SEO Research

DataSEO MCP

Give your AI assistant real SEO data. DataSEO MCP is a Model Context Protocol server that lets Claude, Cursor, and other MCP clients pull backlinks, keyword difficulty, traffic estimates, and keyword ideas from Ahrefs' free tools — plus optional AI query planning — just by asking in plain English.

No dashboards, no CSV exports. Ask "who links to suparank.io?" and get an answer inside your chat.

[!CAUTION] For educational and research use. It automates third-party services (Ahrefs, CapSolver, Anti-Captcha, OpenRouter). You are responsible for complying with their terms of service.

What you can ask

Talk to it in natural language — the assistant picks the right tool.

Maintained by Ege Bese. Built for the AI SEO and rank-tracking workflows behind Suparank.

Quick start

Run it with no install using uv:

export CAPSOLVER_API_KEY="your-capsolver-key"
uvx --python 3.10 dataseo-mcp

That's enough to use every SEO tool. See MCP Setup to wire it into your assistant.

For local development:

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

The legacy seo-mcp command still works as an alias.

Configuration

One CAPTCHA provider is required — it's how the Ahrefs-backed tools clear the Turnstile challenge:

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

If both are set, CapSolver is tried first and Anti-Captcha is the fallback.

AI tools are optional. ai_search_queries and seo_content_brief need OpenRouter; without it, the other tools still work and AI output is marked unavailable:

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

Runtime overrides:

MCP Setup

Claude Code:

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

Claude Desktop / Cursor (claude_desktop_config.json or equivalent):

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

VS Code (.vscode/mcp.json):

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

Add OPENROUTER_API_KEY only if you want the AI tools.

API Reference

get_backlinks_list(domain)

{
  "overview": { "domainRating": 76, "backlinks": 1500, "refdomains": 300 },
  "backlinks": [
    {
      "anchor": "Suparank",
      "domainRating": 71,
      "title": "The best AI SEO tools",
      "urlFrom": "https://source.example/best-seo-tools",
      "urlTo": "https://suparank.io/",
      "edu": false,
      "gov": false
    }
  ]
}

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

Keyword and question ideas in the label / value shape. Volume and difficulty come back as Ahrefs' bucketed estimates.

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

Traffic history, traffic summary, and top pages / countries / keywords. Both costMonthlyAvg and the legacy costMontlyAvg spelling are included.

keyword_difficulty(keyword, country="us")

A keyword difficulty score plus the organic SERP rows with available metrics.

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

{
  "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 is 1–50. Intents are informational, commercial, transactional, navigational.

Composite tools

• domain_overview(domain, country="None") — backlink overview + traffic summary for one domain.
• compare_domains(domains, country="None") — 2–5 unique domains side by side.
• backlink_opportunities(domain, competitors) — competitor backlink sources missing from the target's sample.
• seo_content_brief(keyword, country="us", count=12, model, language) — keyword difficulty, SERP rows, AI queries, and recommended content angles in one call.

How it works

server.py stays thin; the work is split into focused modules:

• services.py — tool orchestration and public return shapes.
• schemas.py — Pydantic validation and normalization.
• captcha.py — CapSolver / Anti-Captcha fallback with bounded polling.
• backlinks.py, keywords.py, traffic.py — Ahrefs endpoint adapters.
• ai.py — OpenRouter query generation.
• cache.py — JSON signature cache (default ~/.cache/dataseo-mcp).

Every external HTTP boundary is mocked in tests.

Development

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"

Troubleshooting

License

MIT with an educational-use notice. Original fork attribution is preserved in LICENSE.