2.4k stars!SEO Machine: Build Your AI Content Factory with Claude Code!

SEO Machine: Build Your AI Content Factory with Claude Code

An open-source SEO writing workspace with 2,300+ GitHub stars — what problem does it actually solve?


01 What Problem Does It Solve?

Anyone who has done content marketing knows the pain: a single SEO long-form article that ranks on Google’s first page requires a massive amount of work. Topic selection, competitor research, keyword clustering, writing, internal linking, meta tags — each step demands time, and demands someone who understands writing, SEO, and data analysis simultaneously.

The biggest bottleneck for content teams isn’t the ability to write. It’s that producing one high-quality, high-ranking article requires coordinating too many roles, too many tools, and too many workflows.

SEO Machine was built by Craig Hewitt, founder of the SaaS podcast-hosting platform Castos. His problem was painfully practical: he needed to produce a steady stream of articles that drove organic search traffic, but building a dedicated content team was expensive and outsourcing quality was unpredictable.

So he built this workspace on top of Claude Code — automating the entire content production pipeline. Not just “let AI write the article,” but a complete Research → Write → Analyze → Optimize → Publish AI collaboration system.


02 What Is SEO Machine?

In short, SEO Machine is a Claude Code workspace template built specifically for content marketing. It’s open-source, free to use, and any team can fork it and adapt it to their needs.

Its core is made up of three layers:

ModuleScaleWhat It Does
⚡ Workflow Commands20+ slash commandsTrigger full research-to-publish pipelines with a single command
🤖 Specialist Agents10 dedicated agentsSEO optimizer, keyword mapper, link builder, headline generator, and more
🧠 Marketing Skills26 built-in skillsCopywriting, CRO, A/B testing, email sequences, pricing strategy
📊 Data IntegrationGA4 · GSC · DataForSEOData-driven content decisions backed by real analytics

The project’s file structure is also thoughtfully designed:

  • research/ — research materials and briefs
  • drafts/ — article drafts in progress
  • published/ — archived published content
  • context/ — brand voice, target keywords, competitor intel config templates

The AI learns your brand’s tone and requirements by reading these files. The result is output that actually fits your business — not generic, one-size-fits-all content.

⭐ Project: https://github.com/TheCraigHewitt/seomachine


03 How to Use It: Complete Setup Guide

Getting started with SEO Machine breaks down into two phases: initial configuration and daily use.

Step 1: Clone the repo & install Claude Code

Fork the project to your GitHub account and clone it locally. Make sure you have Claude Code installed — Anthropic’s official CLI tool.

Step 2: Fill in the context files — this is the most important step

Inside the context/ directory, populate your brand voice (brand-voice.md), target keywords (target-keywords.md), and competitor info (competitors.md). The more specific you are, the more on-brand the AI output will be.

Step 3: Open the project with claude-code .

Navigate into the project directory and run claude-code . to open the workspace. Claude will load all your config files and context automatically.

Step 4: Use slash commands to start producing content

Use the built-in custom commands to kick off your content workflows.

Core Commands Quick Reference:

CommandWhat It Does
/research [topic]Research a topic and generate a brief with competitor analysis and keyword suggestions
/write [topic]Write a full SEO long-form draft based on the research brief
/analyze-existing [url]Audit an existing article and generate a 0–100 SEO score report with specific fixes
/rewrite [topic]Rewrite an existing article incorporating the latest data and SEO best practices
/optimize [file]Final polish pass: keyword density, readability score, internal link suggestions
/performance-reviewPull GA4 + Search Console data and surface content that needs attention
/prioritiesData-backed list of the highest-ROI content tasks to tackle right now

A typical end-to-end content production run:

# Step 1: Research the topic
/research  how to choose a podcast hosting platform

# Step 2: Write the article from the research brief
/write  how to choose a podcast hosting platform

# Step 3: Final optimization pass
/optimize  drafts/how-to-choose-a-podcast-hosting-platform.md

# Step 4: Publish
/publish-draft  drafts/how-to-choose-a-podcast-hosting-platform.md

Beyond blog posts, SEO Machine also ships a complete landing page workflow — /landing-research, /landing-write, /landing-audit — enabling continuous AI-assisted conversion rate optimization.


04 Summary: Who Is This For?

The value of SEO Machine isn’t “using AI to write articles” — anyone can do that. Its real value is packaging an entire SEO content team’s workflow into a locally-runnable, on-demand AI collaboration system.

✅ It’s a great fit for:

  • SaaS products and indie makers who need SEO content output but have limited team capacity
  • Content entrepreneurs who want to shift from occasional publishing to a repeatable production pipeline
  • Growth teams looking to get started with AI tooling but not sure where to begin

❌ It’s not the right fit for:

  • Total SEO beginners with no foundational knowledge (you need to be able to evaluate the output quality)
  • Users who aren’t comfortable with basic command-line operations (running Claude Code is required)

The project is battle-tested on a real SaaS business (Castos), and the examples/ directory includes complete real-world case studies to reference. 2,300+ stars and 386 forks signal that a meaningful number of practitioners have already validated it in production.


Adapted from the open-source project at https://github.com/TheCraigHewitt/seomachine

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