Recently we've been asked to add more AI features to help users — especially in content writing and deep research — so they don't have to switch across multiple platforms for their SEO workflows. For the OPC (One-Person-Company) founders that RankEarly has been actively working with, a common ask is: don't break my vibe.
We could have built another AI writing tool. Instead, we decided to let you stay where you already work. Model vendors give you plenty of tokens. Why not put our work where those tokens can actually use them?
So we repackaged our core functionality as agent skills and exposed the underlying algorithms and data as RankEarly MCP tools. Yes, this basically means open-sourcing part of our business.
Three layers of access
For indie hackers who spend most of their day working with AI agents, here's what this gives you.
The first layer is UI. You can manage your data, save your analyses, arrange them into a content calendar, prioritize content ideas, and view everything more effectively. The dashboard isn't going anywhere.
The second layer is agent skills (and Claude plugins in the future). This is our SEO expertise layer. Our skills encapsulate proven SEO practices. They treat your published web pages as valuable assets and make sure you only spend time on the decisions that actually matter. Your AI agent handles the rest.
For example, our topic research skill builds a full pillar-cluster content plan from a single topic idea. The SERP gap analysis skill tells you whether a keyword is winnable and where the ranking pages are weak. More skills are coming — you can run any of them from your terminal.
Here's the /blog-title-generator skill in action — generating title options for "keyword expansion" directly from Claude Code.
The third layer is MCP. Parallel data analysis, keyword expansion algorithms, real-time SERP data, searcher behavior signals — we put these under RankEarly MCP. Any MCP-compatible client (Claude Code, Codex, OpenClaw, your personal agents) can call them directly.
This layer exists because some work shouldn't happen inside an LLM's context window. When an agent has to fetch raw data, process it, and then get back to your actual task, the context window fills up with stuff that has nothing to do with the goal. Performance degrades, hallucinations creep in. MCP tools handle the data processing on our side and return structured results, so your agent's context stays focused on what you asked it to do.
Getting started
Add RankEarly MCP to your agent's config. It takes about two minutes — see the docs for setup instructions per client.
Connection uses OAuth — your agent will prompt you to authorize RankEarly on first use. If you're new, the free tier covers enough calls to see if this fits how you work.
RankEarly works with indie hackers, solo entrepreneurs, and one-person companies who lack SEO expertise — people who've spent months publishing but still see zero clicks and zero MRR. We help them get to thousands of organic clicks per month. Now you can do that without leaving your editor.