Create AI-powered SEO audit reports with DataForSEO and Claude

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Automated SEO Intelligence Platform with DataForSEO and Claude Transform any company website into a detailed SEO audit report in minutes! This workflow combines real time web scraping, comprehensiv...

Best for

Market Research automation workflows
AI RAG automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.webhook, n8n-nodes-base.httprequest, n8n-nodes-base.aggregate, n8n-nodes-base.wait, n8n-nodes-base.set, n8n-nodes-pdfco.pdfco api, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.gmail

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Harsh Agrawal.

Original n8n.io source

1.1 Workflow description

Title: Create AI-powered SEO audit reports with DataForSEO and Claude
Workflow name: Create AI-powered SEO audit reports with DataForSEO and Claude

Automated SEO Intelligence Platform with DataForSEO and Claude

Transform any company website into a detailed SEO audit report in minutes! This workflow combines real-time web scraping, comprehensive SEO data analysis, and advanced AI reasoning to deliver client-ready reports automatically.

Perfect for digital agencies scaling their audit services, freelance SEO consultants automating research, or SaaS teams analyzing competitor strategies before sales calls.

The Process

Discovery Phase: Input a company name and website URL to kick things off. The system begins with website content extraction.

Intelligence Gathering: A dedicated scraper sub-workflow extracts all website content and converts it to structured markdown.

Strategic Analysis: LLMs process the scraped content to understand the business model, target market, and competitive positioning. They generate business research insights and product strategy recommendations tailored to that specific company. Once this analysis completes, DataForSEO API then pulls technical metrics, backlink profiles, keyword rankings, and site health indicators.

Report Assembly: All findings flow into a master report generator that structures the data into sections covering technical SEO, content strategy, competitive landscape, and actionable next steps. Custom branded cover and closing pages are added.

Delivery: The HTML report converts to PDF format and emails directly to your recipient - no manual intervention needed.

Setup Steps

Add API credentials: OpenRouter (for AI), DataForSEO (for scraping/SEO data), and PDFco (for PDF generation)
Configure email sending through your preferred service (Gmail, SendGrid, etc.)
Optional: Upload custom first/last page PDFs for white-label branding
Test with your own website first to see the magic happen!

Customize It

Adjust analysis depth: Modify the AI prompts to focus on specific SEO aspects (local SEO, e-commerce, B2B SaaS, etc.)

Change report style: Edit the HTML template in the Sample_Code node for different formatting

Add integrations: Connect to your CRM to automatically trigger reports when leads enter your pipeline

Scale it up: Process multiple URLs in batch by feeding a Google Sheet of prospects

What You'll Need

OpenRouter account (Claude Opus 4.1 recommended for best insights)
DataForSEO subscription (handles both scraping and SEO metrics)
PDFco account (converts your reports to professional PDFs)
Email service credentials configured in n8n

Need Help?

Connect with me on LinkedIn if you have any doubt

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Webhook1

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2

Block 2 - Website SEO Data1

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 3 - Aggregate

Type / Role: n8n-nodes-base.aggregate - aggregate
Config choices: Version 1

Block 4 - Wait5

Type / Role: n8n-nodes-base.wait - wait
Config choices: Version 1.1

Block 5 - PDF_First_Page

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 6 - PDF_Last_Page1

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 7 - PDFco Api

Type / Role: n8n-nodes-pdfco.PDFco Api - PDFco Api
Config choices: Version 1

Block 8 - Structured Output Parser1

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.2

Block 9 - Get_Pdf_File

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 10 - Send a message

Type / Role: n8n-nodes-base.gmail - gmail
Config choices: Version 2.1

Block 11 - Report_Generator_Agent

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.7

Block 12 - Crawler Request

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 13 - Sample_Code

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 14 - OpenRouter Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 15 - If https?

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 16 - Markdown1

Type / Role: n8n-nodes-base.markdown - markdown
Config choices: Version 1

Block 17 - Edit Fields29

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 18 - Edit Fields30

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 19 - Edit Fields31

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 20 - Edit Fields34

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 21 - Execute Workflow

Type / Role: n8n-nodes-base.executeWorkflow - executeWorkflow
Config choices: Version 1.2

Block 22 - DATA FOR SEO

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 23 - DATA FOR SEO1

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 24 - When Executed by Another Workflow

Type / Role: n8n-nodes-base.executeWorkflowTrigger - executeWorkflowTrigger
Config choices: Version 1.1

Showing the first 24 of 35 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Create AI-powered SEO audit reports with DataForSEO and Claude
Complexity	advanced
Nodes	35
Categories	Market Research, AI RAG
Author	Harsh Agrawal
Published	12 Oct 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/9502/9502.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Market Research workflows AI RAG workflows

Frequently asked questions

What does Create AI-powered SEO audit reports with DataForSEO and Claude do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI RAG use case.

Harsh Agrawal

1 workflow

Nodes

n8n-nodes-base.webhook n8n-nodes-base.httprequest n8n-nodes-base.aggregate n8n-nodes-base.wait n8n-nodes-base.set n8n-nodes-pdfco.pdfco api @n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.gmail

Complexity

advanced

Published 12 Oct 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/9502/9502.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Answer BigQuery questions in Microsoft Teams with Claude 3.5 dual agents

## Quick overview Turn Microsoft Teams into a natural language BI tool. This dual-agent Claude workflow intelligently classifies user questions, generates safe BigQuery SQL, executes the query, and returns a plain-English summary alongside a data preview directly to your Teams channel. ## How it works 1. The workflow listens for new messages in a designated Microsoft Teams channel or chat. 2. It checks a 24-hour static data cache for your BigQuery schema. If the cache is missing or expired, it automatically fetches the latest INFORMATION_SCHEMA metadata. 3. A main Claude 3.5 Sonnet agent classifies the user's intent (analytical, conversational, or unsafe) and identifies the relevant database tables. 4. If the intent is analytical, a specialized Claude SQL sub-agent generates a read-only SELECT query tailored exactly to your schema. 5. The workflow executes the query against BigQuery (safely constrained to a maximum of 100 rows). 6. A final Claude agent translates the raw query results into a concise, plain-English summary. 7. The answer is posted back to Teams as an Adaptive Card, complete with a formatted data preview and the generated SQL code. 8. Non-analytical questions or pipeline errors are intelligently routed to receive standard conversational replies in Teams. ## Setup 1. CRITICAL SECURITY: Restrict your Google Cloud Service Account IAM roles to BigQuery Data Viewer and BigQuery Job User ONLY. Do not use a highly privileged account. 2. Configure your Microsoft Teams trigger and posting credentials, specifying the target team and channel for the bot to operate in. 3. Configure your Google BigQuery credentials to allow reading metadata and executing queries. 4. Configure your Anthropic credentials for the three Claude LangChain nodes. 5. Update the "Configure Variables" node with your specific GCP Project ID and BigQuery Dataset ID. ## Requirements - A Google Cloud project with BigQuery enabled and existing structured datasets. - An Anthropic API key with access to the Claude 3.5 Sonnet model. - Microsoft Teams administrator access to authorize the n8n integration. ## Customization - Distributed Environments: If you are running n8n with multiple worker nodes (Queue Mode), you must swap the $getWorkflowStaticData() schema cache logic to read/write from a dedicated Key-Value store (like Redis or Supabase) to ensure state synchronization. - UI Layout: Modify the Create Teams Adaptive Card node to add corporate branding, custom colors, or alter the FactSet data preview structure. ## Additional info This architecture features built-in pipeline protections, including strict 40,000-character payload limits to prevent LLM context window blowouts, and fallback handling for "zero-row" query results to ensure users are never left without a response.

View

Evaluate LinkedIn profiles with Apify and Groq Llama chat model

## Quick overview This workflow collects a LinkedIn profile URL via an n8n form, scrapes the public profile data using the Apify LinkedIn Profile Scraper actor, analyzes the results with a Groq-hosted Llama model, and displays an HTML-formatted evaluation back to the user. ## How it works 1. Receives a LinkedIn Profile URL when a user submits the n8n form. 2. Prepares the LinkedIn URL along with the Apify API token and Groq API key used for downstream requests. 3. Sends the profile URL to the Apify `harvestapi/linkedin-profile-scraper` actor and retrieves the scraped dataset items. 4. Passes the scraped profile JSON to a Groq chat model via an LLM chain to generate an HTML evaluation with a score and recommendations. 5. Displays the generated HTML evaluation to the user as the form completion message. ## Setup 1. Add a valid Apify API token and ensure the Apify actor endpoint (`harvestapi/linkedin-profile-scraper`) is accessible for your account. 2. Add Groq API credentials in n8n and confirm the selected model (meta-llama/llama-4-scout-17b-16e-instruct) is available to your Groq account. 3. Replace the placeholder API key values in the workflow (or move them to n8n credentials/environment variables) and verify the form field label matches `LinkedIn Profile URL`.

View

Validate startup ideas with Google Gemini, Groq, and Gmail

## Quick overview This workflow collects a startup idea via an n8n form, uses Google Gemini to generate a SWOT-style analysis, assigns a viability score, uses Groq to turn the results into a structured validation report, and emails the final report through Gmail. ## How it works 1. Receives a startup idea, industry, and target audience from an n8n Form trigger. 2. Sends the submission to Google Gemini to generate a professional analysis covering the problem, business model, and SWOT factors. 3. Generates a startup viability score (currently a random value from 80–100) and packages it with the Gemini analysis. 4. Sends the score and analysis to Groq (Llama 3.3 70B) to compile a full validation report with an executive summary, market potential, recommendations, and final verdict. 5. Emails the generated validation report to the configured recipient using Gmail. ## Setup 1. Add credentials for Google Gemini (PaLM) API, Groq API, and a Gmail OAuth2 connection. 2. Replace the placeholder recipient address in the Gmail step ("[email protected]") with your target email address before activating the workflow. 3. Publish the n8n form, then share the form URL with the users who should submit their startup ideas for validation.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

Create AI-powered SEO audit reports with DataForSEO and Claude

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Automated SEO Intelligence Platform with DataForSEO and Claude

The Process

Setup Steps

Customize It

What You'll Need

Need Help?

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Webhook1

Block 2 - Website SEO Data1

Block 3 - Aggregate

Block 4 - Wait5

Block 5 - PDF_First_Page

Block 6 - PDF_Last_Page1

Block 7 - PDFco Api

Block 8 - Structured Output Parser1

Block 9 - Get_Pdf_File

Block 10 - Send a message

Block 11 - Report_Generator_Agent

Block 12 - Crawler Request

Block 13 - Sample_Code

Block 14 - OpenRouter Chat Model

Block 15 - If https?

Block 16 - Markdown1

Block 17 - Edit Fields29

Block 18 - Edit Fields30

Block 19 - Edit Fields31

Block 20 - Edit Fields34

Block 21 - Execute Workflow

Block 22 - DATA FOR SEO

Block 23 - DATA FOR SEO1

Block 24 - When Executed by Another Workflow

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions