A powerful MCP (Model Context Protocol) server that provides comprehensive SEO analysis using DataForSEO API with advanced PageRank and internal link structure analysis powered by Kuzu graph database.
- OnPage SEO Analysis - Technical SEO audit, content optimization, performance analysis
- Keyword Research - Search volume data, competition analysis, SERP analysis
- Competitor Intelligence - Domain analysis, content gap analysis, competitive positioning
- Comprehensive Auditing - Multi-dimensional analysis with priority scoring
- PageRank Calculation - Authority analysis using Kuzu graph database
- Internal Link Optimization - Link equity distribution and structure analysis
- Pillar Page Identification - Find high-authority pages for content strategy
- Orphaned Page Detection - Discover pages missing from internal linking
- Link Graph Visualization - Complete internal link structure mapping
# Install directly from GitHub repository
uvx --from git+https://github.com/slamer59/mcp-seo mcp-seo
# Or install in development mode
uvx pip install git+https://github.com/slamer59/mcp-seo# Clone the repository
git clone https://github.com/slamer59/mcp-seo
cd mcp-seo
# Install with uvx
uvx pip install -e .
# Or with uv (if you have uv installed)
uv pip install -e .# Install from PyPI (when published)
uvx install mcp-seo
# Or with pip
pip install mcp-seoAdd to your Claude Code/OpenCoder MCP configuration:
{
"mcpServers": {
"mcp-seo": {
"command": "uvx",
"args": ["--from", "git+https://github.com/slamer59/mcp-seo", "mcp-seo"],
"env": {
"DATAFORSEO_LOGIN": "your_login",
"DATAFORSEO_PASSWORD": "your_password"
}
}
}
}- Sign up at DataForSEO
- Get your API credentials
- Set environment variables:
export DATAFORSEO_LOGIN="your_login"
export DATAFORSEO_PASSWORD="your_password"export DEFAULT_LOCATION_CODE=2840 # United States
export DEFAULT_LANGUAGE_CODE="en" # Englishonpage_analysis_start- Start comprehensive OnPage SEO analysiskeyword_analysis- Keyword research and search volume analysisserp_analysis- SERP results and ranking analysisdomain_analysis- Domain performance and metrics analysiscompetitor_comparison- Compare multiple domainscontent_gap_analysis- Find content opportunities vs competitorscomprehensive_seo_audit- Full multi-dimensional SEO audit
Calculate PageRank scores and analyze internal link authority distribution.
{
"domain": "https://example.com",
"max_pages": 100,
"damping_factor": 0.85,
"use_sitemap": true
}Returns: Complete analysis with pillar pages, orphaned pages, and optimization recommendations.
Build and analyze internal link structure from sitemap or custom URLs.
{
"domain": "https://example.com",
"max_pages": 50,
"use_sitemap": true
}Returns: Link graph statistics and structural metrics.
Identify pages with highest PageRank scores for content strategy.
{
"domain": "https://example.com",
"percentile": 90.0,
"limit": 10
}Returns: Top authority pages with strategic recommendations.
Find pages with no incoming internal links that need optimization.
{
"domain": "https://example.com"
}Returns: Orphaned pages categorized by URL structure with fix recommendations.
Generate comprehensive internal linking optimization plan.
{
"domain": "https://example.com",
"max_pages": 100
}Returns: Priority-based optimization plan with specific actionable recommendations.
# Through MCP in Claude Code/OpenCoder
"Run a comprehensive SEO audit for https://example.com focusing on technical SEO and content optimization"# Analyze internal link structure
"Analyze the PageRank and internal linking structure for https://mysite.com, identify pillar pages and orphaned content"
# Find optimization opportunities
"Find internal linking opportunities for https://mysite.com and create an optimization plan"# Identify high-authority pages
"Find the top 10 pillar pages on https://mysite.com and suggest how to leverage them for content strategy"
# Fix structural issues
"Identify orphaned pages on https://mysite.com and recommend how to integrate them into the site structure"# Install with test dependencies
uv pip install -e ".[test]"
# Run tests
pytest tests/ -v
# Run with coverage
pytest tests/ --cov=mcp_seo --cov-report=html- 52+ Tests covering all functionality
- Unit Tests for core components (KuzuManager, PageRankAnalyzer, LinkGraphBuilder)
- Integration Tests for end-to-end workflows
- Async Testing with proper mocking
- FastMCP Server - MCP protocol implementation
- DataForSEO Client - Professional SEO data integration
- Kuzu Graph Database - High-performance graph analysis
- PageRank Engine - Mathematical authority calculation
- Link Analysis - Internal structure optimization
fastmcp>=2.12.2- MCP server frameworkdataforseo-client>=2.0.0- SEO data APIkuzu>=0.5.0- Graph database for PageRankaiohttp>=3.9.0- Async web crawlingbeautifulsoup4>=4.12.0- HTML parsingnumpy>=1.24.0- Mathematical operationspydantic>=2.11.7- Data validation
- DataForSEO Integration - Enterprise SEO data provider
- Advanced Mathematics - Proper PageRank algorithm implementation
- Graph Database - Kuzu for high-performance link analysis
- Comprehensive Testing - 52+ tests with proper async handling
- MCP Protocol - Native integration with Claude Code, OpenCoder
- Structured Data - Clean JSON responses perfect for AI analysis
- Actionable Insights - AI can directly implement recommendations
- Batch Operations - Efficient multi-domain analysis
- Sitemap.xml Processing - Works with all modern frameworks
- Beautiful Soup Parsing - Handles server-side rendered content
- Async Architecture - Non-blocking operations for large sites
- Extensible - Ready for Playwright integration for SPA analysis
- Identify high-authority pillar pages for content hubs
- Find orphaned content that needs internal linking
- Optimize link equity distribution across site sections
- Complete technical audit with DataForSEO professional data
- Internal link structure analysis and optimization
- Page authority analysis for navigation planning
- Multi-domain PageRank comparison
- Competitor link structure analysis
- Content gap identification with authority metrics
- Scalable multi-client SEO analysis
- Automated reporting with actionable insights
- Integration with AI workflows for optimization
- Repository: https://github.com/slamer59/mcp-seo
- Documentation: Full API Documentation
- DataForSEO: https://dataforseo.com/
- MCP Protocol: https://modelcontextprotocol.io/
MIT License - see LICENSE file for details.
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