OpenWeatherMap MCP Server for Pydantic AIGive Pydantic AI instant access to 6 tools to Direct Geocoding, Get Air Pollution, Get Current Weather, and more

Name: OpenWeatherMap
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The OpenWeatherMap MCP Server for Pydantic AI is a standout in the Data Analytics category — giving your AI agent 6 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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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 OpenWeatherMap "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in OpenWeatherMap?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About OpenWeatherMap MCP Server

Connect OpenWeatherMap to your AI agent to get instant access to global meteorological data. Whether you're planning travel, monitoring environmental conditions, or building weather-aware automations, this server provides the precise data you need.

Pydantic AI validates every OpenWeatherMap tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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

Current Conditions — Get live temperature, humidity, wind speed, and weather descriptions for any city or coordinate via get_current_weather.
Extended Forecasts — Access 5-day/3-hour forecasts with get_forecast or use the One Call 3.0 API for 48-hour hourly and 8-day daily projections via get_onecall.
Air Quality Monitoring — Retrieve real-time pollution data including PM2.5, PM10, CO, and Ozone levels using get_air_pollution.
Geocoding Services — Seamlessly convert city names to coordinates with direct_geocoding and vice versa with reverse_geocoding to power location-based queries.

The OpenWeatherMap MCP Server exposes 6 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 OpenWeatherMap tools available for Pydantic AI

When Pydantic AI connects to OpenWeatherMap through Vinkius, your AI agent gets direct access to every tool listed below — spanning meteorology, weather-forecast, air-quality, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

direct

Direct geocoding on OpenWeatherMap

Convert city names or zip codes into coordinates

get

Get air pollution on OpenWeatherMap

5, PM10, and NH3. Get current air pollution data

get

Get current weather on OpenWeatherMap

Get current weather data

get

Get forecast on OpenWeatherMap

Get 5 Day / 3 Hour Forecast

get

Get onecall on OpenWeatherMap

Get One Call API 3.0 weather data

reverse

Reverse geocoding on OpenWeatherMap

Convert coordinates into city names

Connect OpenWeatherMap to Pydantic AI via MCP

Follow these steps to wire OpenWeatherMap into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 6 tools from OpenWeatherMap with type-safe schemas

Why Use Pydantic AI with the OpenWeatherMap MCP Server

Pydantic AI provides unique advantages when paired with OpenWeatherMap 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 OpenWeatherMap integration code

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

Dependency injection system cleanly separates your OpenWeatherMap connection logic from agent behavior for testable, maintainable code

OpenWeatherMap + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the OpenWeatherMap MCP Server delivers measurable value.

Type-safe data pipelines: query OpenWeatherMap with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple OpenWeatherMap tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query OpenWeatherMap and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock OpenWeatherMap responses and write comprehensive agent tests

Example Prompts for OpenWeatherMap in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with OpenWeatherMap immediately.

"What's the current weather in London?"

"Give me the 5-day forecast for Tokyo."

"Check the air pollution levels at latitude 40.71 and longitude -74.00."

Troubleshooting OpenWeatherMap MCP Server with Pydantic AI

Common issues when connecting OpenWeatherMap to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

OpenWeatherMap + Pydantic AI FAQ

Common questions about integrating OpenWeatherMap 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 OpenWeatherMap MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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