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SEO Research MCP

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DataSEO MCP

DataSEO MCPは、AIアシスタントでの実用的なSEO調査のためのModel Context Protocolサーバーです。Ahrefsの無料SEOデータ、CAPTCHAプロバイダーのフォールバック、およびオプションのOpenRouterを利用したクエリプランニングを、少数のMCPツールセットの背後で統合しています。

[!CAUTION] このプロジェクトは教育および研究目的のみを対象としています。Ahrefs、CapSolver、Anti-Captcha、OpenRouterを含むサードパーティサービスと対話します。ユーザーは、適用されるすべての利用規約を遵守する責任があります。

機能

ツール

目的

プロンプト例

get_backlinks_list

バックリンクの概要と上位バックリンク行

"suparank.ioのバックリンクを表示して"

keyword_generator

キーワードと質問のアイデア

"オンボーディング用のSaaS SEOキーワードを見つけて"

get_traffic

オーガニックトラフィックの推定

"ege.mdのトラフィックを推定して"

keyword_difficulty

KD（キーワード難易度）とSERPスナップショット

"AI SEOツールの難易度を確認して"

ai_search_queries

検索意図別のAIクエリアイデア

"SaaS SEO向けのAI検索クエリを生成して"

domain_overview

1ドメインのバックリンク + トラフィックの概要

"suparank.ioを要約して"

compare_domains

2〜5ドメインの比較

"suparank.ioとahrefs.comを比較して"

backlink_opportunities

競合他社のバックリンクソースのギャップ

"自分のドメインのバックリンクギャップを見つけて"

seo_content_brief

SERP + AI支援によるコンテンツブリーフ

"AI SEO監査のコンテンツブリーフを作成して"

DataSEO MCPはEge Beseによって保守されています。AI SEOおよびランク追跡ワークフローについては、Suparankを参照してください。

Related MCP server: SEO Insights MCP Server

インストール

uvx --python 3.10 dataseo-mcp

ローカル開発用:

git clone https://github.com/egebese/dataseo-mcp.git
cd dataseo-mcp
uv sync
uv run dataseo-mcp

レガシーな seo-mcp コマンドは、互換性エイリアスとして引き続き公開されています。

設定

Ahrefsを利用したツールには、少なくとも1つのCAPTCHAプロバイダーが必要です:

export CAPSOLVER_API_KEY="your-capsolver-key"
# or
export ANTICAPTCHA_API_KEY="your-anticaptcha-key"

両方が設定されている場合、CapSolverが最初に試行され、Anti-Captchaがフォールバックとして使用されます。AIツールはオプションです:

export OPENROUTER_API_KEY="your-openrouter-key"
export OPENROUTER_MODEL="openai/gpt-4o-mini"  # optional

便利なランタイムオーバーライド:

変数

デフォルト

目的

DATASEO_CACHE_DIR

~/.cache/dataseo-mcp

シグネチャキャッシュの場所

DATASEO_REQUEST_TIMEOUT

30

HTTPタイムアウト（秒）

DATASEO_MAX_POLLING_ATTEMPTS

120

CAPTCHAポーリングの上限

OPENROUTER_BASE_URL

https://openrouter.ai/api/v1

OpenAI互換のAIエンドポイント

MCPセットアップ

Claude Desktop / Cursorスタイルの設定:

{
  "mcpServers": {
    "dataseo": {
      "command": "uvx",
      "args": ["--python", "3.10", "dataseo-mcp"],
      "env": {
        "CAPSOLVER_API_KEY": "YOUR_CAPSOLVER_KEY",
        "ANTICAPTCHA_API_KEY": "YOUR_ANTICAPTCHA_KEY",
        "OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY"
      }
    }
  }
}

Claude Code:

claude mcp add dataseo --scope user -- uvx --python 3.10 dataseo-mcp

VS Code MCP設定:

{
  "servers": {
    "dataseo": {
      "command": "uvx",
      "args": ["--python", "3.10", "dataseo-mcp"],
      "env": {
        "CAPSOLVER_API_KEY": "YOUR_CAPSOLVER_KEY"
      }
    }
  }
}

CAPTCHAプロバイダーのキーは1つだけ必要です。AI支援によるクエリ生成やコンテンツブリーフが必要な場合にのみ OPENROUTER_API_KEY を追加してください。

APIリファレンス

get_backlinks_list(domain)

戻り値:

{
  "overview": {
    "domainRating": 76,
    "backlinks": 1500,
    "refDomains": 300
  },
  "backlinks": [
    {
      "anchor": "DataSEO MCP",
      "domainRating": 76,
      "title": "Example page",
      "urlFrom": "https://source.example/page",
      "urlTo": "https://example.com/page",
      "edu": false,
      "gov": false
    }
  ]
}

keyword_generator(keyword, country="us", search_engine="Google")

既存の label / value 形式でキーワードと質問のアイデアを返します。

get_traffic(domain_or_url, country="None", mode="subdomains")

トラフィック履歴、トラフィック概要、上位ページ、国、キーワードを返します。レガシーな costMontlyAvg フィールドは保持されており、costMonthlyAvg も含まれています。

keyword_difficulty(keyword, country="us")

キーワード難易度スコアと、利用可能な指標を含むオーガニックSERP行を返します。

ai_search_queries(keyword, count=10, model="openai/gpt-4o-mini", language="en")

重複排除されたAI生成クエリを返します:

{
  "keyword": "ai seo audit",
  "queries": [
    {"query": "what is an AI SEO audit", "intent": "informational"},
    {"query": "best AI SEO audit tools", "intent": "commercial"}
  ],
  "model_used": "openai/gpt-4o-mini",
  "total_queries": 2
}

count は1から50の間で検証されます。有効な意図は informational（情報収集）、commercial（商用）、transactional（取引）、navigational（ナビゲーション）です。

追加ツール

  • domain_overview(domain, country="None"): 1ドメインのバックリンク概要とトラフィック概要。

  • compare_domains(domains, country="None"): 2〜5個のユニークなドメインを比較します。

  • backlink_opportunities(domain, competitors): ターゲットサンプルに存在しない競合他社のバックリンクソースをリストアップします。

  • seo_content_brief(keyword, country="us", count=12, model, language): キーワード難易度、SERP行、AI検索クエリ、推奨されるコンテンツの切り口を組み合わせます。

アーキテクチャ

server.py は意図的に軽量に設計されています。実装は以下のように分割されています:

  • services.py: MCPツールのオーケストレーションと公開される戻り値の形状。

  • schemas.py: Pydanticによる検証と正規化。

  • captcha.py: 制限付きポーリングを備えたCapSolver / Anti-Captchaフォールバック。

  • backlinks.py, keywords.py, traffic.py: Ahrefsエンドポイントアダプター。

  • ai.py: OpenRouter/OpenAI互換のクエリ生成。

  • cache.py: デフォルトで ~/.cache/dataseo-mcp に配置されるJSONシグネチャキャッシュ。

すべての外部HTTP境界はテストでモック化されています。

開発

uv sync
uv run pytest -q
uv run ruff check .
uv run python -m compileall -q src
uv run python -c "from seo_mcp.server import main"

トラブルシューティング

問題

修正

CAPTCHAプロバイダーが設定されていない

CAPSOLVER_API_KEY または ANTICAPTCHA_API_KEY を設定する

CAPTCHA解決に失敗した

プロバイダーの残高、キーの有効性、レート制限を確認する

AIツールがキー不足エラーを返す

OPENROUTER_API_KEY を設定する

SEOレスポンスが空

ドメインまたはキーワードがアップストリームソースによってインデックスされていない可能性がある

古いコマンドがドキュメント化されていない

dataseo-mcp を使用してください。seo-mcp もエイリアスとして機能します

ライセンス

MITライセンス（教育目的の通知付き）。元のフォークの帰属表示は LICENSE に保持されています。

Available Tools

4 tools
get_trafficC
Check the estimated search traffic for any website. 

Args:
    domain_or_url (str): The domain or URL to query
    country (str): The country to query, default is "None"
    mode (["subdomains", "exact"]): The mode to use for the query
Returns:
    Traffic data for the specified domain or URL
ParametersJSON Schema
NameRequiredDescriptionDefault
domain_or_urlYes
countryNoNone
modeNosubdomains

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are present, so the description carries the full burden. It does not disclose whether the tool is read-only, destructive, requires authentication, or has rate limits. For a data query tool, this is a significant gap.

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 concise at two sentences plus an Args/Returns list. It is front-loaded with the purpose and structured for easy scanning. No wasted words.

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

Completeness2/5

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

Given no output schema, the description only vaguely states 'Traffic data' without specifying structure. Combined with missing behavioral context, the description is incomplete for a 3-parameter tool.

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 description includes an Args section that lists parameters and their types, adding some meaning beyond the schema (e.g., domain_or_url is 'The domain or URL to query'). However, it does not explain the difference between 'subdomains' and 'exact' modes, nor the effect of the country parameter, beyond default values.

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

Purpose4/5

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

The description states 'Check the estimated search traffic for any website', which clearly identifies the verb and resource. It distinguishes from sibling tools like get_backlinks_list and keyword_difficulty by focusing on traffic estimation, but does not explicitly differentiate.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor does it specify prerequisites or exclusions. It simply states the tool's function without context for decision-making.

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

keyword_difficultyC

Get keyword difficulty for the specified keyword

ParametersJSON Schema
NameRequiredDescriptionDefault
keywordYes
countryNous

TDQS

C2.6/5.0
Behavior2/5

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

No annotations provided, so description must carry full burden. It does not disclose how difficulty is calculated, what unit/scale is used, or any side effects. Bare minimum.

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

Conciseness3/5

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

Single sentence of 8 words is concise but lacks substance. Appropriate length for the content, but more detail would improve informativeness.

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

Completeness2/5

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

Given no annotations, no output schema, and 2 params requiring explanation, the description is inadequate. Leaves agent guessing about return values, scope, and usage nuances.

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 has 0% description coverage. Description only mentions 'specified keyword' without explaining its meaning or format. Country parameter and default are not explained. Adds minimal value to schema.

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

Purpose4/5

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

The description 'Get keyword difficulty for the specified keyword' clearly states the action and resource. It is distinct from sibling tools like get_backlinks_list and get_traffic, though sibling differentiation is implicit rather than explicit.

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

Usage Guidelines2/5

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

No guidance on when to use this tool compared to alternatives. Lacks context about prerequisites or typical use cases.

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

keyword_generatorC

Get keyword ideas for the specified keyword

ParametersJSON Schema
NameRequiredDescriptionDefault
keywordYes
countryNous
search_engineNoGoogle

TDQS

C2.4/5.0
Behavior2/5

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

No annotations provided. Description only says 'get ideas' with no disclosure of behavior (e.g., return format, rate limits, data source).

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

Conciseness3/5

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

Extremely short, no fluff, but lacks essential details. Conciseness is achieved at the expense of completeness.

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

Completeness1/5

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

With 3 parameters, no output schema, and no annotations, the description is severely incomplete. No information on return values or side effects.

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

Parameters1/5

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

Schema coverage is 0% and description only mentions the keyword parameter, ignoring country and search_engine. Fails to compensate for missing parameter descriptions.

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

Purpose4/5

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

The description clearly states it returns keyword ideas for a given keyword. It distinguishes from sibling tools (backlinks, traffic, difficulty) but lacks specificity about the output format or scope.

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs. alternatives, no prerequisites, no context about typical use cases.

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.

  1. 4 tool updatesv1.0.0
    • First observedget_backlinks_list
    • First observedget_traffic
    • First observedkeyword_difficulty
    • First observedkeyword_generator
Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

B3.1/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: get_backlinks_list retrieves backlink data, get_traffic provides traffic estimates, keyword_difficulty assesses keyword competitiveness, and keyword_generator suggests related keywords. There is no overlap in functionality, making tool selection unambiguous.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with snake_case: get_backlinks_list, get_traffic, keyword_difficulty, keyword_generator. The naming is predictable and readable, with no deviations in style or convention.

Tool Count4/5

With 4 tools, the count is reasonable for an SEO research server, covering key areas like backlinks, traffic, and keywords. It is slightly lean but not insufficient, as these tools address core SEO analysis needs without being overwhelming.

Completeness3/5

The toolset covers essential SEO research functions but has notable gaps. For example, there are no tools for competitor analysis, content suggestions, or SERP features, which are common in SEO workflows. Agents can perform basic research but may lack comprehensive coverage for advanced tasks.

Maintenance

ActivityInactive
ResponsivenessSlow

Resources

Related MCP Connectors

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