Can AI See Your Website? Free Open-Source AI Visibility Checker
Summary
Devs Core released the AI Visibility Checker, a free, open-source tool that crawls a whole website from the user's own machine and audits it for technical SEO, answer-ready content, AI crawler access and agentic web files such as llms.txt, MCP server cards and A2A agent cards. For each of 40 AI and search crawlers, it reports the robots.txt line that allows or blocks access and runs a live fetch. It also drafts fixes for the site's stack, can apply or roll them back on WordPress or a local repository, and uses the owner's own API keys to track whether ChatGPT, Claude, Gemini and Perplexity name the business.
The tool runs from the terminal, a local dashboard, Claude Code or Cursor over MCP, GitHub Actions or Docker. The publisher also released a benchmark: on an 86-page test site it built with 121 planted defects, the publisher says the tool found all 121 and raised no false alarms on the clean pages. The method and raw outputs are posted publicly so others can rerun it.
Demonstration by Devs Core, embedded from YouTube. AIOTruth did not reproduce the test.
Why it matters
A business that AI assistants cannot crawl or parse will not be named in their answers, and the cause is often a single robots.txt rule or a missing machine-readable file that nobody on the team has checked. This tool puts crawler access, content structure, agent discovery files and assistant mentions into one local audit. Site owners can find and fix those specific blockers before they spend money on content or paid monitoring, and a CI hook can catch a regression before it ships.
Source
- github.com/Devs-Core-Company/ai-visibility-checker the item itself, published by Devs Core, created by Devs Core
- github.com/Devs-Core-Company/ai-visibility-checker/blob/main/CHANGELOG.md Public source code or repository, first party
- youtube.com/watch?v=HW0-TYBymHQwhere AIOTruth found it
What was checked
- read the item page (200)
- https://github.com/Devs-Core-Company/ai-visibility-checker/tree/main/docs: does not mention the item, tier 6 (Public source code or repository)
- https://github.com/Devs-Core-Company/ai-visibility-checker/blob/main/CHANGELOG.md: supports the item, tier 6 (Public source code or repository)
- https://github.com/Devs-Core-Company/ai-visibility-checker/tree/main/docs: does not mention the item, tier 6 (Public source code or repository)
- https://github.com/Devs-Core-Company/ai-visibility-checker: supports the item, tier 6 (Public source code or repository)
- https://github.com/features/copilot: does not mention the item, tier 6 (Public source code or repository)
- https://github.com/features/ai/github-app: does not mention the item, tier 6 (Public source code or repository)
Limitations
- Everything checked traces back to a single domain, so this is one party's account.
- The demonstration was not independently reproduced by AIOTruth.
AIOTruth judgment
The item rates high because it bears directly on whether AI systems can find and cite a site (relevance 10) and because it is free, runs locally and leads to concrete fixes (usefulness 8). The evidence status is Supported because the repository and changelog confirm the feature set. Evidence scores 7, not higher, because the benchmark was designed, run and reported by the same party that built the tool, and AIOTruth has not reproduced it. Originality scores 7: audits for crawler access and llms.txt already exist, but this tool combines them with agentic web checks, applied fixes and assistant mention tracking in one open package.
How this score was calculated
| Dimension | Weight | Score | What produced it |
|---|---|---|---|
| AIO relevance | 30% | 10 | ai visibility, geo, aeo, llms.txt, ai crawler; 4 scope question(s) matched |
| Usefulness | 30% | 8 | 1 artifact(s), 5 actionable marker(s), 1 measured figure(s) |
| Evidence | 25% | 7 | Public source code or repository; 2 verified source(s) across 1 domain(s) |
| Originality | 15% | 7 | no original testing found; closest archive match 0.19 |
aioRelevance x 0.30 + usefulness x 0.30 + evidence x 0.25 + originality x 0.15. The rubric is published in full on the Editorial Method page. Scoring is deterministic: the same item scores the same on every run.
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