DEV Community: AgentSEO-dev

How to Add an SEO MCP Server to Claude Code

AgentSEO-dev — Sat, 25 Jul 2026 15:23:20 +0000

How to add an SEO MCP server to Claude Code

Claude Code can already edit files, run commands, and reason through a codebase.

The gap shows up when the work depends on a live external system.

SEO is a good example. If you ask Claude Code to improve a landing page, it can inspect the page and suggest better copy. But it cannot know the current SERP, the competing page formats, the AI Overview behavior, or the backlink context unless you paste that data in.

That is exactly the job MCP is built for.

Claude Code’s MCP docs describe MCP servers as a way to connect Claude Code to external tools, databases, and APIs so Claude can read and act on those systems directly instead of working from copied data.

In this guide, we will add an SEO MCP server to Claude Code and run the first useful prompts.

I will use AgentSEO as the example server because it exposes a hosted Streamable HTTP MCP endpoint and a local npm package. The setup pattern is the important part.

What you get from an SEO MCP server

An SEO MCP server gives Claude Code tool access to live search workflows.

Instead of asking:

Here is a SERP export. Can you summarize it?

you can ask:

Use the SEO MCP server to analyze the SERP for "best seo api" in the United States.
Then identify the search intent and draft a content brief for a comparison page.

The difference is small in wording and large in workflow.

The first prompt makes you the data pipeline.

The second prompt lets Claude Code call the tool directly.

For AgentSEO, the live server card currently lists 45 MCP tools, including SERP analysis, keyword ideas, content briefs, local SEO checks, backlink analysis, rank tracking, and AI Overview extraction.

You can verify that yourself:

curl https://www.agentseo.dev/.well-known/mcp/server-card.json

The hosted endpoint is:

https://www.agentseo.dev/mcp

Before you start

You need three things:

Claude Code installed.
An AgentSEO API key.
A project where you want the MCP server available.

Use a server-side API key. Do not use a browser-restricted key for local agent tooling.

Option 1: add the hosted SEO MCP server

Claude Code supports remote HTTP MCP servers with:

claude mcp add --transport http <name> <url>

For AgentSEO:

claude mcp add --transport http agentseo https://www.agentseo.dev/mcp \
  --header "Authorization: Bearer sk_live_your_key" \
  --header "x-project-id: client-alpha" \
  --header "x-workflow-id: seo-mcp-test"

Replace sk_live_your_key with your AgentSEO API key.

The x-project-id and x-workflow-id headers are optional, but I like adding them early. Once an agent workflow starts making real API calls, traceability matters.

Option 2: add the local npm MCP server

If you prefer a local stdio server, use the npm package:

{
  "mcpServers": {
    "agentseo": {
      "command": "npx",
      "args": ["-y", "@agentseo/mcp-server"],
      "env": {
        "AGENTSEO_API_KEY": "sk_live_your_key",
        "AGENTSEO_API_URL": "https://www.agentseo.dev/api/v1"
      }
    }
  }
}

This is useful when your MCP client expects a local subprocess instead of a hosted HTTP endpoint.

For Claude Code, I would start with the hosted HTTP version unless you have a reason to keep everything local.

Verify the server in Claude Code

After adding the server, open Claude Code and run:

/mcp

Claude Code’s /mcp panel lets you inspect connected MCP servers. It should show the server and its tools.

If the server does not appear:

restart Claude Code
check the API key header
confirm the endpoint URL is exactly https://www.agentseo.dev/mcp
run claude mcp list
run claude mcp get agentseo

The setup is not done until Claude Code can see the tools.

First prompt: analyze a live SERP

Start with one bounded workflow.

Use AgentSEO to analyze the SERP for "best seo api" in the United States.

Return:
1. the dominant search intent
2. the common page formats
3. the SERP features that matter
4. what kind of page I should build
5. three risks before publishing

This is better than asking for “SEO advice.” The prompt names the keyword, location, output shape, and decision you need.

Second prompt: create a content brief

Once the SERP analysis works, ask for something closer to production.

Use AgentSEO to create a content brief for the keyword "seo api for ai agents".

Audience: developers building agent workflows.
Page type: educational comparison page.
Goal: explain when an SEO API should be exposed as MCP tools.

Include:
- search intent
- suggested H2 structure
- entities and subtopics to cover
- internal link ideas
- title and meta options
- what not to claim

The phrase “what not to claim” is important. Agent-generated SEO content gets risky when it turns every tool output into marketing confidence.

Ask Claude Code to preserve the review step.

Third prompt: check AI Overview visibility

If your SEO work touches AI search, use a narrower prompt:

Use AgentSEO to check AI Overview visibility for "best seo api".

Tell me:
1. whether an AI Overview appears
2. what source patterns show up
3. whether AgentSEO or competing pages are citation candidates
4. what page changes would improve citation likelihood

Treat this as directional research, not a magic ranking button.

AI Overview behavior changes. The point is to create a repeatable check, not a one-time screenshot.

Common setup mistakes

The annoying MCP failures are usually small.

Wrong header format

Use:

--header "Authorization: Bearer sk_live_your_key"

Do not paste the header as JSON into the CLI command.

Wrong transport

For the hosted AgentSEO endpoint, use:

--transport http

The MCP spec calls the current HTTP transport Streamable HTTP. Claude Code accepts http in the CLI and also recognizes streamable-http in JSON configuration.

No restart after configuration

If Claude Code was already open, restart it or check /mcp again after adding the server.

Prompt is too vague

This is a bad first prompt:

Improve my SEO.

This is a better first prompt:

Use AgentSEO to analyze the SERP for "best seo api" in the United States and tell me what page type I should build.

MCP gives Claude Code tools. You still need to give it a job.

When not to use an SEO MCP server

Do not use an SEO MCP server for every writing task.

You probably do not need live SEO tools when:

you are editing brand voice
you are cleaning grammar
you are writing internal docs
you already have the source data in the repo
the page is not search-led

Use the server when the decision depends on current search context.

That includes SERP intent, competitor page shape, keyword opportunities, AI Overview visibility, rank tracking, local visibility, or backlink signals.

The operator checklist

Before you call the setup done:

Add the MCP server.
Confirm it appears in /mcp.
Run one live SERP prompt.
Run one production-shaped content brief prompt.
Save the working prompt in your repo or team docs.
Add project/workflow metadata if multiple people will use it.
Decide who reviews the SEO recommendation before it ships.

The last step matters.

An SEO MCP server gives Claude Code fresher context. It does not remove judgment.

The best workflow is not “agent writes, human publishes.”

The better workflow is:

agent gathers live SEO context
agent drafts the recommendation
human checks the tradeoffs
agent helps implement the approved changes

That is where MCP starts to feel useful.

Not as another dashboard.

As a tool layer inside the place where the work is already happening.

Building an SEO MCP server for Claude Code and Codex

AgentSEO-dev — Mon, 20 Jul 2026 16:18:18 +0000

Building an SEO MCP server for Claude Code and Codex

Most SEO APIs were built for dashboards.

That is not a criticism. Dashboards are useful. A marketer opens a report, checks rankings, reviews keywords, exports a CSV, and decides what to do next.

But that is not how work feels inside Claude Code, Codex, Cursor, or a custom AI agent.

Inside an agent workflow, the shape is different. You do not want to stop, open a separate SEO tool, copy data into the chat, ask the model to reason over it, then move back to your editor.

You want the agent to ask for live search data directly.

That is why we shipped AgentSEO as an MCP server.

This post is a practical breakdown of what changed, how the server is installed, and why I think SEO APIs are going to move from dashboard-first products to agent-native workflow tools.

The buyer problem is not only data access

SEO teams already have data.

They have rank trackers, backlink tools, keyword databases, crawl reports, and a growing pile of AI visibility screenshots. The problem is that the data often stops one step before the work.

A typical SEO API gives you a payload.

Then your team still has to answer:

Which result matters?
Which page should we update first?
What is the intent behind this SERP?
What should the writer or developer actually change?
Is this useful for an agent, or does it need another parser layer?

That last question is the one more API teams should ask.

If the output still needs a parser layer, a polling layer, and a summarization layer before an agent can act, the API is not finished for agent workflows.

What an SEO MCP server should do

MCP gives clients a standard way to discover and call tools. The official MCP registry describes itself as a list of MCP servers for clients, like an app store for MCP servers.

That matters because the install surface is moving closer to the place where developers already work.

For SEO, I do not think the best MCP server is just a thin wrapper around raw endpoints. That is a start, but it misses the point.

A useful SEO MCP server should expose workflow-shaped tools.

Instead of only returning raw SERP data, it should help an agent do jobs like:

analyze SERP intent
find content gaps
draft a content brief
check local visibility
review title and meta opportunities
inspect AI Overview presence
identify backlink opportunities
QA a draft before publishing

The agent should be able to move from question to action without making the user become the integration layer.

What we built into AgentSEO

AgentSEO now exposes 45 MCP tools for live SEO workflows.

The tools cover:

SERP analysis
keyword research
content briefs
content refresh briefs
backlink analysis
rank tracking
local SEO checks
sitemap and technical QA
AI Overview extraction
AI search visibility monitoring

The important part is not the number. A big tool count can become noise fast.

The important part is that the tools map to repeatable SEO jobs. A developer, growth engineer, or technical SEO should be able to give the agent a real task and get back something useful enough to act on.

Example:

Use AgentSEO to analyze the SERP for "best seo api" in the United States.
Identify the dominant intent, list the strongest competing angles,
and create a content brief for a comparison page.

That is different from:

Fetch the SERP payload and make me figure out the rest.

The second version is data access. The first version is closer to workflow infrastructure.

Install path: hosted MCP

For clients that support remote MCP servers, AgentSEO can run over hosted Streamable HTTP.

claude mcp add --transport http agentseo https://www.agentseo.dev/mcp \
  --header "Authorization: Bearer sk_live_your_key" \
  --header "x-project-id: client-alpha" \
  --header "x-workflow-id: nightly-refresh"

The extra headers are optional workflow metadata. I like keeping them in the example because production agent workflows need traceability. When an agent calls a paid or rate-limited API, you eventually want to know which project and workflow made the call.

Install path: local stdio MCP

For local MCP clients, the npm package works through stdio.

{
  "mcpServers": {
    "agentseo": {
      "command": "npx",
      "args": ["-y", "@agentseo/mcp-server"],
      "env": {
        "AGENTSEO_API_KEY": "sk_live_your_key",
        "AGENTSEO_API_URL": "https://www.agentseo.dev/api/v1"
      }
    }
  }
}

That gives teams a clean local path without forcing every client through the hosted endpoint.

The GTM lesson: MCP directories are becoming agent app stores

The product work was only half the launch.

The other half was distribution.

If you ship an MCP server and only mention it in your docs, you are making discovery too hard. Developers are already browsing MCP directories to find tools their agents can use.

For AgentSEO, we published or submitted to:

Surface	Status
Official MCP Registry	Live as `dev.agentseo.www/agentseo-mcp`
npm	Live as `@agentseo/mcp-server`
Smithery	Live, 45 tools detected
Glama	Hosted connector live, 45 tools verified
mcp.so	Submitted
awesome-mcp-servers	PR submitted
PulseMCP	Waiting on official registry sync
MCP Market	Submitted
MCP Server Spot	Submitted

This is the new shelf space.

Not all of it will convert. Some directories will send little traffic. Some will take weeks to index. Some will matter mostly as trust signals.

But the intent is unusually clean.

Someone browsing an MCP directory is not vaguely interested in AI. They are looking for a tool their agent can install.

That is a better starting point than most launch traffic.

The product lesson: expose jobs, not endpoints

This is the part I would underline for any API company.

Do not start by asking, "How do we expose every endpoint through MCP?"

Start with a smaller question:

What are the 5 jobs an agent should be able to complete without leaving the workflow?

For an SEO API, those jobs might be:

Analyze a live SERP.
Find keyword or content gaps.
Create an implementation-ready brief.
QA a draft before publishing.
Track whether visibility moved.

That is enough for a useful first version.

The raw endpoint map can come later. If you start with the endpoint map, you risk shipping a server that is technically complete and practically annoying.

A simple checklist for API teams

If you are thinking about turning your API into an MCP server, I would start here:

Pick one user: developer, agency operator, growth engineer, analyst.
Pick one repeatable workflow.
Expose the few tools needed to complete that workflow.
Make the install command copy-pasteable.
Publish to the official MCP registry.
Add one directory listing where your buyers already browse.
Test with a real prompt, not only a protocol inspector.

The inspector can tell you the server works.

A real prompt tells you whether the product works.

The larger shift

APIs used to feed dashboards.

Now they can feed agents.

That does not make dashboards obsolete. It does mean API products need a second interface: one designed for software agents that can plan, call tools, inspect results, and continue the workflow.

For AgentSEO, MCP is that interface.

The bet is simple: if AI agents are where more technical SEO and growth work happens, then SEO infrastructure should be available inside those agents.

Not as a pasted export.

As a tool the agent can actually use.

DEV Community: AgentSEO-dev

How to Add an SEO MCP Server to Claude Code

How to add an SEO MCP server to Claude Code

What you get from an SEO MCP server

Before you start

Option 1: add the hosted SEO MCP server

Option 2: add the local npm MCP server

Verify the server in Claude Code

First prompt: analyze a live SERP

Second prompt: create a content brief

Third prompt: check AI Overview visibility

Common setup mistakes

Wrong header format

Wrong transport

No restart after configuration

Prompt is too vague

When not to use an SEO MCP server

The operator checklist

Links

Building an SEO MCP server for Claude Code and Codex

Building an SEO MCP server for Claude Code and Codex

The buyer problem is not only data access

What an SEO MCP server should do

What we built into AgentSEO

Install path: hosted MCP

Install path: local stdio MCP

The GTM lesson: MCP directories are becoming agent app stores

The product lesson: expose jobs, not endpoints

A simple checklist for API teams

The larger shift

Links