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Integrating AI with Open-Meteo API for enhanced weather forecasting

Davi Saranszky MesquitaDavi Saranszky Mesquita
3339 views
2/3/2026
PostgreSQLData IntegrationHTTP RequestAPI TriggerDatabase Query
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Use case

Workshop

We are using this workflow in our workshops to teach how to use Tools a.k.a functions with artificial intelligence. In this specific case, we will use a generic "AI Agent" node to illustrate that it could use other models from different data providers.

Enhanced Weather Forecasting

In this small example, it's easy to demonstrate how to obtain weather forecast results from the Open-Meteo site to accurately display the upcoming days.

This can be used to plan travel decisions, for example.

What this workflow does

  1. We will make an HTTP request to find out the geographic coordinates of a city.
  2. Then, we will make other HTTP requests to discover the weather for the upcoming days.

In this workshop, we demonstrate that the AI will be able to determine which tool to call first—it will first call the geolocation tool and then the weather forecast tool. All of this within a single client conversation call.

Setup

Insert an OpenAI Key and activate the workflow.

by Davi Saranszky Mesquita https://www.linkedin.com/in/mesquitadavi/

Integrating AI with Open-Meteo API for Enhanced Weather Forecasting

This n8n workflow demonstrates how to build an AI agent that can interact with the Open-Meteo API to fetch and interpret weather forecasts based on user queries. It leverages LangChain nodes within n8n to create a conversational AI that can understand natural language requests and use a custom HTTP Request tool to retrieve real-time weather data.

What it does

This workflow simplifies and automates the process of getting weather information through a conversational AI interface. Here's a step-by-step breakdown:

  1. Listens for Chat Messages: The workflow is triggered whenever a new chat message is received, acting as the user's input to the AI.
  2. Manages Conversation History: A "Simple Memory" node maintains the context of the conversation, allowing the AI to remember previous turns and provide more coherent responses.
  3. Utilizes an OpenAI Chat Model: An OpenAI Chat Model (e.g., GPT-3.5 or GPT-4) serves as the brain of the AI agent, understanding user queries and formulating responses.
  4. Enables an AI Agent: The "AI Agent" node orchestrates the interaction between the chat model, memory, and available tools to decide the best course of action for a given user input.
  5. Provides an HTTP Request Tool: A custom "HTTP Request Tool" is configured specifically to interact with the Open-Meteo API. This tool allows the AI Agent to make API calls to fetch weather data when needed. The AI Agent is designed to understand when to use this tool based on the user's weather-related questions.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance (cloud or self-hosted).
  • OpenAI API Key: An API key for OpenAI to use their chat models. This will need to be configured as a credential in your n8n instance.
  • Open-Meteo API: While the Open-Meteo API is generally open and doesn't require an API key for basic usage, the HTTP Request Tool in this workflow is designed to interact with it.

Setup/Usage

  1. Import the Workflow:
    • Download the provided JSON workflow.
    • In your n8n instance, go to "Workflows" and click "New".
    • Click the "Import from JSON" button and paste the workflow JSON.
  2. Configure Credentials:
    • Locate the "OpenAI Chat Model" node.
    • Click on the "Credential" field and select or create an "OpenAI API" credential. Enter your OpenAI API Key.
  3. Activate the Workflow:
    • Ensure the workflow is active by toggling the "Active" switch in the top right corner.
  4. Interact with the Chat Trigger:
    • The "When chat message received" node acts as the entry point. You would typically interact with this via a connected chat service (e.g., Telegram, Slack, etc., configured with a separate chat trigger) or by manually testing the node with a sample message.
    • Send a message like "What's the weather like in London?" or "Will it rain tomorrow in Berlin?" to the chat trigger. The AI agent will then use the HTTP Request Tool to fetch the weather data and respond.

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