How I Use AI to Write Blog Posts
2026-04-02
mcpdjangoclaude
2026-04-02
I like writing about software development but I rarely do it. The problem was never a lack of ideas. I have plenty of opinions about testing, framework choices, and how to build things. The problem was the time it took to go from "I want to write about X" to a published post. Sitting down, drafting, editing, formatting, and finally getting the thing into my blog's CMS felt like a side project on top of my actual side projects.
So I decided to treat it like any other engineering problem: find where the friction is and remove it.
I needed 3 things to make this work: a way to create posts programmatically in my blog, a bridge between Claude and that API, and a way to teach Claude how I write and what I care about.
My blog runs on Django. Until recently, the only way to create a post was through the Django admin. That's fine for manual writing, but it doesn't connect to anything else.
I added a simple API endpoint that accepts a POST request with the fields I need for a blog post: title, slug, meta description, content in Markdown, and tags. The post gets created as a draft so nothing goes live without my review.
You can see the pull request here. It's nothing fancy. A straightforward DRF endpoint with token authentication. The kind of thing Django makes easy and boring in the best way.
MCP (Model Context Protocol) is a standard that lets AI assistants like Claude interact with external tools and services. Instead of copying text from a chat window and pasting it into a form, Claude can call my blog's API directly.
I built a small MCP server that exposes my blog's POST endpoint as a tool Claude can use. The server runs locally and the configuration looks like this:
{
"mcpServers": {
"blog": {
"command": "uv",
"args": ["run", "server.py"],
"cwd": "/absolute/path/to/blog-mcp"
}
}
}
With this in place, I can ask Claude to create a draft and it sends the post data directly to my Django backend. No copy-pasting, no context switching.
This was the most interesting part. Claude is good at generating text, but generic AI-written content reads like generic AI-written content. I wanted posts that reflect my perspective, my background, and my opinions.
Claude Skills are instruction files that teach Claude specific workflows and preferences. I created one that captures how I think about software development: my experience with Django and TypeScript, my appreciation for simplicity over complexity, my focus on testability, and the way I prefer to explain things without hiding behind buzzwords.
The Skill also defines the output format so every post comes out with the exact fields my API expects. No reformatting needed.
Writing a post now looks like this:
I start with an idea. Maybe something I ran into at work, a pattern I found useful, or a topic I have a strong opinion about. I open Claude and describe what I want to write about, the key points I want to cover, and any specific angle I want to take.
Claude uses the Skill to generate a complete draft that matches my style and structure preferences. I read through it, adjust whatever needs adjusting, and when I'm happy with it I ask Claude to push the draft to my blog via the MCP server.
The post lands in my Django admin as a draft. I do a final review there, maybe tweak a sentence or two, and hit publish.
The whole process takes a fraction of what it used to take. More importantly, the friction that stopped me from writing is gone. I no longer need a free afternoon to produce a post. I need ten minutes and a clear idea.
Most of the words in my posts are generated by Claude. I want to be transparent about that. But here's what matters to me: every post starts with my idea, my perspective, and my direction. The Skill I built encodes my opinions and my way of explaining things. I review and edit everything before it goes live.
The goal was never to remove myself from the process. It was to remove the parts that slowed me down so I could focus on the part I actually enjoy: figuring out what's worth saying.