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 Pydantic AI 3 tools — connect in under 2 minutes

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

ai.pydantic.dev/mcp

Built by Vinkius GDPR 3 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Open-Meteo Marine Weather through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Open-Meteo Marine Weather "
            "(3 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Open-Meteo Marine Weather?"
    )
    print(result.data)

asyncio.run(main())

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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.

Pydantic AI validates every Open-Meteo Marine Weather tool response against typed schemas, catching data inconsistencies at build time. Connect 3 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

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 Pydantic AI 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 Pydantic AI via MCP

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

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 3 tools from Open-Meteo Marine Weather with type-safe schemas

Why Use Pydantic AI with the Open-Meteo Marine Weather MCP Server

Pydantic AI provides unique advantages when paired with Open-Meteo Marine Weather through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Open-Meteo Marine Weather integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Open-Meteo Marine Weather connection logic from agent behavior for testable, maintainable code

Open-Meteo Marine Weather + Pydantic AI Use Cases

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

Type-safe data pipelines: query Open-Meteo Marine Weather with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Open-Meteo Marine Weather tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Open-Meteo Marine Weather and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Open-Meteo Marine Weather responses and write comprehensive agent tests

Open-Meteo Marine Weather MCP Tools for Pydantic AI (3)

These 3 tools become available when you connect Open-Meteo Marine Weather to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Open-Meteo Marine Weather + Pydantic AI FAQ

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

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Open-Meteo Marine Weather MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.