This article provides a complete, practical walkthrough of the Wait Limit Import 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:  
   Automate Webpage Content Extraction with Markdown and Link Parsing using n8n and Firecrawl.dev
   
   Meta Description:  
   Learn how to build a no-code workflow in n8n to convert website HTML into structured Markdown and extract links using the Firecrawl.dev API. Batch process URLs, handle API limits, and export to your own data source—all in minutes.
   
   Keywords:  
   n8n, no-code automation, Firecrawl.dev, webpage scraping, markdown conversion, link extraction, API integration, data workflow, Airtable integration, content transformation, LLM prep, structured data
   
   Third-Party APIs Used:
   
   - Firecrawl.dev API (https://firecrawl.dev)
   
   Article:
   
   Automating Webpage Markdown Conversion and Link Extraction in n8n with Firecrawl.dev
   
   In today’s AI-first landscape, structured and clean web content is critical for analysis, large language model (LLM) processing, and downstream automations. Manually scraping and cleaning content from websites is inefficient and error-prone. Luckily, with n8n—a powerful no-code workflow automation platform—and Firecrawl.dev’s API, you can build a self-contained workflow to scrape web pages, convert them to Markdown, extract all the embedded links, and export the data wherever needed.
   
   In this article, we walk through a complete n8n workflow that automates HTML-to-Markdown conversion and hyperlink extraction in a scalable, API-friendly, and customizable way.
   
   🧠 What This Workflow Does  
   This workflow solves the common challenge of preparing website content for further processing. It:
   
   - Accepts a batch of webpage URLs
   - Sends them to Firecrawl.dev's /scrape endpoint
   - Retrieves the clean Markdown, metadata (title and description), and internal/external links
   - Handles rate-limiting and batching to prevent server overloads
   - Outputs the extracted data into your preferred database or platform
   
   Perfect for researchers, marketers, and developers needing scalable content processing for hundreds or thousands of web pages.
   
   ⚙️ How It Works – A Step-by-Step Breakdown
   
   1. Manual Trigger Starts the Automation  
   Using an n8n Manual Trigger node, users initiate the workflow by clicking ‘Execute Workflow’ within the UI panel. This is useful for testing and validation of batch runs.
   
   2. URL Input Source  
   The workflow demo includes a node named “Example fields from data source” which mimics a typical input—an array of URLs under the field “Page”. For production use, connect your actual database of URLs (e.g., Airtable, MySQL, Google Sheets). Just ensure each URL is in a field labeled "Page".
   
   3. Preprocessing: Split and Limit  
   - The array of URLs is broken into individual items (Split Out node).
   - A ‘Limit’ node constrains the flow to a maximum of 40 URLs at once to avoid memory issues on servers with limited resources.
   - These are further divided into batches of 10, using n8n’s SplitInBatches node, which balances performance while staying within API rate limits.
   
   4. Respect Firecrawl.dev’s API Requirements  
   A custom HttpRequest node makes POST requests to Firecrawl.dev’s scrape endpoint, structured as:
   
   POST https://api.firecrawl.dev/v1/scrape  
   Headers:
   - Content-Type: application/json  
   - Authorization: Bearer YOUR_API_KEY
   
   Payload:
   {
     "url": "https://example.com",
     "formats": ["markdown", "links"]
   }
   
   The workflow is configured to:
   - Automatically retry failed requests
   - Introduce a deliberate 45-second delay between batches using the Wait node, in accordance with the API’s 10 requests-per-minute limit
   
   5. Extract and Format Returned Content  
   After receiving the JSON response, a Set node maps the desired fields:
   - title = metadata.title  
   - description = metadata.description  
   - content = parsed markdown  
   - links = extracted URLs
   
   6. Output to Your Database or App  
   Finally, the “Connect to your own data source” node marks where you configure your destination. Whether you use PostgreSQL, Airtable, Notion, or Google Sheets, n8n’s native integrations let you export the cleaned content wherever it’s used next.
   
   📌 Configuration Requirements  
   To get started:
   
   - Sign up for Firecrawl.dev and generate your API token
   - Add it to the Header Authorization field in the HttpRequest node
   - Connect your own URL source in lieu of the “Example fields from data source” mock
   - Adjust batch size and wait time if needed, based on your system capabilities and Firecrawl’s API limits
   - Add an output node after the final data transformation to store results in your database or data warehouse
   
   📈 Why This Matters  
   By turning web pages into clean, formatted Markdown containing only readable text and useful links, this workflow saves hours of manual scraping and editing. Whether you're:
   - Building AI training datasets
   - Analyzing site content
   - Monitoring site changes
   - Creating a link index for SEO
   
   …this automation is a robust and flexible foundation.
   
   🔧 Extend It Further  
   - Add multi-threaded branching for concurrent timelines
   - Include metadata capture like HTTP response time
   - Incorporate deduplication or change detection for repeat scans
   - Feed the data into AI summarization through OpenAI or Claude API (add via another n8n node)
   
   ✅ Final Thoughts  
   This low-code automation gives you complete control over extracting, formatting, and exporting structured content from any accessible webpage. With n8n and Firecrawl.dev working together, you can transform content scraping from a manual task into a repeatable, scalable asset for your workflows.
   
   Made by Simon at automake.io – bringing everyday automation within reach for creators and teams.
   
   —
   
   Get started with your own scrape-to-markdown pipeline in minutes—no coding skills needed. Let your data speak Markdown.
   
   For more info:
   - Firecrawl.dev API Documentation: https://docs.firecrawl.dev
   - n8n automation platform: https://n8n.io
   - Built by @simonswiss – https://www.automake.io

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.