How to Use the Tomorrow.io Extended MCP in CrewAI

Q: Is the historical context available from Tomorrow.io Extended on CrewAI?

The getrecenthistory tool lets your agents pull back past weather conditions. This gives the crew enough data to compare current status against long-term trends.

Build autonomous weather intelligence pipelines with CrewAI's collaborative multi-agent system.

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Connect Tomorrow.io Extended MCP to CrewAI

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

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Perplexity

Analyze air quality using dedicated agents.

You can assign a 'Research Agent' to use `get_air_quality`. This agent pulls the pollution data, which is then passed to an 'Analysis Agent.' The analysis agent interprets what those metrics mean for health. This separation of roles means one agent focuses solely on retrieval while another handles complex interpretation.

Monitor and escalate weather alerts with CrewAI.

Set up a 'Monitor Agent' whose sole job is to call `list_weather_alerts`. If the alert status is critical, it triggers an 'Action Agent' that drafts and sends an immediate warning message. This hierarchical execution mimics real-world emergency response protocols.

Build a full weather picture using MCP Server.

A specialized 'Forecasting Crew' can collaborate. One agent fetches `get_weather_forecast`, and another immediately verifies those predictions against the current data using `get_realtime_weather`. The result is a verified, comprehensive report. This shared memory mechanism ensures all agents work from the same pool of accurate, cross-referenced information.

Setup guide

Set up Tomorrow.io Extended 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 Extended tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You pass the MCP Server URL directly to your Agent configuration within CrewAI. The framework then makes the tools available for agents to call during their collaboration cycles.

The server provides a full spectrum: real-time weather, historical summaries (`get_recent_history`), air quality indices, and future predictive forecasts.

Yes. You build an autonomous workflow where one agent checks `list_weather_alerts`, and a second agent takes the findings and drafts an official communication based on those warnings.

This MCP Server deals exclusively with public weather and air quality data types. Your agents only read this information, never touching private user records.

The `get_recent_history` tool lets your agents pull back past weather conditions. This gives the crew enough data to compare current status against long-term trends.

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