How to Use the Meteostat MCP in CrewAI

Q: How do I connect the Meteostat MCP Server to my CrewAI agents?

Pass your Vinkius HTTP URL directly into the agent's mcps list during initialization. CrewAI automatically discovers tools like pointdaily and makes them available to that specific agent.

Q: Can I limit which Meteostat tools a CrewAI agent can use?

Yes. Use the MCPServerHTTP class from crewai.mcp and apply a toolfilter. This lets you restrict a research agent to stationsnearby while blocking access to heavier historical tools.

Equip your CrewAI agent teams with historical weather data to automate climate analysis and regional logistics planning.

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Connect Meteostat MCP to CrewAI

Create your Vinkius account to connect Meteostat 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 Meteostat with CrewAI

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Coordinate Multi-Agent Weather Analysis

The `point_hourly` tool fetches historical hourly weather data for any coordinate on the globe. This tool provides your agents with exact temperature, wind, and precipitation records for precise timeframes. Inside CrewAI, a research agent can use this tool to gather raw data while an analyst agent processes the numbers. The framework coordinates this exchange, passing the hourly metrics between agents using shared memory.

Search Regional Stations via CrewAI MCP Server

The `stations_nearby` tool identifies physical weather stations located close to your target coordinates. It gives your agent team the exact station IDs needed to pull verified sensor data. Your coordinator agent uses this tool first, then delegates the resulting station IDs to specialist agents. Those specialists then call `stations_meta` to verify the station's active status and reporting history.

Track Long-Term Trends with Climate Normals

The `point_normals` tool retrieves historical climate averages for a specific geographic point over several decades. This tool allows your crew to establish baseline environmental conditions for any location. Your agents combine these normals with `point_monthly` data to detect long-term anomalies. The entire process runs autonomously, letting your crew write and save detailed climate reports without manual intervention.

Setup guide

Set up Meteostat 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 Meteostat tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Meteostat 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 →

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="Meteostat Analyst",
        goal="Access and analyze Meteostat data via MCP.",
        backstory="Expert analyst with direct Meteostat access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Meteostat 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 →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Meteostat. 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 Meteostat MCP in CrewAI

Pass your Vinkius HTTP URL directly into the agent's `mcps` list during initialization. CrewAI automatically discovers tools like `point_daily` and makes them available to that specific agent.

Yes. Use the `MCPServerHTTP` class from `crewai.mcp` and apply a `tool_filter`. This lets you restrict a research agent to `stations_nearby` while blocking access to heavier historical tools.

CrewAI uses shared memory to pass tool outputs between agents. Once your research agent fetches climate data using `point_monthly`, that data is immediately available to your writer agent for drafting reports.

Yes. You can appoint a manager agent to oversee the crew. The manager decides when to call `stations_daily` and which specialist agent should analyze the resulting historical weather records.

All latitude, longitude, and station ID inputs are processed in transit to fetch Meteostat records. Vinkius runs the server in an ephemeral sandbox, meaning your query coordinates are never stored or logged permanently.

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