GEO Analysis for AI SEO
This server analyzes web content and text for AI search optimization, helping you understand how well your content will be cited by AI systems like ChatGPT, Claude, Perplexity, and Google AI Overviews.
Two analysis modes:
Analyze a URL: Fetch and evaluate any publicly accessible web page
Analyze text: Directly paste content (minimum 500 characters) in markdown, plain text, or HTML
Both modes assess AI slop detection, writing quality, E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness), and actionability.
Key metrics evaluated:
Claim density (target: 4+ claims per 100 words)
Information density and answer frontloading
Semantic triples and entity recognition
Sentence structure (optimal 15–20 word average)
Scores generated (0–10):
Overall content quality
Extractability (how easily AI can extract facts)
Readability (structure quality for AI parsing)
Citability (how quotable and attributable)
Additional options:
Add a topic/query for relevance scoring
Choose between detailed output (with prioritized recommendations, before/after examples) or a condensed summary
All analysis runs locally without data leaving your system
Evaluates content against metrics such as sentence length and extractability to improve the likelihood of being featured in Google AI Overviews.
Measures content structure and extractable facts to enhance search visibility and attribution within Perplexity's AI-powered search results.
Deprecated and no longer maintained. GEO Analyzer's AI-search content analysis has been consolidated into SEO Audit Console (npm i @houtini/seo-audit-console) — which scores AI-Overview citation, passage relevance, agent readiness and content extractability alongside a full technical SEO audit, all in one MCP. Please migrate there.
GEO Analyzer
Content analysis for AI search visibility. Measures what actually matters for getting cited by ChatGPT, Claude, Perplexity, and Google AI Overviews.
Quick Navigation
What it does | Installation | Usage examples | Output | Tools | Troubleshooting | Research foundation
What It Does
GEO Analyzer examines content for the signals AI systems use when selecting sources to cite:
Claim Density - Extractable facts per 100 words
Information Density - Word count vs predicted AI coverage
Answer Frontloading - How quickly key information appears
Semantic Triples - Structured (subject, predicate, object) relationships
Entity Recognition - Named entities AI can reference
Sentence Structure - Optimal length for AI parsing
The analysis runs locally using Claude Sonnet 4.5 for semantic extraction. No external services, no data leaving your machine.
Related MCP server: agentaeo-mcp-server
Installation
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"geo-analyzer": {
"command": "npx",
"args": ["-y", "@houtini/geo-analyzer@latest"],
"env": {
"ANTHROPIC_API_KEY": "sk-ant-..."
}
}
}
}Config locations:
Windows:
%APPDATA%\Claude\claude_desktop_config.jsonmacOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonLinux:
~/.config/Claude/claude_desktop_config.json
Restart Claude Desktop after saving.
Claude Code (CLI)
Claude Code uses a different registration mechanism -- it doesn't read claude_desktop_config.json. Use claude mcp add instead:
claude mcp add -e ANTHROPIC_API_KEY=sk-ant-... -s user geo-analyzer -- npx -y @houtini/geo-analyzer@latestVerify with:
claude mcp get geo-analyzerYou should see Status: Connected.
Requirements
Node.js 20+
Anthropic API key (console.anthropic.com)
Usage Examples
Analyse a Published URL
Analyse https://example.com/article for "topic keywords"The topic context helps score relevance but isn't required:
Analyse https://example.com/articleAnalyse Text Directly
Paste content for analysis (minimum 500 characters):
Analyse this content for "sim racing wheels":
[Your content here]Summary Mode
Get condensed output without detailed recommendations:
Analyse https://example.com/article with output_format=summaryOutput
Scores (0-10)
Score | Measures |
Overall | Weighted average of all factors |
Extractability | How easily AI can extract facts |
Readability | Structure quality for AI parsing |
Citability | How quotable and attributable |
Key Metrics
Information Density:
Word count with coverage prediction
Optimal range: 800-1,500 words
Pages under 1K words: ~61% AI coverage
Pages over 3K words: ~13% AI coverage
Answer Frontloading:
Claims and entities in first 100/300 words
First claim position
Score indicating answer immediacy
Claim Density:
Target: 4+ claims per 100 words
Extractable facts, statistics, measurements
Sentence Length:
Target: 15-20 words average
Matches Google's ~15.5 word chunk extraction
Recommendations
Prioritised suggestions with:
Specific locations in content
Before/after examples
Rationale based on research
Tools
analyze_url
Fetches and analyses published web pages.
Parameter | Required | Description |
| Yes | URL to analyse |
| No | Topic context for relevance scoring |
| No |
|
analyze_text
Analyses pasted content directly.
Parameter | Required | Description |
| Yes | Text to analyse (min 500 chars) |
| No | Topic context for relevance scoring |
| No |
|
Troubleshooting
"ANTHROPIC_API_KEY is required"
Add your API key to the env section in config.
"Cannot find module" after config change Restart Claude Desktop completely.
"Content too short" Minimum 500 characters required for meaningful analysis.
Paywalled content returns errors The analyser can only access publicly available pages.
Performance
URL analysis: ~8-10 seconds
Text analysis: ~5-7 seconds
Cost: ~$0.14 per analysis (Sonnet 4.5)
Migration from v1.x
v2.0 removed external dependencies. Update your config:
Old (v1.x):
{
"env": {
"GEO_WORKER_URL": "https://...",
"JINA_API_KEY": "jina_..."
}
}New (v2.x):
{
"env": {
"ANTHROPIC_API_KEY": "sk-ant-..."
}
}Development
git clone https://github.com/houtini-ai/geo-analyzer.git
cd geo-analyzer
npm install
npm run buildResearch Foundation
The analysis methodology draws from peer-reviewed research and empirical studies:
MIT GEO Paper (2024)
Aggarwal et al., "GEO: Generative Engine Optimization" - ACM SIGKDD
Key findings applied:
Claim density target of 4+ per 100 words
Optimal sentence length of 15-20 words
40% improvement in AI citation rates with extractability focus
Dejan AI Grounding Research (2025)
Empirical analysis of 7,060 queries and 2,275 pages
Key findings applied:
~2,000 word total grounding budget per query
Rank #1 source gets 531 words (28% of budget)
Rank #5 source gets 266 words (13% of budget)
Average extraction chunk: 15.5 words
Pages <1K words: 61% coverage
Pages 3K+ words: 13% coverage
dejan.ai/blog/how-big-are-googles-grounding-chunks
dejan.ai/blog/googles-ranking-signals
MIT License - Houtini.ai
Available Tools
2 toolsanalyze_textB
Analyze pasted text content for AI search optimization. Performs comprehensive content quality analysis including AI slop detection, writing quality, E-E-A-T signals, data points, originality, and actionability.
Inputs: content (required), query, output_format.
analyze_urlC
Analyze a published URL for AI search optimization. Performs comprehensive content quality analysis including AI slop detection, writing quality, E-E-A-T signals, and actionability.
Inputs: url (required), query, output_format.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: analyze_text for pasted text content and analyze_url for published URLs. While their analysis components overlap significantly (both include AI slop detection, writing quality, E-E-A-T signals, and actionability), the input type distinction prevents confusion. The only minor ambiguity is that analyze_text mentions additional features like data points and originality not listed for analyze_url.
Both tools follow a perfect verb_noun pattern with consistent snake_case naming: analyze_text and analyze_url. The naming is completely predictable and readable, with no deviations in style or convention across the tool set.
With only 2 tools for a server named 'GEO Analysis for AI SEO' that suggests geographical and SEO analysis capabilities, the tool count feels too thin. The server's name implies broader functionality (potentially geographical data analysis, keyword research, competitor analysis, etc.), but the tools only cover content analysis of text and URLs, leaving significant gaps in the apparent domain scope.
The tool set is severely incomplete for the server's stated purpose of 'GEO Analysis for AI SEO'. While the two tools provide content quality analysis, there are obvious gaps: no geographical analysis tools (e.g., location-based SEO, regional keyword analysis), no SEO-specific tools (e.g., keyword research, backlink analysis, ranking tracking), and no AI SEO optimization beyond content assessment. This will likely cause agent failures when trying to perform comprehensive GEO or SEO tasks.
Maintenance
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