内容
> [!WARNING]
> **Deprecated and no longer maintained.** GEO Analyzer's AI-search content analysis has been consolidated into **[SEO Audit Console](https://github.com/houtini-ai/seo-audit)** (`npm i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.
---
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<img src="https://raw.githubusercontent.com/houtini-ai/geo-analyzer/main/assets/logo.png" width="120" height="120" alt="GEO Analyzer" />
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# GEO Analyzer
[](https://www.npmjs.com/package/@houtini/geo-analyzer)
[](https://registry.modelcontextprotocol.io)
[](https://snyk.io/test/github/houtini-ai/geo-analyzer)
[](https://opensource.org/licenses/MIT)
Content analysis for AI search visibility. Measures what actually matters for getting cited by ChatGPT, Claude, Perplexity, and Google AI Overviews.
<p align="center">
<a href="https://glama.ai/mcp/servers/@houtini-ai/geo-analyzer">
<img width="380" height="200" src="https://glama.ai/mcp/servers/@houtini-ai/geo-analyzer/badge" alt="GEO Analyzer MCP server" />
</a>
</p>
> **Quick Navigation**
>
> [What it does](#what-it-does) | [Installation](#installation) | [Usage examples](#usage-examples) | [Output](#output) | [Tools](#tools) | [Troubleshooting](#troubleshooting) | [Research foundation](#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.
## Installation
### Claude Desktop
Add to your `claude_desktop_config.json`:
```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.json`
- macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
- Linux: `~/.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:
```bash
claude mcp add -e ANTHROPIC_API_KEY=sk-ant-... -s user geo-analyzer -- npx -y @houtini/geo-analyzer@latest
```
Verify with:
```bash
claude mcp get geo-analyzer
```
You should see `Status: Connected`.
### Requirements
- Node.js 20+
- Anthropic API key ([console.anthropic.com](https://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/article
```
### Analyse 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=summary
```
## Output
### 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 |
|-----------|----------|-------------|
| `url` | Yes | URL to analyse |
| `query` | No | Topic context for relevance scoring |
| `output_format` | No | `detailed` (default) or `summary` |
### analyze_text
Analyses pasted content directly.
| Parameter | Required | Description |
|-----------|----------|-------------|
| `content` | Yes | Text to analyse (min 500 chars) |
| `query` | No | Topic context for relevance scoring |
| `output_format` | No | `detailed` (default) or `summary` |
## 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):**
```json
{
"env": {
"GEO_WORKER_URL": "https://...",
"JINA_API_KEY": "jina_..."
}
}
```
**New (v2.x):**
```json
{
"env": {
"ANTHROPIC_API_KEY": "sk-ant-..."
}
}
```
## Development
```bash
git clone https://github.com/houtini-ai/geo-analyzer.git
cd geo-analyzer
npm install
npm run build
```
## Research 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
[arxiv.org/abs/2311.09735](https://arxiv.org/abs/2311.09735)
### 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](https://dejan.ai/blog/how-big-are-googles-grounding-chunks/)
[dejan.ai/blog/googles-ranking-signals](https://dejan.ai/blog/googles-ranking-signals/)
---
MIT License - [Houtini.ai](https://houtini.ai)
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