This article provides a complete, practical walkthrough of the Code Schedule 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:  
   Automate SEO Reporting with AI Analysis Using n8n, SERPBear, and OpenRouter
   
   Meta Description:  
   Learn how to automate SEO keyword tracking, analysis, and reporting using n8n, SERPBear, OpenRouter’s LLM, and Baserow—with no coding skills required.
   
   Keywords:  
   n8n workflow, SEO automation, SERPBear, keyword tracking, OpenRouter AI, LLM analysis, Baserow, automate SEO reports, no-code SEO, performance trend tracking
   
   Third-Party APIs Used in the Workflow:
   
   1. SERPBear API (Keyword position data)
   2. OpenRouter API (Meta LLaMA 3.1 model for AI-driven analysis)
   3. Baserow API (Storing summarized analysis)
   
   —
   
   Article:
   
   Automate SEO Reporting with AI Analysis Using n8n, SERPBear, and OpenRouter
   
   Staying ahead in the SEO game requires regular data observation and thoughtful analysis, especially when tracking keyword performance. But manually reviewing keyword rankings and compiling weekly reports can be a time-consuming task—especially for non-technical marketers running solo or small teams.
   
   If you’ve ever wished there were a smarter way to review SEO data and get actionable recommendations without diving into spreadsheets or hiring an SEO analyst, here’s good news: it’s possible to automate this process using free and no-code-friendly tools.
   
   This article walks you through a powerful, easy-to-configure workflow built in n8n—an open-source workflow automation tool—that connects SERPBear, OpenRouter’s AI model (Meta LLaMA 3.1), and Baserow. The result? A fully autonomous system that pulls your keyword performance data weekly, analyzes trends using AI, and stores a report in a readable format—all without you lifting a finger.
   
   Let’s break down each step of this workflow to understand how it works and how you can implement it yourself.
   
   Step 1: Trigger the Workflow on a Schedule
   
   The n8n workflow begins with a Schedule Trigger set to run weekly. This ensures that your SEO performance gets reviewed consistently without the need for manual initiation.
   
   You can also test the flow manually using an additional trigger node configured for test runs, allowing you to validate everything before going live.
   
   Step 2: Pull Keyword Data from SERPBear
   
   The workflow then fetches current keyword ranking data from your SERPBear instance using a simple HTTP request. SERPBear is an open-source keyword tracking tool that offers a REST API for querying a website’s keyword rankings.
   
   This step uses HTTP Header Authentication to securely connect to the API and pulls data specific to your domain (in this case, rumjahn.com).
   
   Step 3: Parse and Summarize Keyword Trends Using Code
   
   Once the raw data is retrieved, a code node processes and transforms it into a meaningful summary. This includes:
   
   - Identifying each keyword’s current rank
   - Calculating the 7-day average rank
   - Highlighting trend status (improving, declining, or stable)
   - Capturing the URL that's ranking (if available)
   
   The result is a structured text prompt automatically formatted for an AI to understand.
   
   Step 4: Send the Data to an AI for Analysis
   
   Next, this prompt is sent to the OpenRouter API—which harnesses the Meta LLaMA 3.1 70B Instruct language model. The model acts like a seasoned SEO consultant and:
   
   - Summarizes key observations
   - Highlights keywords showing the most improvement
   - Identifies keywords needing attention
   - Provides specific recommendations to improve rankings
   
   This integration relies on a secure HTTP request using bearer token authentication (Header Auth) to maintain privacy and handle API access.
   
   Step 5: Save the AI Summary to a Baserow Table
   
   Once the AI delivers its insights, the workflow saves the results into a Baserow database—a user-friendly, Airtable-like platform ideal for structured data and team collaboration.
   
   The saved entry includes the analysis date, the AI-generated report, and a project label (“Rumjahn” in this case). Over time, this builds up a historical log of weekly SEO audits, neatly stored and accessible in one place.
   
   Bonus: Fully Customizable and Expandable
   
   This workflow is just a starting point. You can easily enhance it by:
   
   - Sending weekly summaries via email
   - Triggering Slack notifications with links to the Baserow report
   - Comparing week-over-week performance metrics visually
   
   Thanks to the modular nature of n8n, everything is configurable—even for non-coders. Sticky notes included in the workflow also provide useful instructions guiding you on setting up credentials and preparing Baserow tables.
   
   Why This Workflow Matters
   
   This entire setup can be accomplished using free tools, providing a zero-cost solution to a traditionally time-intensive problem. You no longer need to reinterpret raw ranking data or pull reports manually. AI takes the heavy lifting, leaving you with meaningful insights and time to act on them.
   
   This is especially beneficial for:
   
   - Solo bloggers and creators managing SEO on their own
   - Small agencies looking to streamline SEO reporting for clients
   - Marketing teams that want automation without technical investment
   
   Conclusion
   
   By combining SERP tracking, AI-powered summarization, and no-code automation, you can now maintain an informed, up-to-date SEO strategy—with minimal maintenance. This workflow, powered by n8n, OpenRouter, and Baserow, exemplifies the real-world impact of automation and AI when set up thoughtfully.
   
   If you’re ready to give your SEO reporting a smart, efficient upgrade, try building this workflow yourself. For a complete guide on how to configure these nodes in n8n, check out the tutorial on [rumjahn.com](https://rumjahn.com/how-to-create-an-a-i-agent-to-analyze-serpbear-keyword-rankings-using-n8n-for-free-without-any-coding-skills-required/).
   
   Say goodbye to manual reports—let the bots do the hard work.
   
   —  
   Tools & APIs Used:
   
   - SERPBear API (Keyword tracking engine)
   - OpenRouter API (Meta LLaMA 3.1 AI for SEO insights)
   - Baserow API (Database for storing reports)
   - n8n (Orchestration and workflow automation)

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.