How do I use seo-audit-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@seo-audit-mcp Audit example.com and tell me which pages are missing from its sitemap." That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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seo-audit-mcp

by huanmxwp-crypto

Overview Schema Related Servers Score Discussions

Python

Remote

seo-audit-mcp

An MCP server that gives Claude (or any MCP client) the ability to audit a live website's technical SEO: sitemap coverage, per-page issues, and redirect chains.

Ask in plain language — "audit mortgagecalculatortools.com and tell me which pages Google is never told about" — and the model calls the tools, crawls the site, and answers with specifics.

The problem it solves

A site's sitemap.xml is how you tell Google which pages exist. When a page is missing from it, nothing errors and nothing warns — the page simply never accumulates impressions. Checking it by hand means diffing a filesystem listing against an XML file, so in practice nobody does it.

Case study: a 25-page gap that turned out to be correct

The first site this was pointed at had 125 HTML files on disk and 100 URLs in its sitemap. A 25-page gap — the kind of finding that gets written up as a bug and assigned to someone.

One sitemap_coverage call surfaced the gap, and one audit_urls call on a sample explained it: every one of the 25 carried <meta name="robots" content="noindex, follow">. They were two deliberately de-indexed content clusters, and the sitemap was exactly right to omit them. Verified against the filesystem afterwards: 25 noindex pages on disk, the same 25 absent from the sitemap, zero noindex pages wrongly included. Perfect consistency.

That is the useful result. A coverage number alone ("125 vs 100") reads as a defect and buys a day of somebody's time; coverage plus per-page noindex status closes the question in a minute. This tool is as valuable for the false alarms it kills as for the real gaps it finds — which is why audit_urls reports noindex per page rather than only counting URLs.

Related MCP server: web-audit-mcp

Tools

Tool	What it does
`fetch_sitemap`	Fetches `sitemap.xml`, follows sitemap-index nesting (max depth 3), returns every declared URL, deduped
`audit_urls`	Crawls URLs concurrently and reports per-page issues: broken status, redirect chains, missing/over-length `<title>` and meta description, missing or duplicate `<h1>`, missing canonical, `noindex`, thin content
`sitemap_coverage`	Diffs a sitemap against a list of URLs you know exist → what's missing from the sitemap, what's declared but dead
`check_redirects`	Traces redirect chains, flags multi-hop chains and chains ending in 4xx/5xx — use after a URL-structure change

Every tool returns structured JSON with an issues list per page and an aggregated issue_summary, so the model can reason over counts instead of re-reading raw HTML.

Install

pip install -e .

Requires Python 3.10+. Dependencies: mcp>=2.0.0, httpx.

Connect it to Claude Code

Add to .mcp.json in your project (or ~/.claude.json for global use):

{
  "mcpServers": {
    "seo-audit": {
      "command": "python",
      "args": ["-m", "seo_audit_mcp"]
    }
  }
}

For Claude Desktop, the same block goes in claude_desktop_config.json.

Then just ask:

Fetch the sitemap for https://example.com/sitemap.xml, audit the first 20 URLs, and summarise the issues by frequency.

Run it directly

python -m seo_audit_mcp        # stdio transport

Design notes

Three decisions worth calling out, because they are the difference between a demo and something you can point at a client's production site:

Crawling is rate-limited by construction. fetch_many runs behind an asyncio.Semaphore capped at 16 concurrent requests, and every tool clamps its input. A 500-URL sitemap without that ceiling would open 500 sockets at once and read as an attack to the target host. The crawl is a cost the target site pays, so the ceiling is not configurable upward from the tool surface.

No fetch failure aborts a run. fetch_one catches httpx.HTTPError and records it on the returned PageAudit rather than raising. One dead host in a 200-URL crawl degrades one row instead of losing 199 good results.

Parsing is deliberately lenient. Real-world HTML is malformed often enough that a strict parser raising mid-crawl is a liability. The extractors are permissive regexes that return None rather than throw — but with the traps handled: <script> and <style> bodies are stripped before word-counting and heading extraction, so a <h1> inside a JS string literal is not counted as a heading, and relative canonicals are resolved against the page URL.

normalize_url deliberately does not strip trailing slashes: /a and /a/ can be genuinely different pages, and collapsing them would hide duplicate-content problems this tool exists to surface.

Tests

pip install -e ".[dev]"
pytest

The suite is network-free — HTTP is exercised through httpx.MockTransport, so it runs in CI and on a plane. It covers the parsing edge cases that bite in production: script-embedded headings, namespace-less sitemaps, relative canonicals, sitemap URLs that return a styled HTML 404 with a 200 status, and non-HTML content types being wrongly reported as pages "missing a title".

License

MIT

Available Tools

4 tools

audit_urlsA

Crawl a list of URLs and report per-page technical SEO issues: broken status codes, redirect chains, missing or over-length titles and meta descriptions, missing or duplicate H1, missing canonical, noindex, and thin content. Returns a per-URL breakdown plus an issue summary.

ParametersJSON Schema

Name	Required	Description	Default
`urls`	Yes
`concurrency`	No
`timeout_seconds`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A3.5/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral disclosure burden. It usefully states that the tool crawls URLs and returns a per-URL breakdown plus an issue summary, but it does not disclose operational behaviors such as crawl duration, rate limiting, redirect-following details, or auth/network requirements. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single information-dense sentence that front-loads the action and resource, then lists issue categories and the return shape. It avoids repetition and wastes no words, though the enumeration makes it slightly dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the description does not need to detail return values, and it does give a useful high-level summary. However, with zero annotations, zero schema descriptions, and no usage guidance, the description leaves concurrency/timeout semantics and tool-selection boundaries undocumented, making it only moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it never names or explains urls, concurrency, or timeout_seconds. The parameter names are somewhat self-explanatory, yet the description adds no detail about what concurrency or timeout_seconds control, how URLs should be formatted, or whether limits apply.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb-resource pair ('Crawl a list of URLs and report per-page technical SEO issues') and then enumerates the exact issue categories. This clearly distinguishes it from siblings like fetch_sitemap and sitemap_coverage by centering on per-URL technical SEO auditing, even though it overlaps with check_redirects on redirect chains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies its use case by listing SEO checks, but it never explicitly states when to prefer this over check_redirects, fetch_sitemap, or sitemap_coverage, nor does it give any 'when not to use' guidance. An agent can infer the purpose but must decide on selection criteria without direct help.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_redirectsA

Trace the redirect chain for each URL and flag chains longer than one hop, redirect loops, and URLs that resolve to a 4xx/5xx. Use after a site migration or a URL-structure change.

ParametersJSON Schema

Name	Required	Description	Default
`urls`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral disclosure burden. It clearly discloses what the tool does: traces chains, flags one-hop violations, loops, and error responses. It could add operational details like network cost or rate limits, but the core behavior is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no filler, and the main behavior is front-loaded. The second sentence supplies a practical trigger for use. Every part earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with an output schema present, the description covers what the tool does and when to use it. It does not fully cover input format details, but the missing information is minor given the low complexity and available output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds little about the 'urls' parameter beyond saying 'for each URL.' It does not clarify expected URL format (absolute vs relative), whether schemes are required, or any limits on list length, so the agent gets almost no parameter guidance beyond the bare schema type.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Trace the redirect chain for each URL' and names concrete detection outcomes (long chains, loops, 4xx/5xx). This is distinct from siblings like fetch_sitemap or audit_urls, making the tool's purpose immediately clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use after a site migration or a URL-structure change,' which gives a clear context for when this tool is appropriate. It does not mention alternatives or when not to use it, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

fetch_sitemapA

Fetch and parse a sitemap.xml, following sitemap-index nesting, and return every page URL it declares. Call this first when auditing a site you do not have a URL list for.

ParametersJSON Schema

Name	Required	Description	Default
`sitemap_url`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral burden. It discloses that the tool follows sitemap-index nesting and returns every declared page URL, which are meaningful behavioral details beyond what the schema shows. It does not mention failure modes or network behavior, but for a straightforward fetch-and-parse read operation this is reasonably transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The first sentence states what the tool does and the second gives usage guidance. The most important behavioral details are front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with an output schema present, the description is complete: it explains what the tool does, how it behaves with index nesting, what it returns, and when to call it. Nothing essential for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description must compensate. It indirectly clarifies that sitemap_url should point to a sitemap.xml and that index nesting is followed, but it does not explicitly describe the URL format, required scheme, or example values. Because the single parameter is highly self-evident from the tool name and description, this is adequate but not enriched.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Fetch and parse a sitemap.xml' and the specific outcome: 'return every page URL it declares.' It also mentions the non-obvious behavior of following sitemap-index nesting, which distinguishes this from simply fetching one XML file. The phrase 'Call this first when auditing a site' also separates it from siblings like audit_urls and sitemap_coverage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit guidance: 'Call this first when auditing a site you do not have a URL list for.' This clearly tells an agent when to use it. However, it does not name alternative tools or explicitly state when not to use it, so it falls just short of full usage differentiation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sitemap_coverageA

Compare a sitemap against a list of URLs you know exist (e.g. from the filesystem or a crawl) and report which are missing from the sitemap and which the sitemap declares but are unreachable. Missing pages are pages Google is never told about.

ParametersJSON Schema

Name	Required	Description	Default
`verify`	No
`known_urls`	Yes
`sitemap_url`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose that the tool checks reachability and reports missing/unreachable URLs, which is meaningful. However, it does not explain the 'verify' behavior, whether network requests are made to each known URL, or any side effects such as rate-limit impact or request costs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences cover the operation, inputs, outputs, and practical significance with no filler. The core comparison is front-loaded, and every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so describing return values is not necessary. The description is adequate for a straightforward comparison tool, but it omits the semantics of the optional 'verify' parameter and does not provide guidance on how this tool relates to siblings such as audit_urls or check_redirects, which would help an agent choose correctly in more ambiguous cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds some meaning by indicating 'sitemap' maps to sitemap_url and 'list of URLs you know exist' maps to known_urls. However, the 'verify' parameter is entirely unexplained despite being a schema property with a default value, and the mapping from description to parameters remains implicit rather than explicit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('compare') with clear resources: a sitemap and a list of known URLs. It precisely defines the two reported outcomes—URLs missing from the sitemap and sitemap entries that are unreachable—and the final sentence explains why this matters. It is clearly distinct from siblings like fetch_sitemap or audit_urls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear scenario for when to use the tool: when you have a sitemap and a separate list of URLs known to exist, such as from a filesystem or crawl. It does not explicitly name alternatives or exclusion conditions, but the context is sufficient for an agent to identify this as the coverage-comparison tool among the siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

4 tool updatesv1.0.0Sep 3, 2026
- First observedaudit_urls
- First observedcheck_redirects
- First observedfetch_sitemap
- First observedsitemap_coverage

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A3.8/5.0

Disambiguation4/5

Each tool targets a distinct phase of an SEO audit: sitemap fetching, page-level auditing, sitemap coverage comparison, and redirect tracing. The main overlap is that audit_urls already reports redirect chains and broken status codes, which overlaps with check_redirects.

Naming Consistency4/5

Three tools follow a clear verb_noun pattern (fetch_sitemap, audit_urls, check_redirects), but sitemap_coverage is a noun_noun exception. The inconsistent name is still readable and does not create real confusion.

Tool Count5/5

Four tools is a well-scoped size for a focused SEO audit server. Each tool has a clear job, and there is no redundant filler or overwhelming number of endpoints.

Completeness3/5

The server covers sitemap parsing, on-page/technical issue auditing, sitemap coverage, and redirects, but it lacks a site-crawling or internal-link-discovery tool, which is needed to find URLs not listed in a sitemap. This is a notable gap for a full audit, though the core workflow is usable with an existing URL list.

Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

GitHub Repository

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