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:**  
   How to Automate SERP Analysis with AI Using n8n, SERPBear, and Baserow — No Coding Required
   
   **Meta Description:**  
   Learn how to automate SEO keyword tracking and AI-powered analysis using SERPBear, OpenRouter AI, and Baserow with a no-code n8n workflow. Get weekly insights on your domain’s performance with zero manual effort.
   
   **Keywords:**  
   n8n workflow, SEO automation, SERPBear, Baserow, OpenRouter, AI SEO analysis, no-code automation, keyword ranking tracker, SEO insights, Google SERP monitoring, llama model, OpenRouter AI, automate keyword reports
   
   ---
   
   # How to Automate SERP Analysis with AI Using n8n, SERPBear, and Baserow — No Coding Required
   
   Search engine rankings are one of the most trackable, measurable, and important indicators of your website’s SEO health. But keeping tabs manually on where your keywords stand can be time-consuming—even more so when you're trying to detect trends or uncover optimization opportunities.
   
   That’s where automation meets intelligence.
   
   In this guide, we’ll walk you through an automated workflow built in n8n, a powerful open-source automation platform. This workflow pulls your keyword ranking data from SERPBear, uses AI (via OpenRouter and Meta’s LLaMA 3.1 model) to analyze performance trends, and stores a summarized report in Baserow.
   
   Best of all? You don’t need to write a single line of code.
   
   ---
   
   ## What This Workflow Does
   
   The “SERPBear Analytics Template” enables you to:
   
   ✅ Pull current keyword ranking data from your SERPBear instance  
   ✅ Automatically analyze the trends—highlighting improvements, declines, and SEO opportunities  
   ✅ Use an AI model to generate actionable insights and recommendations  
   ✅ Store that analysis neatly in your Baserow database for ongoing SEO tracking
   
   All of this is either triggered manually or scheduled automatically (e.g., weekly).
   
   ---
   
   ## Step-by-Step Breakdown of the Workflow
   
   Let’s walk through how this n8n workflow functions in the background:
   
   ### 1. Trigger the Workflow
   
   The automation can be started in two ways:
   
   - Manually via a “Test Workflow” trigger within n8n for immediate testing/debugging  
   - Automatically on a timed schedule (e.g., every week) using the built-in Schedule Trigger node
   
   ### 2. Fetch SERPBear Keyword Data
   
   Once triggered, n8n makes an HTTP GET request to your SERPBear API endpoint (`/api/keyword`) with domain filtering applied. This retrieves the latest ranking data for your selected keywords.
   
   SERPBear is a lightweight and open-source alternative to paid SEO monitoring tools, making it a perfect choice for DIY automation.
   
   ### 3. Parse and Summarize the Data
   
   In this step, a JavaScript code node processes each keyword:
   
   - Evaluates current ranking position  
   - Computes average ranking across the past 7 days using SERPBear’s historical data  
   - Determines whether the keyword’s performance is improving, declining, or stable  
   - Creates a summary with metrics: keyword, position, trend, and URL
   
   This summary is then used to dynamically generate a prompt tailored for AI analysis.
   
   ### 4. Send Data to an AI Model for Insights
   
   Now it gets interesting.
   
   A request is sent to OpenRouter.ai, which acts as a gateway to large language models like Meta’s LLaMA 3.1. The prompt structured above is encoded and included as context, asking the model to return:
   
   - Key observations from the data  
   - Most improved keywords  
   - Keywords needing attention  
   - Suggested SEO actions for improvement
   
   Basically, your automated SEO strategist goes to work.
   
   ### 5. Store the Result in Baserow
   
   Finally, the AI-generated analysis is sent to your Baserow database. Baserow is an open-source no-code alternative to Airtable where you can create structured tables for storage.
   
   A new entry is added to your designated table with:
   
   - The date of extraction  
   - The AI-generated SEO summary  
   - The blog or domain (“rumjahn.com” in this example)
   
   Over time, this builds a repository of week-to-week performance reports.
   
   ---
   
   ## Benefits of Using This Workflow
   
   - ⏱️ Saves time by eliminating manual keyword audits  
   - 🧠 Leverages AI to create human-readable insights and SEO strategies  
   - 🚀 No coding required—just plug in your API keys and go  
   - 📊 Centralized data storage for easy trend analysis  
   - ✅ Open-source tools used throughout = completely free setup
   
   ---
   
   ## How to Set It Up
   
   1. Install and self-host n8n or use n8n.cloud  
   2. Plug in your SERPBear API credentials (Header Authorization)  
   3. Get an API key from OpenRouter.ai and configure it with “Bearer” header  
   4. Set up a table in Baserow with columns: Date, Note (for analysis), and Blog  
   5. Import the template into your n8n instance and connect credentials  
   6. Test manually or let it run automatically every week
   
   You'll receive a fresh batch of AI-enhanced SEO insights each week—output that would normally take hours to generate manually.
   
   ---
   
   ## Third-party APIs Used in This Workflow
   
   - 🌐 **SERPBear API** — Retrieves keyword ranking and historical data  
   - 🧠 **OpenRouter AI API** — Sends prompts to the Meta LLaMA 3.1 model for SEO analysis  
   - 📋 **Baserow API** — Stores the AI-generated reports in a structured table
   
   ---
   
   ## Final Thoughts
   
   SEO is fundamentally a data-driven discipline. But making sense of that data—and taking action based on it—is where most SaaS tools fall short or get expensive.
   
   This open-source, no-code automation with n8n brings together powerful yet affordable platforms to do just that: retrieve keyword performance data, analyze it through AI, and help you track how your site is really doing over time.
   
   All this is customizable, scalable, and replicable across multiple domains.
   
   If you'd like to try it yourself, check out the guide by the original creator at [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/).
   
   ---
   
   ⏳ Time to build: ~30 minutes  
   💸 Estimated cost: $0 (assuming use of free tiers)  
   🧠 AI model used: Meta LLaMA 3.1 via OpenRouter  
   📦 Data stored: Daily/weekly keyword trend summaries  
   
   This is automation done smart. Try it—your SEO strategy will thank you.

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.