Semrush runs an MCP server at mcp.semrush.com. The reason to care is that SEO analysis is mostly joining datasets — keywords to positions to competitors — and that is work an agent does faster than a spreadsheet.
https://mcp.semrush.com/v1/mcp
Claude Sonnet 4.5
Chat with 60+ AI models on the same workflow — switch to a different model mid-conversation and re-run the same prompt, or use Compare mode to put several side-by-side and balance quality vs. cost.
A Semrush API key. Calls consume API units from your plan quota, so a broad keyword sweep has a real cost attached.
How models use it and what it is built for.
The server exposes Semrush’s research datasets as MCP tools. Keyword work is the core: search volume, difficulty, CPC and related or question-form variants for a seed term in a given database. Domain analytics covers organic and paid visibility for any domain, which is what makes competitor comparison possible without three browser tabs. Backlink data and position tracking are reachable, so an agent can answer where a page ranks now and which referring domains changed. The workflow this unlocks is the tedious one: take fifty seed keywords, pull volume and difficulty for each, cross-reference against which competitors already rank, and return a prioritised shortlist. That is an hour of manual work and about four tool calls. Note that Semrush bills by API units, so an agent looping over a large keyword set consumes quota quickly.
Typical tools an AI model can call. Exact names vary by version.
Copy any of these into MCP Agent Studio after connecting.
For the seed term "mcp server", give me volume and difficulty for the top twenty related keywords.
Which domains outrank us for our tracked keyword set, and what do they have in common?
Compare our organic visibility against these three competitors over the last six months.
Find question-form keywords around MCP testing with low difficulty and real volume.
This is not a single-model product: you get the same MCP connection with 60+ models (Claude, GPT, Gemini, DeepSeek, open-weight, and more), you can switch mid-conversation, and you can open Compare mode to run the same prompt against multiple models at once. The card above is a suggested starting point for this server — not the only choice.
Default pick for Semrush
Claude Sonnet 4.5
Keyword prioritisation means weighing volume against difficulty against intent. Sonnet 4.5 gives a defensible ranking; cheaper models just sort by volume and call it a strategy.
Listing tools proves the server is reachable, not that a model can work with it. Evals go further: they read every tool on the server, write a test suite from its real schemas, and run it — code decides pass/fail on the responses (schema conformance, error codes, pagination, result caps) while a scoring model grades plain-English tasks driven through the tools.
Get a pass/fail report per tool with the evidence behind each verdict — and replay the same suite after every schema change. Destructive tools are excluded from the run.
Run evalsOpen MCP Agent Studio with the connection pre-filled. Add your token, pick any of 60+ models, and start chatting — no install required.
Open Agent StudioCommon questions about connecting, scoping and using it safely.
Semrush’s hosted MCP server at mcp.semrush.com. It exposes keyword research, domain analytics, competitor discovery, backlinks and position tracking as MCP tools an AI assistant can call directly.
Yes, and this is the thing to plan for. Each tool call draws on your plan’s API quota, so an agent told to analyse two hundred keywords will do exactly that and bill accordingly. Constrain the set before you let it loop.
Semrush data is partitioned by country database, and results differ sharply between them. Specify the database in your prompt — an agent defaulting to US data while you care about the UK produces numbers that look right and are not.
Semrush is strongest on keyword and competitive research breadth. Ahrefs is generally regarded as stronger on backlink data. DataForSEO is a raw data API rather than a research product — cheaper per call, but you assemble the analysis yourself.
It can do the mechanical part well — gathering, joining and ranking. Judgement about which terms are worth pursuing for your specific business still needs you, because the model cannot see what you can actually rank for or sell.
Ahrefs
Backlink and ranking data an agent can query directly, without the export step.
DataForSEO
Raw SERP, keyword and backlink APIs priced per call, for agents that assemble their own analysis.
OpenSEO
Keyword research, SERP data, rank tracking and Search Console metrics, from chat.
Exa
Give an agent live web search and clean page reads — no API key to get started.