Weather MCP Server — Forecast & Air Quality avatar

Weather MCP Server — Forecast & Air Quality

Pricing

from $5.00 / 1,000 mcp tool calls

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Weather MCP Server — Forecast & Air Quality

Weather MCP Server — Forecast & Air Quality

Get current weather, forecasts, historical conditions, and air-quality data through an MCP-ready API for AI agents and automated workflows.

Pricing

from $5.00 / 1,000 mcp tool calls

Rating

0.0

(0)

Developer

Muhammad Afzal

Muhammad Afzal

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

17 days ago

Last modified

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MCP server exposing 4 weather tools for AI agents. Connect Claude, Cursor, ChatGPT, n8n, OpenAI Agents SDK, or any MCP-compatible client to live weather data worldwide. No API key required.

What it does

This Actor runs a Model Context Protocol (MCP) server in Standby mode on the Apify platform. It exposes four agent-callable tools that fetch weather data from the free Open-Meteo API (no API key, commercially licensed):

ToolWhat it returns
get_current_weatherCurrent temperature, feels-like, humidity, precipitation, cloud cover, pressure, wind speed/direction/gusts, day/night flag, weather description, and a one-line summary
get_weather_forecast1–16 day forecast with per-day high/low temp, feels-like, precipitation, rain, snowfall, precipitation probability, wind, sunrise/sunset, UV index; optional hourly breakdown
get_historical_weatherHistorical weather observations for any date range — per-day temp, precipitation, wind, sunshine duration
get_air_qualityCurrent air quality — PM10, PM2.5, CO, NO₂, SO₂, O₃, UV index, European AQI, US AQI, and category label (Good/Moderate/Unhealthy/etc.)

Use cases

  • AI assistants querying current weather and multi-day forecasts for user-specified locations
  • Travel and trip planning agents that need up-to-date conditions and short-term forecasts
  • Logistics and supply chain automation checking weather along routes
  • Agriculture and field-operations planning (frost risk, irrigation windows)
  • Air quality monitoring and health advisory applications
  • LLM-driven planning workflows that require weather context during reasoning
  • n8n / Make / Zapier integrations for weather-triggered automations

How to use

Connect to Claude, Cursor, or any MCP client

Add the server to your MCP client configuration:

{
"mcpServers": {
"weather-mcp-server": {
"url": "https://muhammadafzal--weather-mcp-server.apify.actor/mcp",
"headers": {
"Authorization": "Bearer <YOUR_APIFY_API_TOKEN>"
}
}
}
}

Get your Apify API token from the Apify Console → Account → Integrations.

Call tools programmatically

Each tool accepts either a city name (location) or direct coordinates (latitude + longitude):

get_current_weather(location="London")
get_weather_forecast(location="Tokyo", forecastDays=5, includeHourly=true)
get_historical_weather(location="Berlin", startDate="2024-01-01", endDate="2024-01-31")
get_air_quality(location="Delhi")

Pricing

This Actor uses pay-per-event pricing:

EventPrice
Actor Start$0.00005 per event (one per GB of memory, minimum one)
MCP Tool Call$0.005 per tool invocation

Typical cost: A single weather lookup costs ~$0.005. A week of daily weather checks for 10 cities = ~$0.35.

Data sources

No API keys, no logins, no rate limits beyond fair use.

Technical details

  • Language: Python 3.12
  • Framework: FastMCP + uvicorn
  • Transport: Streamable HTTP (MCP standard)
  • Mode: Standby (always-ready, auto-scales with demand)
  • Endpoint: https://muhammadafzal--weather-mcp-server.apify.actor/mcp

Input

In Standby/MCP mode, tool calls are made through the /mcp endpoint — the Actor input is only used for batch-mode connectivity tests.

FieldTypeDefaultDescription
defaultLocationstring""City name for batch-mode test
defaultLatitudenumber0Latitude for batch-mode test
defaultLongitudenumber0Longitude for batch-mode test

Output

Each tool call returns a structured JSON object. The dataset also stores each tool call result for auditing.

Export scraped data, run the scraper via API, schedule and monitor runs, or integrate with other tools

Apify gives you access to the raw data, APIs, webhooks, and automation tools you need to build data pipelines. Export to JSON, CSV, Excel, or send to Google Sheets, Airtable, or any webhook via integrations.

Support

Found a bug or have a feature request? Open an issue on the Apify Store page.

What is Weather MCP Server?

Weather MCP Server turns the target data into structured, reusable results on Apify. Use it when you need repeatable collection for analysts, developers, agencies, researchers, and AI-agent workflows without maintaining a custom scraper or one-off integration. Run it manually, schedule recurring jobs, call it through the Apify API, or connect it to an AI agent through the Apify MCP server.

The Actor stores results in an Apify dataset, where they can be previewed and exported as JSON, CSV, Excel, XML, or RSS. Availability and completeness depend on the source, supplied inputs, public visibility, authentication requirements, and upstream rate limits.

Use cases for Weather MCP Server

  • Build structured datasets for research, reporting, enrichment, or monitoring.
  • Automate repetitive collection with schedules, webhooks, and API calls.
  • Feed clean records into spreadsheets, databases, CRMs, BI tools, AI agents, or RAG pipelines.
  • Track changes over time by running the same validated input on a schedule.
  • Replace fragile manual copy-and-paste work with a reproducible Apify workflow.

How to use Weather MCP Server

  1. Open the Actor input page and choose a focused, valid target.
  2. Set a conservative result limit for the first run.
  3. Start the Actor and inspect the dataset for coverage and field availability.
  4. Export the results or connect the dataset to your downstream system.
  5. Scale gradually and use scheduling, pagination, or proxies when supported.

Important input options

  • defaultLocation — City name for batch-mode connectivity test. In Standby/MCP mode this is ignored — each tool call provides its own location. Example: 'London'. Use this field when the user says 'test the wea
  • defaultLatitude — Latitude for batch-mode connectivity test. Overrides defaultLocation. Example: 51.5074. NOT used in MCP tool calls.
  • defaultLongitude — Longitude for batch-mode connectivity test. Overrides defaultLocation. Example: -0.1278. NOT used in MCP tool calls.

API and automation example

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('muhammadafzal/weather-mcp-server').call({
// Add the same input fields you use in the Apify Console.
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Use these dedicated tools when a neighboring data source or workflow is a better match:

Frequently asked questions

How many results can I scrape with Weather MCP Server?

The practical total depends on the source, input limits, pagination, available records, run timeout, and upstream restrictions. Start with a small run, verify the output, and increase the limit gradually.

Can I integrate Weather MCP Server with other apps?

Yes. Use Apify integrations, webhooks, schedules, dataset exports, Make, Zapier, Google Sheets, cloud storage, or your own application.

Can I use Weather MCP Server with the Apify API?

Yes. Start runs with the Apify REST API or an official Apify client, then retrieve records from the run's default dataset. Keep your API token in a secret or environment variable.

Can I use Weather MCP Server through an MCP Server?

Yes. The Apify MCP server can expose the Actor to compatible AI clients and agents. Review the input and expected cost before allowing an autonomous workflow to run it at scale.

Do I need proxies?

It depends on the source and volume. Use the default configuration first. For larger or geographically sensitive jobs, select an appropriate proxy configuration only when the Actor supports it.

Scraping rules vary by source, jurisdiction, data type, and intended use. Collect only data you are authorized to access, respect applicable terms and privacy laws, and avoid restricted or personal data misuse. This documentation is not legal advice.

Your feedback

If a field is missing, a source layout has changed, or you need a supported use case documented, open an issue on the Actor page with a reproducible input and run ID.