Self-host GeoLook
v0.2.0Open-source GEO platform for AI search visibility
- Stars
- 789
- Port
- 8765 (Local dashboard HTTP server)
What is GeoLook?
GeoLook is an open-source, self-hosted platform for end-to-end Generative Engine Optimization. It helps brands understand and improve how AI engines mention and cite them when answering user questions. The platform runs locally on macOS or Linux with Python 3.9+ and three dependencies, storing all data as plain files. It covers 17 engines across Chinese and global markets, sampling real answers to measure mention rate, rank, and citation share. A four-layer site audit diagnoses why engines may not cite a brand, including robots.txt parsing, WAF/CDN probing with real AI-crawler user agents, and passage-level quotability checks. The Action stage creates implementation tickets with acceptance criteria and risk grades, a content workbench with citability pre-checks, and deployable assets like llms.txt and JSON-LD. Publishing integrations cover several channels for content distribution. Results are auto-verified by re-crawling and next sampling rounds. A Chrome sampling assistant helps with engines lacking APIs. The project is MIT-licensed with no external database or service dependencies, using a local HTTP server on port 8765.
Should you self-host GeoLook?
GeoLook scores 51/100 on selfhost.directory (how scoring works) and ranks #26 of 41 in Search Engines. It has 789 GitHub stars.
It shipped 1 stable release in the past year. The latest, v0.2.0, came out on 8 August 2026.
Setup is moderate: expect some configuration beyond a single command. It is MIT-licensed and written mostly in Python.
Its closest alternative on selfhost.directory is SearXNG (86/100, 38 940 stars). It scores higher overall, so compare the two before you pick. See GeoLook vs SearXNG side by side.
Features
- Auto-verification
- Brand mention distribution analysis
- Channel map with 19 channels
- Chrome sampling assistant
- Client delivery package
- Content workbench with citability pre-check
- Deployable assets generation
- Four-layer site audit
- Implementation tickets with acceptance criteria
- Keyword mining from search demand
- Multi-channel publishing
- Multi-engine AI mention tracking
- Passage-level quotability analysis
- Sample library with human correction
- Scheduled re-runs and multi-brand support
GeoLook README
FAQ
AI answers differ every time — how can sampling results be stable?
GeoLook never reads a single answer as a metric. Stability comes from aggregation over dozens of questions × multiple engines, fixed variables (pinned sampling models, fixed question bank), repeat rounds (sampling each question multiple times), and attribution discipline (only two consecutive rounds moving the same way count as a trend; ticket verification relies on deterministic re-crawling rather than sampling alone).
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