🌦️ Build Your Own Open-Source Weather API Using Python, FastAPI, and Open-Meteo in Windows 11

 

No API Keys. 100% Free. Runs on Windows, Linux, or macOS.

If you’ve ever wanted to build a weather service that you fully control—without relying on paid providers—this guide is for you. Today we’ll build a fully open-source weather API using:

✔ Python
✔ FastAPI
✔ Uvicorn
✔ Open-Meteo (free, no API key)

This weather server runs locally on any computer and can be extended to power automation tools, chatbots, dashboards, or IoT projects.

Let’s get started!

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🚀 Why Open-Source Instead of Claude/Proprietary MCP?

In the MCP ecosystem, servers are often built to integrate with specific applications like Claude Desktop. But not everyone wants to depend on closed-source platforms.

This tutorial shows how to build a fully standalone weather API, powered only by open-source tools:

• FastAPI → modern Python web framework

• Uvicorn → lightning-fast ASGI server

• Open-Meteo API → real-time global weather data

• httpx → async HTTP client

The result?
A clean, extensible, open-source weather microservice you can run anywhere.

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🖥️ Step 1 — Install Requirements (Windows / macOS / Linux)

Open a terminal or PowerShell window and install dependencies:

pip install fastapi uvicorn httpx

That’s all you need.

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🏗️ Step 2 — Create the Project File

Create a new directory:

mkdir weather-server
cd weather-server

Then create:

server.py

Paste in the full working code:

from typing import Any
import httpx
from fastapi import FastAPI

# Initialize FastAPI app
app = FastAPI()

# Constants
OPENMETEO_API_BASE = "https://api.open-meteo.com/v1"
USER_AGENT = "weather-mcp/1.0"

# Helper function to interact with the Open-Meteo API
async def make_openmeteo_request(url: str) -> dict[str, Any] | None:
    """Make a request to the Open-Meteo API with proper error handling."""
    headers = {
        "User-Agent": USER_AGENT,
        "Accept": "application/json",
    }
    async with httpx.AsyncClient() as client:
        try:
            response = await client.get(url, headers=headers, timeout=30.0)
            response.raise_for_status()
            return response.json()
        except Exception:
            return None

# -----------------------------
# Endpoint - Get Current Weather
# -----------------------------
@app.get("/current-weather")
async def get_current_weather(latitude: float, longitude: float) -> dict:
    """Get current weather data for a specified latitude/longitude."""
    
    url = (
        f"{OPENMETEO_API_BASE}/forecast"
        f"?latitude={latitude}&longitude={longitude}"
        "&current=temperature_2m,is_day,showers,cloud_cover,wind_speed_10m,"
        "wind_direction_10m,pressure_msl,snowfall,precipitation,"
        "relative_humidity_2m,apparent_temperature,rain,weather_code,"
        "surface_pressure,wind_gusts_10m"
    )

    data = await make_openmeteo_request(url)

    if not data:
        return {"error": "Unable to fetch current weather data for this location."}

    return data

# -----------------------------
# Endpoint - Get Weather Forecast
# -----------------------------
@app.get("/forecast")
async def get_forecast(latitude: float, longitude: float, days: int = 3) -> dict:
    """Get forecast for next X days."""
    
    url = (
        f"{OPENMETEO_API_BASE}/forecast"
        f"?latitude={latitude}&longitude={longitude}"
        f"&hourly=temperature_2m,precipitation,cloud_cover"
        f"&forecast_days={days}"
    )

    data = await make_openmeteo_request(url)
    if not data:
        return {"error": "Unable to fetch forecast."}

    return data

# -----------------------------
# Endpoint - Get Location by Name
# -----------------------------
@app.get("/location")
async def get_location(query: str) -> dict:
    """Search for a city/place name and get coordinates."""
    
    url = f"https://geocoding-api.open-meteo.com/v1/search?name={query}&count=5"
    
    data = await make_openmeteo_request(url)
    
    if not data:
        return {"error": "Location not found."}
    
    return data

---

▶️ Step 3 — Run Your Server

Start the server using Uvicorn:

uvicorn server:app --reload

You’ll see:

Uvicorn running on http://127.0.0.1:8000

Open your browser and test:

✔ Current Weather

http://127.0.0.1:8000/current-weather?latitude=40.7128&longitude=-74.0060

✔ Forecast

http://127.0.0.1:8000/forecast?latitude=40.7128&longitude=-74.0060&days=3

✔ Location Search

http://127.0.0.1:8000/location?query=London

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📘 Step 4 — Use the Interactive Dashboard

FastAPI provides automatic documentation.

Open:

http://127.0.0.1:8000/docs

You now have:

• A UI for testing all endpoints

• Auto-generated schema

• Live API explorer

No additional setup. It just works.

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🧩 Step 5 — Why This Matters

This small project demonstrates how you can:

• Build useful microservices with only open-source tools

• Consume real-time weather data without API keys

• Extend the API into dashboards, chatbots, IoT devices, and more

• Deploy the service anywhere (Docker, VPS, Raspberry Pi, etc.)

It’s clean, lightweight, and completely free to use.

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🎉 Final Thoughts

With Python, FastAPI, and Open-Meteo, you now have a fully functioning open-source weather server that you can run locally or deploy to the cloud.

This is a perfect foundation for:

• AI integrations

• Automation scripts

• Custom user interfaces

• Smart home systems

• Education and learning projects

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