bofusions-geo-mcp 1.1.0

Bofusions GEO MCP Server — AI Search Engine Optimization (GEO) analysis tools for MCP clients

Bofusions GEO MCP

AI Search Engine Optimization (GEO) Analysis Tools for MCP Clients

Optimize your website for AI-powered search engines — ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews.

GEO (Generative Engine Optimization) focuses on being the source AI models quote — not just ranking on Google.

Built by Bofusions

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Why GEO?

Traditional SEO	GEO (This Tool)
Optimize for Google crawlers	Optimize for AI model training data
Rank #1 on search results	Be the cited source in AI answers
Keywords & backlinks	Citability, brand authority, structured data
Google-focused	ChatGPT, Claude, Perplexity, Gemini, AIO

The market is shifting:

• AI-referred traffic grew +527% year-over-year
• GEO services market projected $7.3B by 2031
• AI traffic conversion rate 4.4x higher than organic

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Installation

# Run directly (recommended)
uvx bofusions-geo-mcp

# Or install with pip
pip install bofusions-geo-mcp

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MCP Client Configuration

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "Bofusions GEO": {
      "command": "uvx",
      "args": ["bofusions-geo-mcp"]
    }
  }
}

Cursor / VS Code / 5ire / Other MCP Clients

{
  "mcpServers": {
    "bofusions-geo": {
      "command": "uvx",
      "args": ["bofusions-geo-mcp"]
    }
  }
}

pip install (alternative)

{
  "mcpServers": {
    "Bofusions GEO": {
      "command": "python",
      "args": ["-m", "bofusions_geo_mcp.server"]
    }
  }
}

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Tools (7)

Tool	Input	Description
geo_audit	URL	Full GEO audit with scoring (0-100) and prioritized action items
geo_citability	URL	Score every content passage for AI citation readiness
geo_brand_scan	Brand name	Scan brand presence across YouTube, Reddit, Wikipedia, LinkedIn, GitHub + 7 platforms
geo_llmstxt	URL + mode	Validate existing llms.txt or generate a new one
geo_technical	URL	Technical analysis — SSR detection, robots.txt AI directives, meta tags, security headers
geo_schema	URL	Detect and validate JSON-LD structured data for AI discoverability
geo_report	URL + brand	Comprehensive markdown report combining all analyses

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Usage Examples

Once connected to your MCP client, just ask naturally:

Full GEO Audit

Run a GEO audit on https://example.com

AI Citability Scoring

Score https://example.com/blog/post for AI citation readiness

Brand Presence Scan

Scan brand "Acme Corp" across AI-cited platforms

llms.txt Generation

Generate an llms.txt file for https://example.com

Structured Data Check

Check JSON-LD schema on https://example.com

Full Report

Generate a comprehensive GEO report for https://example.com with brand "Acme Corp"

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GEO Score Breakdown

Every geo_audit and geo_report produces a GEO Score (0-100):

Component	Weight	What It Measures
AI Citability	25%	Passage-level scoring — how likely AI will quote your content
Brand Authority	20%	Presence on YouTube, Reddit, Wikipedia, LinkedIn (3x stronger than backlinks)
Content Quality	20%	E-E-A-T signals, readability, statistical density
Technical	15%	SSR rendering, robots.txt AI crawler access, meta tags
Structured Data	10%	JSON-LD schema completeness (Organization, WebSite, etc.)
Platform Optimization	10%	llms.txt existence, AI crawler friendliness

Grading: A (80+) / B (65+) / C (50+) / D (35+) / F (<35)

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Citability Scoring Engine

Each content passage is scored on 5 dimensions:

Dimension	Weight	Optimal
Answer Block Quality	30%	Definition patterns, early answers, quotable claims
Self-Containment	25%	134-167 words, low pronoun density, named entities
Structural Readability	20%	10-20 word sentences, list patterns, paragraph breaks
Statistical Density	15%	Percentages, dollar amounts, named sources
Uniqueness Signals	10%	Original research, case studies, specific tools

Key finding: Optimal AI-cited passages are 134-167 words, self-contained, and fact-rich.

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AI Crawler Coverage

The technical analysis checks access for 14 AI crawlers:

GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, anthropic-ai, PerplexityBot, CCBot, Bytespider, cohere-ai, Google-Extended, GoogleOther, Applebot-Extended, FacebookBot, Amazonbot

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Brand Scan Platforms

Platform	Correlation	Why It Matters
YouTube	0.737 (strongest)	Video transcripts are major AI training source
Reddit	High	Authentic discussions heavily cited by AI
Wikipedia	High	Structured entity data, knowledge graph
LinkedIn	Moderate	Thought leadership, company authority
GitHub	Moderate	Developer brand, open-source authority
+ 7 more	Varies	Quora, Stack Overflow, G2, Trustpilot, Crunchbase, Product Hunt

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Output Format

All tools return Markdown — optimized for LLM consumption and human readability:

# GEO Audit Report

> **Bofusions GEO MCP** | `https://example.com`

## Overall GEO Score: 72.5/100 (Grade B)

| Component | Weight | Score |
|-----------|--------|-------|
| Ai Citability | 25% | 68.2 |
| Brand Authority | 20% | 45.0 |
| Content Quality | 20% | 71.3 |
| Technical | 15% | 85.0 |
| Schema | 10% | 75.0 |
| Platform | 10% | 90.0 |

## Priority Action Items
1. Restructure content into 134-167 word self-contained passages
2. Add Organization + WebSite JSON-LD schema
...

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Development

git clone https://github.com/botfusions/bofusions-geo-mcp.git
cd bofusions-geo-mcp

python -m venv .venv
# Windows:
.venv\Scripts\activate
# macOS/Linux:
source .venv/bin/activate

pip install -e .
python -m bofusions_geo_mcp.server

Run Tests

python -c "
import asyncio
from bofusions_geo_mcp.tools.technical import run_technical
print(asyncio.run(run_technical('https://example.com')))
"

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Tech Stack

• Framework: FastMCP — Model Context Protocol server
• HTTP Client: httpx — async HTTP with SSL fallback
• HTML Parsing: BeautifulSoup4 + lxml
• Python: 3.11+ (3.12, 3.13 supported)

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Requirements

• Python >= 3.11
• mcp[cli] >= 1.6.0
• httpx >= 0.27.0
• beautifulsoup4 >= 4.12.0
• lxml >= 5.0.0
• validators >= 0.22.0

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License

MIT License — Copyright (c) 2026 Bofusions

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