How to Build a Full SEO Analysis Dashboard with the Moz API MCP Server

August 3, 2026 7 min read

Written by: Jonathan Berthold Edited By: Jo Cameron

How to Build a Full SEO Analysis Dashboard with the Moz API MCP Server

Every SEO knows the drill: when organic traffic starts to decline, or a new competitor siphons customers, a distressed client or over-eager executive is likely to interrupt your late-night Dungeon Crawler Carl reading session and demand an SEO analysis pronto. ( And yes—my old agency days mean I’ve lived this scenario more than once!)

We’re living in a new acronym-infused era that gives marketers access to a wide range of skills and data with a single prompt. As someone who loves building products for fun, especially with the ubiquity of AI coding tools, and that's why I'm proud to announce that:

The Moz API is now accessible via MCP, making it even easier to access our data!

Instead of spending months coding custom apps, the Moz API MCP server lets you turn plain-English prompts into instant, full-stack SEO dashboards across all our Moz API data endpoints.

Work with the MCP where you're comfortable

The Moz Data MCP Server gives you access to all of our SEO API endpoints: keyword metrics, search intent, site metrics, Brand Authority, link research, ranking keywords, and more.

While the examples in this post heavily focus on Claude Code & Codex (OpenAI), the Moz API MCP server works with any MCP-compliant platform:

• AI Assistants: Claude Desktop (Anthropic), ChatGPT (OpenAI), Gemini CLI
• AI IDEs & Editors: Cursor, Windsurf, VS Code (via MCP extension)
• Custom Engines: Any local or custom agent built on the Open MCP standard

Getting started

Experimenting with the Moz API MCP server is easier than you might think. Getting set up only takes a few moments. Connect the Moz API to your assistant via MCP using the official step-by-step guide. If you’d like to replicate some of the reports above from my initial testing, you can follow the process below:

• Start with a prompt: Ask Claude (or the LLM of your choice) to run a competitive snapshot of your brand against competitors. Feel free to use the prompts shown in this post.
• Consolidate at the end: End every conversation with a consolidation request. "Build me a dashboard from all of this" is the difference between a folder of files and one shareable deliverable.
• Enjoy building: Experiment, iterate on prompts, and find a groove with your preferred models. For example, check out this sample backlink gap analysis report built in a single prompt using the Moz MCP server.

What MCP actually is, and why you should care

MCP (Model Context Protocol) is a standard that lets an AI assistant call external data sources directly. Any platform with data useful in daily workflows is likely to spin up an MCP server to make access easier and keep requests focused on the data you need.

Without connections to an MCP server, running a backlink analysis with your LLM of choice can wreak havoc on your token usage and spin up all types of analyses, which might return something adequate. The Moz MCP server focuses on the data specific to your request, using the tools and features available within the connection, so you get a more targeted result without writing a line of code.

The workflow: from plain-English prompts to a full report set

My first experiment started with one sentence, typed exactly as you would say it to a colleague or write it out in a Jira ticket:

"Run an SEO analysis for me comparing bose.com to jbl.com and sennheiser.com."

This simple prompt in Claude Code, without any specific guardrails, ran a full analysis using a variety of Moz API endpoints to paint a picture of how my favorite audio brand is faring in organic search relative to its feisty competitors. As you can see from the snapshot below, Claude reviewed the data, packaged it in a neat little report, and provided some pertinent takeaways I can use to add context to share with stakeholders above my station, showing how MCP turns a plain-English request into targeted analysis and a usable report.

Level up your backlink gap analysis with ease

Now that I had my high-level competitive analysis done, I wanted to dig a bit deeper and unearth some of the link building opportunities I could tap into in the audio niche. Assuming I have a solid marketing budget (Bose headphones aren’t cheap), I could use the Moz API MCP server to analyze my competitors to understand my gap and what I needed to achieve, so I kicked off this next part of the workflow with the following prompt:

“Now I would like a backlink opportunity analysis for bose.com vs. the other two competitors. Are there any valuable links I can build to help my brand?"

In my mind, I was hoping Claude would run one of my favourite Moz API endpoints: Fetch Link Intersect. The link intersect tool is the best endpoint to use when analyzing link gaps among pages and/or domains, because you can request URLs that link to your competitors but not to your own domain. Fortunately, Claude and I have been working a lot together recently, so our near-Borg collective connection allowed it to choose the link intersect method without even asking me, making the MCP value obvious in a single step by focusing on the exact links I needed. The output provided the following overview:

Not only was I able to get a list of the top domains to link to, but Claude also provided additional context based on the data it extracted from the Moz API MCP server to steer me in the right direction. If I were a marketing manager at Bose, I know now that I should focus my digital PR and link-building efforts on websites that publish “best of” roundups, gift guides, and other similar content.

The dashboard: a walkthrough of what one conversation produced

Now that I had a rhythm going, I prompted Claude to run the following types of individual reports:

• Analyze recently gained links from my competitors and surface any existing campaigns I should replicate for my brand.
• Analyze the anchor text profile of each domain and show how each brand is linked (brand vs. commercial vs. spammy anchors)
• Create a content opportunity report based on a keyword gap analysis of my domain vs. my competitor.
• Analyze authority over time → who is gaining/losing DA over recent months.
• Analyze recently lost links to unearth any unsettling trends for my brand or any opportunities based on links lost from my competitors.
• Which specific competitors' pages attract the most backlinks, and are there any link-worthy content formats I should reverse-engineer?

After playing around with the MCP server, I thought of some tools I haven’t been using in my custom app built on the Moz API. For example, the DA trend over time can be tapped into via our Fetch Site Metric Histories endpoint, but I didn’t even think to run that over the last few months. Additionally, tapping into the power of Claude during the brief Fable is available window allowed me to dig deeper into the overall analysis. Opus remains a very solid option moving forward, which reinforces why MCP is useful for faster, deeper analysis.

Once I wrapped up all my individual reports, I asked Claude to create a final report dashboard in HTML that I could share with others and make the analysis easier to pass along.

In addition to the high-level authority scorecard, Claude converted all of my individual analysis files into the following breakdowns:

• Who wins the SERP → a report providing the organic ranking footprint using the ranking keyword data, showing where Bose owns the #1 spot outright and, more usefully, where it sits at #15 to #22 on high-volume terms it should already be winning. Those near-misses are the cheapest rankings you will ever buy back.
• Domain Authority vs. Brand Authority → the gap between authority earned through real search demand and authority earned by links alone. As SEO continues to evolve and GEO emerges, knowing how your brand performs across both metrics is vital.
• Contextualize backlink gaps → lists of potential high-leverage targets you should chase from a brand marketing perspective, as well as some potential links that could be harming your overall profile. Claude added a “disavow list”, which was an added surprise. Author’s note: tread carefully with disavow lists. While this was a monthly tactic back in the old SEO days where SEO programs needed a veritable checklist of mundane tasks to appease clients, there’s very little (if any) you need to disavow these days. In future iterations, I may ask Claude to omit this language.
• Anchor-text health → a quick read on whether each brand's link profile looks natural and branded or stuffed with exact-match commercial anchors, which is usually the first tell of a profile that ages badly. Additionally, with the evolution of AI search, you want links earned to eventually fall into the more natural/branded category to win more visibility in targeted prompts.
• Content and keyword gaps → the terms my competitors rank for that my brand doesn’t, prioritized by volume and difficulty. This type of snapshot provides insights into the potential content roadmap to build.
• A prioritized action list → the substance of the analysis that provides actionable follow-ups. Every finding distilled into ranked items that can easily fit within your next Asana task list or quarterly review.

Ready to plug in? Whether you’re running Claude Desktop, ChatGPT, or Gemini, the setup is the same. Moz handles the server, your favorite LLM handles the thinking, and you get your weekend back.