How to Use the AccuWeather MCP in CrewAI
Equip your CrewAI agent teams with professional-grade weather intelligence from AccuWeather for autonomous research and action.
Works with every AI agent you already use
…and any MCP-compatible client
Connect AccuWeather MCP to CrewAI
Create your Vinkius account to connect AccuWeather 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.
Assemble a Weather Research Team
The `search_location` tool is the first step for any weather query. With CrewAI, you can assign this task to a dedicated agent. Create a 'Location Scout' agent that finds the right location key. It then passes that key to a 'Forecast Analyst' agent, which uses `get_daily_forecast` and `get_hourly_forecast` to gather data. This role-based specialization is exactly what CrewAI was built for.
Run Weather-Aware Autonomous Agents
Your crew can use the `get_weather_indices` tool to make decisions without human help. Imagine a 'Travel Logistics' crew monitoring a future trip. One agent checks the `flight_delay_probability` index daily. If it crosses a certain threshold, it alerts a 'Booking Agent' to start looking for alternate flights. This isn't a script; it's an autonomous team using this MCP server to respond to changing conditions.
Delegate Tasks to Specialist Agents
The `get_weather_alarms` tool is critical for safety. You can build a 'Safety Crew' where one agent's only job is to monitor for severe weather alerts. If that agent finds an active hurricane or tornado warning, it passes the alert details to an 'Action Agent' that executes an emergency plan—like sending mass notifications or shutting down equipment. CrewAI allows each agent to focus on one part of the problem, using shared context from the AccuWeather MCP to collaborate.
Set up AccuWeather MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke AccuWeather tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="AccuWeather Analyst",
goal="Access and analyze AccuWeather data via MCP.",
backstory="Expert analyst with direct AccuWeather access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent AccuWeather transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="AccuWeather Analyst",
goal="Access and analyze AccuWeather data via MCP.",
backstory="Expert analyst with direct AccuWeather access.",
tools=mcp_tools,
)
task = Task(
description="List recent AccuWeather transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AccuWeather. 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 AccuWeather MCP in CrewAI
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