seo-audit-mcp
seo-audit-mcp
Claude(または任意のMCPクライアント)に、ライブサイトの技術的SEO監査(サイトマップのカバレッジ、ページごとの問題、リダイレクトチェーン)の能力を提供するMCPサーバーです。
平易な言葉で質問すると — "mortgagecalculatortools.comを監査して、Googleに伝えられていないページを教えて" — モデルがツールを呼び出し、サイトをクロールし、具体的な答えを返します。
解決する問題
サイトのsitemap.xmlは、どのページが存在するかをGoogleに伝える方法です。ページがそこにない場合、エラーも警告も発生しません — そのページは単にインプレッションが蓄積されることがありません。手動で確認するには、ファイルシステムの一覧をXMLファイルと差分比較する必要があるため、実際には誰も行いません。
ケーススタディ:正しいと判明した25ページのギャップ
このツールを最初に適用したサイトでは、ディスク上に125個のHTMLファイルがあり、サイトマップには100個のURLがありました。25ページのギャップ — バグとして報告され、誰かに割り当てられる類の発見です。
sitemap_coverageの1回の呼び出しでギャップが浮かび上がり、サンプルに対するaudit_urlsの1回の呼び出しで説明がつきました:25ページすべてが<meta name="robots" content="noindex, follow">を保持していました。それらは意図的にインデックスから除外された2つのコンテンツクラスターであり、サイトマップがそれらを除外するのはまったく正しいことでした。その後ファイルシステムと照合:ディスク上に25のnoindexページがあり、同じ25ページがサイトマップに存在せず、noindexページが誤って含まれることはゼロでした。完璧な整合性です。
それが有用な結果です。カバレッジの数値だけ("125 vs 100")は欠陥と読まれ、誰かの1日分の時間を費やします。カバレッジにページごとのnoindexステータスを組み合わせれば、質問は1分で解決します。このツールは、見つける実際のギャップと同じくらい、排除する誤報にも価値があります — そのためaudit_urlsはURLを数えるだけでなく、ページごとにnoindexを報告します。
Related MCP server: web-audit-mcp
ツール
Tool | 機能 |
|
|
| URLを並行してクロールし、ページごとの問題を報告します:壊れたステータス、リダイレクトチェーン、 |
| サイトマップを、存在すると分かっているURLのリストと差分比較 → サイトマップから欠落しているもの、宣言されているが無効なもの |
| リダイレクトチェーンを追跡し、マルチホップチェーンと4xx/5xxで終わるチェーンにフラグを立てます — URL構造の変更後に使用します |
すべてのツールは、ページごとのissuesリストと集計されたissue_summaryを持つ構造化JSONを返すため、モデルは生のHTMLを読み直す代わりに件数を基に推論できます。
インストール
pip install -e .Python 3.10+が必要です。依存関係:mcp>=2.0.0、httpx。
Claude Codeに接続する
プロジェクトの.mcp.jsonに追加します(またはグローバルに使用する場合は~/.claude.json):
{
"mcpServers": {
"seo-audit": {
"command": "python",
"args": ["-m", "seo_audit_mcp"]
}
}
}Claude Desktopでは、同じブロックをclaude_desktop_config.jsonに置きます。
あとは質問するだけです:
https://example.com/sitemap.xmlのサイトマップを取得し、最初の20 URLを監査し、問題を頻度別に要約してください。
直接実行する
python -m seo_audit_mcp # stdio transport設計ノート
デモと、クライアントの本番サイトに向けられるものとの違いを生む、特筆すべき3つの決定事項があります:
クロールは設計上レート制限されています。 fetch_manyは16の同時リクエストに制限されたasyncio.Semaphoreの背後で実行され、すべてのツールが入力を制限します。その上限がないと、500 URLのサイトマップは同時に500のソケットを開き、対象ホストへの攻撃とみなされるでしょう。クロールは対象サイトが負担するコストであるため、上限はツール面から引き上げることはできません。
取得失敗によって実行が中止されることはありません。 fetch_oneはhttpx.HTTPErrorを捕捉し、例外を発生させる代わりに返されたPageAuditに記録します。200 URLのクロールでの1つの死んだホストは、199の良い結果を失う代わりに1行を劣化させるだけです。
解析は意図的に寛容です。 実際のHTMLは不正な形式であることが多いため、厳格なパーサーがクロール中に例外を発生させるのは危険です。抽出器はNoneを返す寛容な正規表現で、例外は投げません — ただし罠は処理されます:<script>と<style>の本文は、単語数と見出し抽出の前に除去されるため、JS文字列リテラル内の<h1>は見出しとして数えられず、相対canonicalはページURLに対して解決されます。
normalize_urlは意図的に末尾のスラッシュを除去しません:/aと/a/は実際に異なるページになり得るため、それらをまとめると、このツールが表面化するために存在する重複コンテンツの問題が隠れてしまいます。
テスト
pip install -e ".[dev]"
pytestこのスイートはネットワーク不要です — HTTPはhttpx.MockTransportを通じて実行されるため、CIでも飛行機内でも動作します。本番で問題になる解析のエッジケースをカバーしています:スクリプトに埋め込まれた見出し、名前空間のないサイトマップ、相対canonical、200ステータスでスタイル付きHTML 404を返すサイトマップURL、非HTMLコンテンツタイプが「タイトルがない」ページとして誤って報告されるケース。
ライセンス
MIT
Available Tools
4 toolsaudit_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.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | ||
| concurrency | No | ||
| timeout_seconds | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| sitemap_url | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| verify | No | ||
| known_urls | Yes | ||
| sitemap_url | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
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.
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.
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.
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.
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.
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.
4 tool updates
v1.0.0- First observed
audit_urls - First observed
check_redirects - First observed
fetch_sitemap - First observed
sitemap_coverage
TDQS
Scored across 4 tools
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.
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.
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.
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
Related MCP Connectors
- CrawlieOAuthapp.crawlie
Technical SEO + GEO (AI-search) site audits: hosted crawls, prioritized fixes, report diffs.
Audit public webpages and supplied markup for HTML, CSS, SEO, JSON-LD, and link issues.
Audit any site's AI visibility from your assistant: crawler access, rendering, and schema.
- seegeoOAuthcom.see-geo
Audit any website for AI visibility: graded report, findings with fixes, AI crawler access check.
Related MCP Servers
- AlicenseAqualityDmaintenanceEnables SEO auditing and site analysis by crawling websites, identifying issues, and generating reports like sitemaps and markdown exports.59 npm4MIT
- FlicenseNot gradedqualityDmaintenanceEnables auditing of websites for performance, SEO, accessibility, security, and mobile readiness, with tools to validate URLs, run page audits, save results, and retrieve reports.1-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to crawl and audit websites for SEO issues, returning structured JSON reports with errors, warnings, and key statistics.MIT
- FlicenseNot gradedqualityDmaintenanceAudits any website for SEO issues, providing scored health checks, schema validation, and performance analysis through AI assistants.-