AI SEO agents: what they do, and whether to use one or build your own

Should you use an AI SEO agent, or build your own? Short answer: use Frase’s agent if you want the work done for you, and build your own on Frase’s MCP if you want to design the workflow yourself.

Personally I do both most days. I use Frase directly inside the app, and I also run my own agents in Claude, connected to Frase through MCP. Some of it comes down to personal preference and the work you’re already doing, and some comes down to what your team looks like and differing levels of comfort with different set-ups. This post covers what an AI SEO agent actually is, what it does, and how to decide which route suits your team.

What is an AI SEO agent?

An AI SEO agent is a system that reasons, plans and uses tools to complete multi-step search tasks end to end: pulling SERP data, drafting against it, scoring the output and acting on performance signals, without a human re-prompting it at each stage.

The difference from the tools you already use is who carries out each step.

What makes a workflow agentic is that the handoffs between tasks disappear. Our post on AI agents for SEO goes deeper into agentic workflows.

What an AI SEO agent actually does

It starts with research. The agent pulls what’s ranking for a query, works out the subtopics and questions those pages share, and flags what they cover that you don’t. Then it builds the brief from those current results rather than a static template, so a writer never inherits a brief built against last quarter’s results.

From there it drafts against that research and scores the draft for both Google and AI search, so you can see where it’s thin before it goes live.

An optimisation tool stops at publish. Frase’s Content Guard keeps reading Search Console, so a page that drops from position 3 to 7 gets caught the same week. It then drafts the fix and shows you the word-level changes to approve.

Use one, or build your own?

Option 1: use Frase in app

Frase’s agent takes a topic through the whole loop: it researches what ranks and what AI engines quote, writes the page in your brand voice, scores it, publishes it to WordPress, Webflow, Wix, Sanity or FraseCMS, and picks the page back up if it starts to slip.

By default it drafts and waits: every publish, every fix and every change to a live page comes to you first. Once it’s earned some trust, you can let it publish a content type on its own (glossary pages, say) inside a quality bar and a monthly cap you set, and keep everything else in your queue. Fixes to live pages come through Content Guard, where statistic edits and substantial changes always wait for a human.

Option 2: build your own on Frase’s MCP

The Model Context Protocol (MCP) is an open standard that lets an AI assistant use outside tools directly. Once Frase is connected, your assistant can use Frase’s tools in whatever order you design. The ones I use most are SERP research, keyword research, Search Console data, site audits and AI-visibility tracking.

There are three ways to connect:

1. In Claude: Frase is in the Claude connector directory. Search for it, click Connect and sign in.

2. Any MCP client (Cursor, Windsurf and others): point it at https://next.frase.io/api/mcp and sign in when the browser opens.

3. Locally, for developers: run npx @frase/mcp-server with an API key from your Frase settings.

It works on every plan, including the free trial. If you want work to run without you prompting it, Frase’s CLI (npx @frase/cli) can run Frase work from your terminal or on a schedule overnight.

The workflow runs both ways. On the read side, your agent pulls current rankings, Search Console data, audit results and what’s ranking for a query, and works out what’s decaying, what’s missing and what’s overlapping. On the write side, it pushes the result back: an updated draft, revised metadata, a published page. Nothing gets exported to a spreadsheet and copied back in.

For the step-by-step setup, I’ve written a full guide to building your own SEO agent with Frase, Claude and Cursor.

How we run agents on Frase’s MCP

Of course we lean into Frase for all of our content operations, but here are a few other things our team runs through Claude, using Frase’s MCP (and its API where the MCP doesn’t return what we need), that might be less obvious:

• An editorial reviewer that checks whether a post is worth publishing. Before this post went out, an agent we built pulled the search results for “AI SEO agent”, the keyword data, 90 days of our Search Console data and our own post library. It told us we already rank on page one for the term with an existing post, and that the first draft of this one would have competed with it. That’s why this version is about choosing between the two routes rather than another explainer.

• GEO audit reports for prospects considering Frase. We’ve built 15 of them with an agent that runs Frase’s AI-visibility and audit tools and turns the results into a report. AI-engine answers and scores can shift between runs, so a second agent re-checks the report’s claims against the raw AI answers, and a person reviews the report before it goes to a prospect.

• A separate checking agent. Our drafts go through a validator agent that treats each number and quote as unverified until it matches a source, and sends the draft back if it doesn’t.

Where agents still need a human

Agents remove handoffs, but a few decisions still need a person.

Keep a person on anything that changes a live page, at least until you’ve seen how the agent behaves enough times to win your trust. And check facts: an agent will happily write a confident number, so build in a check that every statistic links to a real source, or have a second agent do it.

Answers from ChatGPT, Perplexity and others vary from run to run, so date every result and re-run before you quote it.

Deciding what’s worth publishing at all should stay with a person too. In our own workflow, the most useful thing the editorial-review agent does is sometimes say “don’t publish this”, but someone on the team makes that call.

How to choose

Ask yourself:

1. Does your team already work in Claude, Cursor or an automation tool every day? If yes, building on the MCP fits how you work.

2. Do you want to design the workflow, or have it designed for you? Design it yourself: build. Have it done: use the agent.

3. Who will maintain it? A custom agent needs someone to update its instructions as your process changes.

4. Does it need to run when nobody’s prompting it? Frase’s agent and Content Guard keep watching pages on their own. A workflow you build in Claude runs when you run it, unless you schedule it yourself.

You don’t have to pick one forever. Try it out. See what feels right for your team and your needs. There’s no right or wrong path here. You might even end up like our team, using some workflows in the app and then leaning into different Frase tools via MCP when you have slightly more creative needs.

FAQs

Is there an AI that can do SEO?

Yes. AI SEO agents can research, write, optimise, publish and monitor content. The ones worth using keep a person in charge of what goes live.

Can ChatGPT do SEO?

On its own, ChatGPT can write and suggest, but it doesn’t have live ranking data, your Search Console or your CMS. Connecting an assistant to an SEO platform over MCP gives it that data and lets it act on it.

Which AI agent is best for SEO?

It depends on whether you want a ready-made agent or the building blocks for your own. We compare the main options in the best AI SEO agents in 2026.

What’s the difference between an AI SEO agent and an MCP server?

An agent carries out the tasks. An MCP server is the connection that gives an agent, yours or anyone’s, access to a tool’s data and actions. Frase offers both. There’s more on how MCP fits into SEO in our guide to MCP servers for SEO.

Start a free trial and give Frase’s agent one topic. If you’d rather build your own, the same trial lets you connect Frase to Claude over MCP. The trial lasts seven days and needs no credit card.