How to Automate Content Creation with InfraNodus MCP Server and Claude Code / Cursor AI

You can use the InfraNodus MCP server with LLM tools like Claude Code or Cursor AI to automate content creation while also ensuring that it sounds human and has your personal touch. 

Unlike other approaches where you'd get generic content that sounds AI-generated, this content automation workflow ensures that your writing retains your style and original ideas. The main difference here is that it uses a combination of meticulous adjusted context, MCP servers, skills, and reasoning graphs: 

• The context provides the original content to draw from, 
• MCP servers root the content in existing search patterns and optimize them for search engines and LLMs, 
• the skills make sure that you retain your language and humanize the content,

• the reasoning graphs ensure coherence and avoid hallucinations

   

Content Creation Tool Stack

Most people who want to automate content creation use specialized AI tools or ChatGPT. However, we recommend to use IDE coding environment such as Cursor AI together with Claude Code. The reason is that these tools are made for software development, which is the most lucrative and best-researched AI case so far. So the quality of their AI agents are much higher than any other tool can provide. 

Cursor AI also has Obsidian-like markdown viewer and editor, so you can review your content and make edits. Claude Code can be used inside Cursor AI, through the terminal, or its own standalone desktop app. You can use any of them for context engineering.

Then you'll also need the InfraNodus MCP server. It provides advanced text analysis capabilities not available in LLMs. It can optimize a text's structure to make it more coherent and develop ideas in text to make sure that it has novel aspects and no content gaps. Additionally, the InfraNodus MCP server has access to search intent and search results data, so you can use it to get the data on what people search for (and what they find) and better understand what would be in demand. 

You can also use Skills — available at https://github.com/infranodus/skills — that you can install into your Claude Code or Cursor to make LLMs write in your style and to improve various SEO workflows.

Finally, the reasoning graphs available in InfraNodus can help you ensure that your content has an original perspective, follows a certain logic, and is coherent at its core. 

Step 1: Context Engineering

To create good content, you need to define your context. The easiest way to do that is to copy all the notes, files, or raw data that you want to use into a separate project folder and run your AI from there. 

For instance, it could be a folder with markdown files (such as your Obsidian vault) or a folder with the raw files you use for your website. 

If you'd like more advanced setup, you can use something like LLM Wiki — an automated content processing, ingestion, and interpretation system that you can run in your Claude Code or Cursor AI.

Use the context you have and ask the AI what would be the most interesting topic to write about based on the content it has. If you have an InfraNodus MCP server attached, you can also ask it to analyze the current contet gaps and identify the ideas that could bridge them in new interesting way. This way you'd develop your ideas while also touching upon the topical clusters that are relevant for this particular context.

Step 2: SEO Optimization

Before you start writing, you need to define the subject and study the market. Your idea might be too narrow (so it won't be found) or too broad (it it'll get lost). You need to find the sweet spot or a gap where you cover a topic that has enough search intent (so people actually look for it) but where you also contribute something original so that search engines and LLMs surface your content in search results. 

In order to perform SEO analysis you can use the InfraNodus MCP server SEO tool. Just give it a topic and ask it to run search intent and search results analysis (or a full SEO report). InfraNodus will then deliver its report and suggest how you can modify your topic for it to have a broader appeal but to avoid competing in an over-saturated market.

Additionally, a nice trick to use here is to analyze the search queries where you already get clicks and views in the search results using the Google Search Console. You want to target the queries where you already rank on the first page but get only a few clicks (or none). Moving up 2-3 positions can make a huge difference and is not an impossible task because Google already ranks your content for these queries. 

Once you define the topic, you can move to the next step and create content for it.

Step 3: Content Generation

At this stage, you already defined a topic that's also optimal for SEO based on the context you have. Now you can give your AI (via Cursor Agent or Claude Code) an instruction to write the content based on this topic. 

In this process, you can use additional skills you have and ask the AI to use the /humanizer skill to make the content sound more human. If you have a skill that details your personal writing style, you can add that skill description to the task as well.

Step 4: Reiterate — Add Important Nuance

Once you have the first version generated, run it through the SEO tools again and also ask the AI to see if there's anything interesting in the context that relates to the article but is missing from it. Ask the InfraNodus tool to identify structural gaps and also to use its transcend mode to see if the content can be developed further. 

This step is an important one because that's where you can add original ideas and ensure that the content will also be in demand for your potential audience. 

At this step, you can also use the InfraNodus reasoning graphs to verify the logic in the content generated and avoid hallucinations. You can also add an external expert to see this content from a different perspective and ensure that it has all the details it needs to be at the top 1%.

Step 5: Use the Graph to Review the Text

At this last optional step, you can use the graph extension to view your text and see if you cover all the important topics and bridge all the gaps. The graph is like a dashboard for meaning in your text. You can use it through Obsidian via the InfraNodus Obsidian plugin or inside Cursor AI via the InfraNodus VSCode Extension.