How to Use the MeteoSource MCP in CrewAI

Q: Is it possible to filter which MeteoSource tools my CrewAI agents can access?

Use the toolfilter option in your server setup. You can restrict agents to only use specific tools like getpointforecast, preventing them from making unnecessary changes.

Coordinate autonomous weather monitoring teams using CrewAI and the MeteoSource MCP Server.

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Connect MeteoSource MCP to CrewAI

Create your Vinkius account to connect MeteoSource 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 MeteoSource with CrewAI

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Autonomous Monitoring with CrewAI

Deploy a specialized crew where one agent watches for weather alerts and another takes action. Use `get_point_forecast` to provide the data the crew needs to make decisions. Your agents can collaborate to compare current conditions against thresholds. If a storm is coming, the crew acts immediately based on the data they pull.

Coordinate Management via Tooling

Use `get_nearest_weather_place` to resolve coordinates for your fleet of agents. This allows the crew to track weather across multiple global locations simultaneously. Each agent uses the tool to ensure they are looking at the correct local data. This keeps the entire crew synchronized on the same set of facts.

Operational Readiness Checks

Before the crew starts their shift, have an agent run `check_api_status`. This ensures the service is reachable so the crew doesn't run into errors mid-mission. If the service returns a warning, the crew can switch to a standby mode. This keeps your autonomous operations running smoothly without manual resets.

Setup guide

Set up MeteoSource 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 MeteoSource tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent MeteoSource 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="MeteoSource Analyst",
        goal="Access and analyze MeteoSource data via MCP.",
        backstory="Expert analyst with direct MeteoSource access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent MeteoSource 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 MeteoSource. 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 MeteoSource MCP in CrewAI

Include the server URL in your agent's mcps list. The framework will automatically register the available tools and make them available for your agents to use.

Yes, use the shared memory feature in your crew setup. When one agent fetches forecast data, the others can access that context to inform their next steps.

Use the tool_filter option in your server setup. You can restrict agents to only use specific tools like `get_point_forecast`, preventing them from making unnecessary changes.

Implement a delay or a sequential execution pattern in your crew. This spaces out the tool calls and keeps your usage well within the server's operational limits.

The server operates in a sandbox environment that restricts access to only the data requested by your tools. Your location queries are ephemeral and deleted after the agent finishes its task.

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