How to Use the Tomorrow.io MCP in CrewAI

Q: How do I check historical weather data using Tomorrow.io and CrewAI?

You pass gethistoricalweather to your crew. A research agent can pull past observations, allowing the team to analyze trends or verify current predictions against recorded facts.

Q: What specialized weather inputs does Tomorrow.io provide for CrewAI?

The server offers highly specific tools like getairqualityindex and getpollenforecast. A crew can be built where one agent focuses solely on air quality while another handles temperature.

Q: Can I use Tomorrow.io to monitor weather conditions with CrewAI?

Yes. You can set up an autonomous monitoring loop using getminutelyprecipitation and gethourlyforecast. The system continuously checks the latest data points for immediate action.

Autonomous Operations: Build specialized climate analysis crews with CrewAI.

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Connect Tomorrow.io MCP to CrewAI

Create your Vinkius account to connect Tomorrow.io 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 Tomorrow.io with CrewAI

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Running Automated Weather Scouting

Set up a research agent to run `get_realtime_weather`. The crew can automatically gather current conditions for multiple locations across the globe. This works well when you need several specialized agents to report back on conditions simultaneously, sharing the results in the shared memory.

Analyzing Extreme Climate Events

Assign an analysis agent to run `get_wildfire_risk` and another to check `get_road_weather_risk`. These two agents work together to analyze potential travel hazards. This shows the power of role-based specialization in CrewAI, allowing multiple perspectives on a single complex event.

Scheduling Multi-Day Operations

Use `get_daily_forecast` to gather 15 days of data. One agent researches the long-term trend, and a monitor agent reviews the results for anomalies. This process is ideal for autonomous operations where a full operational cycle—research, analysis, reporting—must happen without human input.

Setup guide

Set up Tomorrow.io 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 Tomorrow.io tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You pass `get_historical_weather` to your crew. A research agent can pull past observations, allowing the team to analyze trends or verify current predictions against recorded facts.

The server offers highly specific tools like `get_air_quality_index` and `get_pollen_forecast`. A crew can be built where one agent focuses solely on air quality while another handles temperature.

Yes. You can set up an autonomous monitoring loop using `get_minutely_precipitation` and `get_hourly_forecast`. The system continuously checks the latest data points for immediate action.

The server covers comprehensive global climate intelligence, from daily forecasts to minute-by-minute precipitation nowcasts, supporting various operational needs.

This server touches location-based weather and air quality data, specifically including latitude/longitude coordinates and general city names when making a request.

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