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

Q: Can CrewAI agents share INMET (Apitempo - Meteorologia) data?

They can. Using shared memory, an agent that calls getstationdatahourly can provide that information to the entire crew for collaborative analysis.

Deploy specialized agent crews using CrewAI to analyze Brazilian weather patterns with official INMET data.

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Connect INMET (Apitempo - Meteorologia) MCP to CrewAI

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

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Role-based weather research in CrewAI

Assign a researcher agent to use `get_station_data_daily` while a separate analyst agent interprets the results. This division of labor keeps your crew efficient. Each agent focuses on its specific task. This prevents the model from getting overwhelmed by too much raw data at once.

Autonomous weather tracking in CrewAI

Configure a crew to monitor `get_satellite_images` continuously. If the agent detects specific cloud formations, it can escalate to another agent for further action. This creates a closed-loop system for weather observation. It runs continuously until your stop condition is met.

Shared memory for CrewAI weather crews

Use the shared memory feature to let agents pass context from `get_all_forecasts` to other crew members. Agents build a running understanding of the climate. This makes your crew smarter over time. They don't need to re-query the same data if another agent has already fetched it.

Setup guide

Set up INMET (Apitempo - Meteorologia) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke INMET (Apitempo - Meteorologia) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="INMET (Apitempo - Meteorologia) Analyst",
    goal="Access and analyze INMET (Apitempo - Meteorologia) data via MCP.",
    backstory="Expert analyst with direct INMET (Apitempo - Meteorologia) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent INMET (Apitempo - Meteorologia) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="INMET (Apitempo - Meteorologia) Analyst",
        goal="Access and analyze INMET (Apitempo - Meteorologia) data via MCP.",
        backstory="Expert analyst with direct INMET (Apitempo - Meteorologia) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent INMET (Apitempo - Meteorologia) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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

Add the server URL to your agent's MCP configuration. This allows the crew to select the right tools for weather-related tasks automatically.

They can. Using shared memory, an agent that calls `get_station_data_hourly` can provide that information to the entire crew for collaborative analysis.

It is. The server provides structured access to all major meteorological endpoints, allowing your crew to handle regional and national data effectively.

It offers official Brazilian meteorological records, including hourly station readings, daily summaries, and GOES-16 satellite imagery.

The server operates on an ephemeral basis, meaning it doesn't store your query history. It only processes the specific weather requests you send.

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