This article provides a complete, practical walkthrough of the Manual Googlesheets Automation 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:  
   Automating Agricultural Data Collection with n8n: A No-Code Workflow for Sheep Market Prices
   
   Meta Description:  
   Learn how to automate the retrieval and storage of agricultural market price data using n8n. This step-by-step workflow pulls sheep market prices from the Taiwan Ministry of Agriculture and saves the data directly into a Google Sheet.
   
   Keywords:  
   n8n, automation, Google Sheets, agriculture data, sheep market prices, Taiwan Ministry of Agriculture API, no-code automation, API integration, data scraping, workflow automation, agri-tech
   
   Third-Party APIs Used:
   
   - Taiwan Ministry of Agriculture API (https://data.moa.gov.tw/api/v1/SheepQuotation)
   - Google Sheets API via OAuth2
   
   Article:
   
   In the ever-growing agri-tech space, data automation plays a crucial role in improving efficiency, minimizing human error, and enabling informed decision-making. For analysts, researchers, and businesses dealing with real-time agricultural data, staying updated with market trends is vital — and time-consuming if done manually.
   
   In this guide, we explore how to automate the retrieval of sheep market price data from the Taiwan Ministry of Agriculture’s public API and store it directly into a Google Spreadsheet using n8n, an open-source, no-code workflow automation tool.
   
   What Does This Workflow Do?
   
   Named “n8n-農產品” (Agricultural Products), this workflow fetches transactional sheep price data from the Ministry of Agriculture’s open data API, filters the desired timeframe and market, splits the response data into individual records, and stores them neatly in a Google Sheet for easy access and further analysis.
   
   Let’s break down how each part of the workflow contributes to this seamless process.
   
   1. Triggering the Workflow
   
   The first node is a Manual Trigger named “When clicking ‘Test workflow’.” This allows the user to run the workflow on-demand for testing or manual updates. While it doesn’t run on a schedule (yet), this manual initiation lets you validate inputs and outputs before full automation.
   
   2. Fetching Sheep Quotation Data from the API
   
   Next is an HTTP Request node configured to call the following API endpoint:
   
   https://data.moa.gov.tw/api/v1/SheepQuotation
   
   With parameters:
   - Start_time: "2024/12/01"
   - End_time: "2024/12/31"
   - MarketName: "台北二" (Taipei Second Wholesale Market)
   - api_key: “3AFID4BGE9PDQ2WTFDO1X61H4RNQLE”
   
   This call retrieves sheep market prices from the Taiwan Ministry of Agriculture, filtered by time range and market. The response header is expected in JSON format.
   
   This data includes fields such as:
   - Transaction Date
   - Product Type
   - Crop Code
   - Market Name
   - Price Ranges (Upper, Middle, Lower, Average)
   - Transaction Volume
   
   3. Splitting Out Individual Records
   
   Once the dataset is received, a Split Out node processes the "Data" array returned in the API response. This is crucial, as the response is likely a nested array of transaction objects. Each object in the “Data” array is separated and passed through as a single item to the next node, allowing for structured insertion into a spreadsheet.
   
   4. Storing the Data in Google Sheets
   
   The final node, connected to Google Sheets via OAuth2, takes each individual record and appends it to a sheet titled “n8n爬蟲-農產品.” Specifically, the sheet used is “Sheet1” with the GID set to 0.
   
   The mapped fields added to the spreadsheet include:
   - TransDate
   - TcType
   - CropCode
   - CropName
   - MarketCode
   - MarketName
   - Upper_Price
   - Middle_Price
   - Lower_Price
   - Avg_Price
   - Trans_Quantity
   
   All of these are automatically mapped thanks to n8n’s intelligent data-matching capabilities.
   
   Benefits of This Workflow
   
   - No coding required: Perfect for non-developers who still need access to automated processes.
   - Time-saving: Automatically fetches data that would otherwise require manual downloads or website visits.
   - Customizable: Can easily be extended to cover more marketplaces, product types, or time ranges.
   - Scalable: Run it on a schedule using a Cron node, or integrate with email/slack alerts for dynamic reporting.
   
   Conclusion
   
   Using n8n’s visual builder and prebuilt integrations, you can automate crucial data flows like government dataset ingestion and reporting in just minutes. This workflow is a clear example of how open data and no-code platforms empower individuals and organizations to optimize their digital processes.
   
   Whether you’re a data scientist tracking commodity trends, a policymaker monitoring livestock prices, or a developer prototyping agri-tech solutions, this n8n workflow offers a robust template for feeding real-time data into the tools you already use — and all without writing a single line of code.
   
   Ready to take your data automation to the next level? Start experimenting with n8n today.
   
   — 
   
   Note: Ensure that your use of the API key complies with the Taiwan Ministry of Agriculture’s terms of service. For automated and scheduled usage, consider requesting appropriate API limits or secure credentials management.

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.