How accurate is the flood forecast?

Data comes from **GloFAS v4** (Global Flood Awareness System) by Copernicus at 5km resolution. Short-term forecasts (1-30 days) are highly reliable. Seasonal forecasts (1-7 months) indicate trends but have wider uncertainty bands.

Open-Meteo Flood & Rivers MCP Server for Pydantic AI 3 tools — connect in under 2 minutes

Name: Open-Meteo Flood & Rivers
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 Flood & Rivers 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 Flood & Rivers "
            "(3 tools)."
        ),
    )

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

asyncio.run(main())

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About Open-Meteo Flood & Rivers MCP Server

Arm your AI with flood intelligence powered by the Global Flood Awareness System (GloFAS).

Pydantic AI validates every Open-Meteo Flood & Rivers 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

River Discharge — Real-time simulated river discharge in m³/s at 5km resolution
Flood Forecast — Up to 7 months of forward river discharge predictions for early warning
Historical Discharge — 40+ years of reanalysis data from 1984 for trend analysis

The Open-Meteo Flood & Rivers 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 Flood & Rivers to Pydantic AI via MCP

Follow these steps to integrate the Open-Meteo Flood & Rivers 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 Flood & Rivers with type-safe schemas

Why Use Pydantic AI with the Open-Meteo Flood & Rivers MCP Server

Pydantic AI provides unique advantages when paired with Open-Meteo Flood & Rivers 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 Flood & Rivers 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 Flood & Rivers connection logic from agent behavior for testable, maintainable code

Open-Meteo Flood & Rivers + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Open-Meteo Flood & Rivers MCP Server delivers measurable value.

Type-safe data pipelines: query Open-Meteo Flood & Rivers with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Open-Meteo Flood & Rivers 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 Flood & Rivers and output structured, schema-compliant notifications

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

Open-Meteo Flood & Rivers MCP Tools for Pydantic AI (3)

These 3 tools become available when you connect Open-Meteo Flood & Rivers to Pydantic AI via MCP:

get_flood_forecast

Data from GloFAS covering up to 210 days of prediction. Get flood forecast up to 7 months ahead

get_historical_discharge

Get historical river discharge data (1984–present)

get_river_discharge

Useful for flood monitoring and water resource management. Get river discharge data at 5km resolution

Example Prompts for Open-Meteo Flood & Rivers in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Open-Meteo Flood & Rivers immediately.

"What's the current river discharge near Bangkok?"

"Is there flood risk along the Rhine River in the next 3 months?"

"Compare Danube River discharge in 2002 vs today"

Troubleshooting Open-Meteo Flood & Rivers MCP Server with Pydantic AI

Common issues when connecting Open-Meteo Flood & Rivers to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Open-Meteo Flood & Rivers + Pydantic AI FAQ

Common questions about integrating Open-Meteo Flood & Rivers 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 Flood & Rivers MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.