What is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the discipline of auditing, structuring, and optimizing digital assets so your brand is accurately discovered, cited, and recommended in generative AI search engines like ChatGPT Search, Perplexity, Google AI Overviews, and Gemini.

What is the difference between open-geo and the GeoFN Cloud Platform?

open-geo is a 100% free, MIT-licensed open-source CLI and MCP server built for local developer audits, single-model BYOK probing, and llms.txt generation. GeoFN Cloud is the enterprise commercial platform offering automated 4-engine concurrent probing across residential proxies, competitor entity gap diffs, 24/7 citation drift alerts, and agency white-label portals.

How does GEO differ from traditional SEO?

Traditional SEO optimizes for blue links, backlinks, and keyword rankings on search engine result pages (SERPs). GEO optimizes for direct knowledge graph grounding, multi-model LLM citation win rates, semantic entity alignment, and AI crawler access policies (GPTBot, PerplexityBot, ClaudeBot).

How can developers and teams get started with open-geo?

Developers can run 'npx open-geo audit ' directly in any terminal for an instant zero-dependency technical audit, or connect open-geo as a native MCP server to Cursor, Claude Code, or Antigravity IDE.

100% OPEN SOURCE GEO TOOLCHAIN

Is your brand recommended in AI search?Or is your competitor taking the traffic?

Open-source Generative Engine Optimization toolchain. Inspect citation share, diagnose crawl blockers, and patch deficits locally.

Star on GitHub Live Interactive Demo

open-geo-cli -- target

$npx open-geo audit

← Type domain to customize

✔Target resolved:geofn.com

✔Deterministic checks:Robots AI policy + llms.txt validation + Schema.org entities

✔Multi-LLM probing:ChatGPT, Google Gemini, Perplexity share of voice

> Ready. Run this command in your terminal for a full report in seconds:

npx open-geo audit geofn.com

100% self-hosted & local-first · Zero data uploaded · Fully transparent source

MIT Licensed

LIVE ENGINE DEMO

Probe Your Domain Live in AI Search

Real-time Google AI Overview search inspection and neural citation extraction. Inspect whether your brand is recommended or if your competitors capture the traffic.

open-geo probe --engine google-ai --deep-audit

Credits: 1 / 1 Free(Unlock 2 more deep probes with work email)

Quick Presets:

Why Traditional SEO Is Losing Growth Velocity

When potential customers bypass search links and rely on synthesized AI answers, discovery dynamics fundamentally shift.

CITATION STEALING RISK

AI answers recommend your competitor with direct outbound links

In ChatGPT Search and Perplexity, when buyers ask for category recommendations, models synthesize 2-3 specific vendors with detailed rationales. If your brand lacks recognized entity authority, you lose both the referral click and default buyer trust.

Common indicator: Traditional SERP ranks hold, while high-intent brand inbound and conversions quietly erode.

TRAFFIC BLACK HOLE

Ranking #1 on Google, but invisible as search shifts to AI answers

Technical decision-makers and modern buyers increasingly favor direct AI answers. High SERP rank cannot help if language models cannot retrieve your value proposition.

KNOWLEDGE BLOCKERS

Missing llms.txt or blocking GPTBot and ClaudeBot

Lacking an agent-friendly /llms.txt entrypoint or misconfiguring robots.txt causes crawler rejection, prompting language models to hallucinate specs or omit your domain.

Built for the Terminal: Three Core Scenarios

No black-box scoring or guesswork. open-geo delivers an open-source CLI and native MCP server with deterministic heuristics and transparent rules.

SCENARIO 01 / HEAD-TO-HEAD

Multi-LLM Competitive Probing: Real-Time Share of Voice

Concurrently probe ChatGPT, Google Gemini, and Perplexity across commercial queries to inspect citation share and sentiment.

open-geo compare --head-to-head

$ open-geo compare notion.so obsidian.md --intent "knowledge management"

┌── Target Intent: [Personal Knowledge Management & Team Wiki] (3 LLMs concurrent)

│

├── Share of Voice Breakdown:

│ notion.so [███████████████···········] 54.2% (First-choice: 4x)

│ obsidian.md [█████████████·············] 45.8% (First-choice: 3x)

│

├── Model Breakdown & Reasoning:

│ • ChatGPT (GPT-4o): Cites Notion for team collaboration, databases, and onboarding velocity

│ • Perplexity Pro: Favors Obsidian for offline local-first Markdown and privacy guarantees

│ • Google Gemini: Balanced synthesis; highlights Obsidian plugin graph vs Notion integrations

│

└── Verdict: Tight battle; Notion leads collaborative queries, Obsidian dominates privacy-first intents.

SCENARIO 02 / TECHNICAL READINESS

Deterministic Technical Audit: Remove Invisible AI Crawl Blockers

Inspect AI crawler access rules, llms.txt specification compliance, and Schema.org structured data.

open-geo audit --technical-readiness

$ open-geo audit geofn.com

┌── Target Site: https://geofn.com

│

├── 1. AI Crawler Accessibility (Robots Policy):

│ ✔ GPTBot: ALLOWED

│ ✔ ClaudeBot: ALLOWED

│ ✔ PerplexityBot: ALLOWED

│

├── 2. LLMs.txt Formatting & Compliance:

│ ✔ /llms.txt present and valid (18 core knowledge anchors and API specs)

│

├── 3. Structured Entity Markup (Schema.org JSON-LD):

│ ✔ SoftwareApplication entity detected

│ ⚠ Warning: Organization.sameAs missing link to GitHub repository

│

└── Technical Readiness Score: 94/100 (Optimal for LLM retrieval)

SCENARIO 03 / AGENTIC WORKFLOW

19 Native MCP Tools: Let AI Agents Fix Your GEO Deficits

Connect seamlessly to Cursor, Claude Code, and Codex via Model Context Protocol. Empower agents to write remediation patches autonomously.

open-geo-mcp --stdio

$ open-geo mcp

✔ open-geo MCP Server ready on stdio

Registered 19 atomic GEO protocol tools:

[1] geo_audit_domain - Inspect domain AI readiness score

[2] geo_probe_llms - Concurrent probing across target models

[3] geo_compare_brands - Head-to-head share of voice benchmarking

[4] geo_generate_llmstxt - Generate compliant /llms.txt from site entities

[5] geo_fix_robots_policy - Diagnose and patch AI crawler blockages

[6] geo_validate_jsonld - Validate and enrich Schema.org graph

... (and 13 additional audit, citation & provenance tools)

Native zero-config support for Cursor, Claude Code, and Codex.

Why Teams Choose Open-Source open-geo

Purpose-built for Generative Engine Optimization without proprietary markups. Retain complete ownership of your heuristics and data.

Capability	open-geo (Open Source)	Closed SaaS (OtterlyAI, Profound)
Starting Price	$0 (Free & Open Source)	$29 - $99+ / mo
Source Transparency	100% MIT Licensed	Closed Black Box
Local Self-Hosting	Supported (CLI / Docker / Air-gapped)	Not Supported
Data Privacy & Governance	100% Local, Zero Cloud Uploads	Requires Cloud Server Upload
AI Agent & MCP Integration	Built-in 12+ MCP Tools (Cursor/Claude)	No MCP Protocol Support
Actionable Remediation	Automated Code Patches & /llms.txt	Generic Text Recommendations

Note: Benchmarked against representative commercial closed-source alternatives. Prices based on publicly listed tier plans as of 2026.Need Custom Agency Plan? Contact support@geofn.com →