfers of station IDs and regional parameters run through an encrypted zero-trust gateway. No telemetry is stored on the Vinkius platform, keeping your operational queries private.

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