seo-audit-mcp
Enables auditing of a live website's technical SEO, including sitemap coverage, per-page issues, and redirect chains.
README
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.
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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
E2B
Using MCP to run code via e2b.