How accurate are the wave forecasts?

Wave data is sourced from **ECMWF WAM, DWD EWAM, and NCEP GFS Wave** models at 5km resolution. Accuracy is excellent for open ocean but limited near coastlines due to resolution constraints.

Open-Meteo Marine Weather MCP Server for CrewAI 3 tools — connect in under 2 minutes

Name: Open-Meteo Marine Weather
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 3 Tools Framework

Connect your CrewAI agents to Open-Meteo Marine Weather through Vinkius, pass the Edge URL in the `mcps` parameter and every Open-Meteo Marine Weather tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Open-Meteo Marine Weather Specialist",
    goal="Help users interact with Open-Meteo Marine Weather effectively",
    backstory=(
        "You are an expert at leveraging Open-Meteo Marine Weather tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Open-Meteo Marine Weather "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 3 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Open-Meteo Marine Weather MCP Server

Turn your AI agent into a maritime weather specialist with real-time ocean data at 5km resolution.

When paired with CrewAI, Open-Meteo Marine Weather becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Open-Meteo Marine Weather tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Wave Forecasts — Wave height, period, direction, plus wind-wave and swell components separated
Ocean Currents — Current velocity, direction, and sea surface temperature
Daily Marine Summary — Max wave height, dominant wave direction, and dominant period aggregated daily

The Open-Meteo Marine Weather MCP Server exposes 3 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Open-Meteo Marine Weather to CrewAI via MCP

Follow these steps to integrate the Open-Meteo Marine Weather MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 3 tools from Open-Meteo Marine Weather

Why Use CrewAI with the Open-Meteo Marine Weather MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Open-Meteo Marine Weather through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Open-Meteo Marine Weather + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Open-Meteo Marine Weather MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Open-Meteo Marine Weather for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Open-Meteo Marine Weather, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Open-Meteo Marine Weather tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Open-Meteo Marine Weather against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Open-Meteo Marine Weather MCP Tools for CrewAI (3)

These 3 tools become available when you connect Open-Meteo Marine Weather to CrewAI via MCP:

get_daily_marine

Get daily marine weather summary

get_marine_forecast

Provides hourly forecast data for maritime planning. Get marine wave forecast at 5km resolution

get_ocean_currents

Get ocean current velocity and sea surface temperature

Example Prompts for Open-Meteo Marine Weather in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Open-Meteo Marine Weather immediately.

"What are the wave conditions off the coast of Hawaii right now?"

"Is it safe to sail across the English Channel tomorrow?"

"What's the maximum wave height expected in the North Sea this week?"

Troubleshooting Open-Meteo Marine Weather MCP Server with CrewAI

Common issues when connecting Open-Meteo Marine Weather to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Open-Meteo Marine Weather + CrewAI FAQ

Common questions about integrating Open-Meteo Marine Weather MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.