This article provides a complete, practical walkthrough of the Openweathermap Webhook Create Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Real-Time Weather Updates Using n8n and OpenWeatherMap: A No-Code Guide
   
   Meta Description:
   Learn how to build an automated weather-fetching workflow using n8n and OpenWeatherMap. This step-by-step guide helps you integrate weather data via a simple HTTP webhook without writing a single line of code.
   
   Keywords:
   n8n, OpenWeatherMap API, no-code automation, real-time weather, HTTP webhook, weather integration, automation workflow, API data retrieval, set node, HTTP GET webhook
   
   Third-Party APIs Used:
   - OpenWeatherMap API
   
   Article:
   
   Automate Real-Time Weather Reporting with n8n and the OpenWeatherMap API
   
   The modern world thrives on automation—and when it comes to accessing real-time data like current weather conditions, automation tools like n8n make it easier than ever. Whether you're building a weather dashboard, integrating climate data into your app, or simply want to receive quick weather updates via HTTP requests, you can do all of that without writing a single line of traditional code.
   
   In this article, we’ll walk you through a simple but powerful n8n workflow that fetches current weather data from the OpenWeatherMap API based on a city specified via a GET request. Let’s dive into how it works and how you can implement it yourself.
   
   Overview of the Workflow
   
   This n8n workflow contains four primary nodes:
   
   1. Webhook (GET) – receives the request with query parameters.
   2. Set – extracts or defaults the city name.
   3. OpenWeatherMap – fetches weather data for the specified city.
   4. Set – builds a readable response message.
     
   Together, these nodes allow you to expose a public URL (via Webhook), receive a city parameter, get the current weather for that city, and return a human-readable weather summary.
   
   Step-by-Step Breakdown
   
   1. Webhook GET Node – Creating the Entry Point
   
   The workflow initiates with a Webhook node set to respond to an HTTP GET request on the path /weather. This publicly accessible endpoint listens for incoming requests that may (optionally) include a query parameter named "parameter" (e.g., ?parameter=london,uk). The webhook is configured to send the workflow’s final node output as the response, making it ideal for building a live weather query endpoint.
   
   2. Set Node – Determining the City
   
   Next, the workflow uses a Set node titled "Set City" to extract the city name from the incoming HTTP request query. If the city is not provided via query parameter, it defaults to 'berlin,de'.
   
   For example:
   - User sends: /weather?parameter=london,uk → the city is set to "london,uk"
   - User sends: /weather → the city defaults to "berlin,de"
   
   This conditional logic ensures there’s always a valid city name passed to the OpenWeatherMap API.
   
   3. OpenWeatherMap Node – Fetching Real-Time Data
   
   This is where the magic happens. n8n’s built-in OpenWeatherMap node takes the city value and sends a request to OpenWeatherMap to fetch real-time weather data. Once authenticated (by adding your API key in the credentials), the node returns a JSON response containing temperature, “feels like” temperature, humidity, city name, and more.
   
   4. Set Node – Crafting the Response
   
   The final stop is another Set node titled "Create Response". This node extracts key weather details from the OpenWeatherMap response, including:
   - Current temperature
   - "Feels like" temperature
   - City name
   
   It then creates a user-friendly string such as:
   "It has 21.5℃ and feels like 20.3℃ in London"
   
   This response string is stored in a property called "data", which becomes the final output returned by the Webhook node.
   
   Usage Examples
   
   To test your newly-created workflow, simply deploy it on your local n8n instance or on a remote instance like n8n.cloud.
   
   Example API calls:
   - GET http://localhost:5678/webhook/weather?parameter=london,uk
   - GET http://localhost:5678/webhook/weather
   
   These will return real-time temperature and “feels like” conditions in London or Berlin depending on whether a parameter is supplied.
   
   Real-World Applications
   
   - Weather dashboards or info panels
   - Automated climate alerts via Slack or email
   - On-demand weather reporting in other apps and services
   - Voice assistant integrations
   
   Why Use n8n?
   
   n8n is a powerful automation and integration tool that empowers both developers and non-developers to build complex workflows without coding. By using pre-built nodes and logical connectors, you can automate data collection, transformation, and distribution in just a few clicks.
   
   With over 300+ available integrations, n8n plays nicely with APIs, databases, messaging services, and cloud tools. Its visual drag-and-drop UI makes it an ideal choice for flexible, low-maintenance automations.
   
   Closing Thoughts
   
   This basic n8n workflow demonstrates how easy it can be to tap into the rich data offered by third-party APIs like OpenWeatherMap. With just four nodes, you’ve created a real-time weather microservice that can be embedded into larger applications or used on its own.
   
   As next steps, consider enriching your weather bot by:
   - Adding error handling for incorrect or missing API keys
   - Formatting temperature data more elegantly
   - Supporting multiple response formats (JSON, text, etc.)
   - Logging incoming requests with timestamps
   
   Whether you're automating business intelligence, building personal tools, or experimenting with APIs, this workflow is a simple yet powerful example of what you can achieve with n8n. So go on—try it out and let your creativity reign in the world of no-code automation.
   
   Happy automating!

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.