dataseo-mcp
Health Pass
- License — License: NOASSERTION
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 174 GitHub stars
Code Pass
- Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Pass
- Permissions — No dangerous permissions requested
This MCP server provides SEO research capabilities inside AI-powered IDEs. It retrieves backlink data, keyword ideas, and traffic estimates by pulling information from Ahrefs.
Security Assessment
Overall risk: Medium. The static code scan of 12 files found no dangerous patterns, hardcoded secrets, or dangerous local permissions. However, the tool makes external network requests to third-party services and requires API keys for CAPTCHA-solving providers (CapSolver, Anti-Captcha) to function. Because it uses automated CAPTCHA solvers to fetch live data from Ahrefs, developers should be aware that this strongly risks violating Ahrefs' Terms of Service. The project's author explicitly notes it is for "educational and research purposes only" and places the burden of legal compliance entirely on the user.
Quality Assessment
The project is very active, with its most recent push being today, and has garnered solid community trust with 174 GitHub stars. The codebase is easy to install via standard Python packaging (`uvx`). The only notable health check flag is the license status, which is marked as "NOASSERTION." This means the repository lacks a clear open-source license, meaning the default, restrictive copyright rules technically apply.
Verdict
Use with caution: The code itself is safe, but relying on automated CAPTCHA bypassing to scrape third-party platforms poses significant ethical, legal, and Terms of Service compliance risks.
A free SEO research tool using Model Context Protocol (MCP) powered by Ahrefs data. Get backlink analysis, keyword research, traffic estimation, and more — directly in your AI-powered IDE.
DataSEO MCP
DataSEO MCP is a Model Context Protocol server for practical SEO research in AI
assistants. It combines Ahrefs free SEO data, CAPTCHA-provider fallback, and
optional OpenRouter-powered query planning behind a small set of MCP tools.
[!CAUTION]
This project is for educational and research purposes only. It interacts with
third-party services including Ahrefs, CapSolver, Anti-Captcha, and OpenRouter.
Users are responsible for complying with all applicable terms of service.
Features
| Tool | Purpose | Example prompt |
|---|---|---|
get_backlinks_list |
Backlink overview and top backlink rows | "Show backlinks for suparank.io" |
keyword_generator |
Keyword and question ideas | "Find SaaS SEO keywords for onboarding" |
get_traffic |
Organic traffic estimates | "Estimate traffic for ege.md" |
keyword_difficulty |
KD and SERP snapshot | "Check difficulty for AI SEO tools" |
ai_search_queries |
AI query ideas by search intent | "Generate AI search queries for SaaS SEO" |
domain_overview |
One-domain backlink + traffic summary | "Summarize suparank.io" |
compare_domains |
Compare 2-5 domains | "Compare suparank.io and ahrefs.com" |
backlink_opportunities |
Competitor backlink source gaps | "Find backlink gaps for my domain" |
seo_content_brief |
SERP + AI-assisted content brief | "Create a content brief for AI SEO audit" |
DataSEO MCP is maintained by Ege Bese. For AI SEO and
rank-tracking workflows, see Suparank.
Installation
uvx --python 3.10 dataseo-mcp
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 is still exposed as a compatibility alias.
Configuration
At least one CAPTCHA provider is required for Ahrefs-backed tools:
export CAPSOLVER_API_KEY="your-capsolver-key"
# or
export ANTICAPTCHA_API_KEY="your-anticaptcha-key"
If both are configured, CapSolver is tried first and Anti-Captcha is used as
fallback. AI tools are optional:
export OPENROUTER_API_KEY="your-openrouter-key"
export OPENROUTER_MODEL="openai/gpt-4o-mini" # optional
Useful runtime overrides:
| Variable | Default | Purpose |
|---|---|---|
DATASEO_CACHE_DIR |
~/.cache/dataseo-mcp |
Signature cache location |
DATASEO_REQUEST_TIMEOUT |
30 |
HTTP timeout in seconds |
DATASEO_MAX_POLLING_ATTEMPTS |
120 |
CAPTCHA polling cap |
OPENROUTER_BASE_URL |
https://openrouter.ai/api/v1 |
OpenAI-compatible AI endpoint |
MCP Setup
Claude Desktop / Cursor-style config:
{
"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 config:
{
"servers": {
"dataseo": {
"command": "uvx",
"args": ["--python", "3.10", "dataseo-mcp"],
"env": {
"CAPSOLVER_API_KEY": "YOUR_CAPSOLVER_KEY"
}
}
}
}
Only one CAPTCHA provider key is required. Add OPENROUTER_API_KEY only when
you want AI-assisted query generation or content briefs.
API Reference
get_backlinks_list(domain)
Returns:
{
"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")
Returns keyword and question ideas in the existing label / value shape.
get_traffic(domain_or_url, country="None", mode="subdomains")
Returns traffic history, traffic summary, top pages, countries, and keywords.
The legacy costMontlyAvg field is preserved and costMonthlyAvg is also
included.
keyword_difficulty(keyword, country="us")
Returns a keyword difficulty score and organic SERP rows with available metrics.
ai_search_queries(keyword, count=10, model="openai/gpt-4o-mini", language="en")
Returns deduplicated AI-generated queries:
{
"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 validated from 1 to 50. Valid intents are informational,commercial, transactional, and navigational.
Additional Tools
domain_overview(domain, country="None"): backlink overview plus traffic
summary for one domain.compare_domains(domains, country="None"): compares 2-5 unique domains.backlink_opportunities(domain, competitors): lists competitor backlink
sources not present in the target sample.seo_content_brief(keyword, country="us", count=12, model, language): combines
keyword difficulty, SERP rows, AI search queries, and recommended content
angles.
Architecture
server.py is intentionally thin. The implementation is split into:
services.py: MCP 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/OpenAI-compatible query generation.cache.py: JSON signature cache under~/.cache/dataseo-mcpby default.
All external HTTP boundaries are 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
| Problem | Fix |
|---|---|
| No CAPTCHA provider configured | Set CAPSOLVER_API_KEY or ANTICAPTCHA_API_KEY |
| CAPTCHA solving failed | Check provider balance, key validity, and rate limits |
| AI tool returns missing key error | Set OPENROUTER_API_KEY |
| Empty SEO response | Domain or keyword may not be indexed by the upstream source |
| Old command no longer documented | Use dataseo-mcp; seo-mcp still works as alias |
License
MIT with educational-use notice. Original fork attribution is preserved in
LICENSE.
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