An AI SEO agent can help you perform important tasks faster and easier than doing them manually. You can set one up with relatively little initial effort, and the agent can continue working long into the future.
This guide will show you how to set up your own AI SEO agent, step by step.
What is an AI SEO agent?
An AI SEO agent is a fully or partly automatic workflow you build into an AI tool to carry out a specific process.
SEO agents don’t need to be fully autonomous. In fact, you’re likely to get better and more consistent results if you build human approval into your SEO agent processes.
For example, if you use an SEO agent to find internal linking opportunities for your website, it's best to have a human actually implement the internal links.
Even when set up properly for tasks related to SEO, AI agents can still hallucinate and make mistakes that can be costly depending on the task.
What can AI SEO agents actually do?
SEO agents can automate important tasks like keyword research, competitor analysis, and link building outreach. Other tasks they can help with include:
- Keyword clustering
- Content decay detection
- Identifying opportunities to refresh content
- Technical audits
- Internal linking at scale
- Performance reporting
You usually need to connect external tools to an AI platform to perform these tasks effectively, which you can do via an API or model context protocol (MCP) connection. MCP is a way for AI tools to communicate with data providers like Semrush.
All Semrush SEO subscriptions and SEO + AI subscriptions come with 50K MCP API units per month. Connect your AI tool to the Semrush MCP to give your agent access to data sources like the keyword and backlink databases.
When is an agent the wrong tool?
SEO agents are usually the wrong tool for:
- One-off tasks: Entering a single prompt in an AI tool is generally cheaper, easier, and faster
- Anything that needs editorial judgment or brand risk assessment: The oversight required for these types of tasks means an agent becomes less cost-effective to set up and use
- Workflows that change every time they run: Making constant changes to the agent’s instructions erodes the value of setting one up in the first place
How to build an AI SEO agent of your own
Here's how to build an SEO agent that performs keyword research, creates topic clusters based on that research, then generates content briefs for the topics you want to target. You can adapt the steps in this workflow to whatever use case you need to build an agent for.
Step 1: Choose one clearly defined workflow
Choose one clearly defined, repeatable SEO task for your AI agent to perform.
You can set up AI SEO agents for complex tasks, but I don’t recommend doing this for your first build. There are simply too many potential points of failure, and you're likely to spend more time trying to fix things than getting results.
And since API units for the tools that you connect cost real money, a badly scoped agent can very quickly spend your budget as you go through API units. Also the trial-and-error process of setting up the agent and testing it can quickly use API units.
I recommend starting with a workflow that has clear inputs, clear outputs, and easy-to-validate success metrics. For this guide, we’re going to build an agent that clusters keyword ideas and then generates a content brief. It’ll do this by:
- Taking a seed keyword as input
- Checking the seed keyword against existing Google Search Console (GSC) data to spot opportunities to optimize existing pages
- Performing keyword research using the Semrush MCP and grouping the results into distinct topic clusters
- Creating a content brief for a user-chosen topic based on SERP analysis and Semrush data
We’ll measure the success of the SEO agent by the quality of the content briefs it produces.
This agent does have multiple steps, but they’re all fairly straightforward. And we get one distinct output (a content brief) each time we run it.
Step 2: Document the existing human process
Document the existing human process to align the agent’s behavior with how you’d ideally perform the task yourself as an SEO professional.
Documenting the process should include:
- Any data sources you use
- Rules or filters that you employ
- Any exceptions that you would account for
You'll turn this documented process into the agent's operating instructions in a later step.
Below is an example documented process for the agent we'll be creating to help us perform keyword research, cluster topics, and generate a content brief:
Step 3: Choose your inputs and outputs
Choose clear user inputs and agent outputs based on your documented human process to help users to get the most out of your agent and improve the consistency of the agent’s results.
For example, we have three stages for our content-brief-creation agent, each with its own inputs and outputs:
- Stage 1 (one-time setup): The user inputs their business context file, GSC data, and a list of their existing URLs. The agent’s output is a CSV with clustered queries from GSC to be used for each run of the agent going forward.
- Stage 2 (keyword research): The user inputs their seed keyword or topic. The agent outputs a CSV of topics clustered around the user’s input keyword.
- Stage 3 (content brief): The user inputs their chosen topic to target from stage 2’s CSV output. The agent outputs a content brief for the user’s chosen topic.
You’ll use each of these inputs in step 5. I recommend specifying the file types you’ll be uploading and what you want the agent to output. For our agent, I’ve specified the content brief should be a docx file, but you could change this to be a markdown file, PDF, or Google Doc (if you connect to your Google Drive).
Step 4: Connect verified data sources
Connect verified data to ensure your AI SEO agent is working from reliable sources of truth — this is a must to keep the agent from hallucinating metrics or data points.
Relevant data sources for your AI agent can include:
- The Semrush API or MCP
- Google Search Console
- Google Analytics
- Your content management system
- Any manually created sources of data, like lists of URLs or keywords you plan to target
For our agent, we’re going to connect the Semrush MCP to enable the tool to perform keyword research using Semrush’s keyword database.
This process may vary slightly depending on the AI tool you’re using. We’ll use Claude below, but for ChatGPT, you’ll find the connection in the “Plugins” area.
In Claude, you can connect the Semrush MCP to your own agent by clicking the plus icon on any chat window, then click “Connectors” > “Add connector” > “Browse connectors.”
In the search bar that appears, type “Semrush” and click the plus (+) button to connect Semrush to Claude via the MCP.
Follow the sign-in workflow to finish connecting Semrush to Claude.
We're also going to upload CSVs of our Google Search Console data. While this is a manual step, it's fairly quick and easy to do. And you only need to do it once at the start, and then monthly to keep the data updated.
If you want an explanation of how to connect GSC directly to your agent, read our article on turning Claude Code into your SEO analyst.
Finally, we're also going to upload a list of our URLs. This allows the agent to suggest internal linking ideas in the content brief.
Step 5: Turn your human process document into agent instructions
Turn your human process document from step 2 into instructions for your AI SEO agent by pasting the document into the AI tool and telling it to do this for you.
In my experience, tools like Claude and ChatGPT are generally quite good at taking this kind of input and turning it into a set of instructions that the AI tool itself can use.
I recommend providing the document of the human process along with a summary of the inputs and outputs you expect. I also recommend clarifying which tools you want the agent to use and when, to cut down on token and API unit use.
When you upload all of this information, I suggest asking the tool if it understands everything and if there’s anything else it needs to perform the workflow.
You won’t get the perfect agent with one prompt, and it will likely require a bit of back and forth (you may want to experiment with different models, too). You can then edit this output to create a finalized set of instructions for the agent that you’ll upload as a skill file (a set of custom, reusable instructions) in the next step.
You can download this example skill doc here if you want to build your own agent to generate content briefs.
You can also connect the agent to communication or project management tools like Monday.com or Slack, so the agent can deliver reports or create tasks automatically. But I recommend keeping high-impact tasks (like publishing, redirects, or code deployments) behind human approval.
Step 6: Add your skill to the AI platform
Add your instructions to the AI platform as a skill file to build a repeatable, callable workflow directly within the platform that you can reference as you need it.
If you’re using Claude, click “Customize” in the left-hand sidebar.
Then select “Add” > “Create a skill.”
Give your skill a name using only lowercase letters, numbers, and hyphens. Also add a description, add your agent instructions to the free text box, and click “Create” when you’re done.
Step 7: Add relevant files to the skill
Add relevant files to your skill to improve the quality of your AI agent’s output.
I recommend adding a business context file, so your agent understands what your business does and who your audience is to help it generate outputs that are better tailored to your situation. Specifically, I recommend including information about:
- What you sell (including specifics about product/service features)
- Who you sell to (primary and secondary audiences)
- Who your main competitors are
- Important pages on your website (e.g., best-selling products, highest-traffic posts)
- Any rules or filters you want the AI to take into account
For our content brief agent, this business context is especially useful since it can impact the types of keywords the agent focuses on. For example, the agent can look for or prioritize keywords related to our upcoming product launches.
You can download a business context template file here. I recommend adding this no matter what SEO agent workflow you plan to create.
To add your business context file in Claude, click the “+ Add file” button within the skill editor.
Give the file a name and press enter.
Add or paste in your business context in the free text area. Then click “Create” to create the skill.
Step 8: Test and tweak your agentic workflow
Test your AI SEO agent to iron out any major issues, which you can do by uploading dummy data sources and monitoring the agent's output.
For our agent, I uploaded our CSV of Google Search Console data along with a list of existing URLs. I then used a prompt that called out the content brief skill and specified a seed keyword for the tool to use in the test (“AI tools for freelancers”).
Pay attention to the reasoning and evidence the AI gives you for the decisions it makes and the outputs it provides in this testing step. This helps you spot issues and why they’ve occurred.
You may want to require the agent to provide evidence like this when it's running the live workflow as well.
For example, for our content brief agent, I specified that the agent should provide sources for all the keywords it suggests to include in the content brief.
This way, if at the human review stage the user is concerned about the inclusion of a specific keyword or heading suggestion, they can look at the source file to understand why that is being suggested.
For our workflow, the reasoning may be that a competitor included a specific heading or that Semrush data suggests the keyword has a high search volume and is worth including in the content.
I recommend running multiple tests with different inputs. For example, I asked our agent to run the process for several different seed keywords. This way, I could ensure the output was reliable for different kinds of content briefs (like listicles, comprehensive guides etc.).
Here’s an example of a test I ran for this agent using a GSC export from my own website, along with relevant context about my business, and a list of my site’s URLs:
The agent output the topic cluster CSV as planned:
I then prompted the agent to generate a content brief for “AI Tools for Freelancers (General Roundup).” Here’s what the output looked like:
Since I uploaded a list of my website’s URLs, the agent was able to suggest relevant internal linking opportunities in the brief.
In the “Notes for the writer” section, the agent included a recommendation to include mentions of upcoming products once they launch. This was only possible because I uploaded the business context file that contained information about these upcoming products.
Step 9: Deploy, monitor, and improve
Once you’ve performed multiple successful tests of your AI SEO agent, you can start using it right away or deploy it to your wider team.
You may want to record yourself going through the process if it requires approval from other stakeholders. Or if the agent is going to be used by other people on your team. This could be a quick Loom video or a Google Doc with screenshots showing exactly what you prompted the tool with.
You can adapt your AI SEO agent over time based on your own interactions and those of your team as issues pop up. Just navigate to your skill file, click the three-dot menu, and select “Edit.” Make your changes, then rerun the testing step.
Be mindful of who you share the agent with, and how many people have access to it. Many people using the agent with a wide range of models can quickly spend both Claude tokens and API units within Semrush.
Final takeaway
In the realm of SEO, AI agents can streamline important tasks and scale your efforts without having to build and maintain complex automations. You can even build multiple agents as skills you can call as you need them, and they can be for everything from keyword research to backlink outreach.
Connect your agent to data sources like Semrush to improve their outputs. Try it today by connecting your favorite AI tool to the Semrush MCP.
