How to add llms.txt to Framer
Framer Sites can serve custom files via redirects to a hosted text endpoint, but the cleanest setup uses Cloudflare in front of the Framer domain.
Before you start
- ✓A static host for the file (GitHub Pages, Cloudflare R2, or any CDN)
- ✓Framer Site Settings access for redirects
- ✓Optional: Cloudflare in front of the Framer domain
Install in 3 steps
- 1
Host the file externally
Put llms.txt on any static host (GitHub Pages, Cloudflare R2, Vercel static).
- 2
Add a redirect
In Framer Site Settings → Redirects: /llms.txt → https://your-host.example.com/llms.txt.
- 3
Verify
Curl the canonical URL and confirm the redirect chain ends at 200 + text/plain.
Troubleshooting
Set proper CORS headers on the host serving the file: Access-Control-Allow-Origin: *.
Use Cloudflare to serve the file at the apex domain instead of redirecting.
Common gotchas
- • Framer redirects are 301 — that's fine for AI crawlers but verify in Search Console
- • If you serve from another origin, set CORS and cache headers appropriately
Generate your llms.txt in 30 seconds
Use the free OptimAIze generator, then follow the steps above to deploy on Framer.
Frequently asked questions
Does Framer need both llms.txt and robots.txt?
Yes. robots.txt grants crawler permission; llms.txt curates which pages matter. Together they form the minimum AI-search setup on any Framer site.
Will adding llms.txt slow down my site?
No. It's a tiny static text file fetched once and cached aggressively. Page-load impact is effectively zero.
How often should I update llms.txt?
Whenever your canonical content set changes — new docs section, new product line, new pricing page. A monthly review is a sensible cadence for most sites.
Can I see whether AI engines read my llms.txt?
Check your server logs for user agents like GPTBot, ClaudeBot, PerplexityBot, and Google-Extended hitting /llms.txt. Most sites see traffic within days of publishing.
Other platforms
The Strategic Imperative of llms.txt on Framer
For Framer-hosted sites, implementing an `llms.txt` file is no longer optional; it's a strategic necessity for AI search visibility. This file acts as a critical directive for large language models, governing how they crawl, index, and cite your content. Neglecting `llms.txt` means surrendering control over your digital footprint in the generative AI landscape, potentially leading to misattribution, lack of citation, or even misuse of your proprietary content. Framer's simplicity means you need a precise approach to ensure this file is not just present but correctly configured to align with your content strategy, guiding LLMs to acknowledge your authorship and purpose effectively.
Crafting Your llms.txt for Framer's Architecture
Framer's no-code environment presents a unique challenge and opportunity for `llms.txt` implementation. Unlike traditional CMS platforms, direct server access for file placement is abstracted. The key is to leverage Framer's custom code or asset management features to ensure the `llms.txt` is accessible at the root of your domain. This requires careful consideration of how Framer serves static files and whether it allows for direct root file uploads or if it necessitates a workaround, such as hosting the file externally and redirecting, or utilizing specific Framer app integrations. Precision in pathing and content within the file is paramount to avoid misinterpretation by LLM agents.
Maintaining LLM Directives on a Dynamic Platform
Maintaining an `llms.txt` file on Framer demands vigilance, especially as LLM capabilities and ethical guidelines evolve. Initial setup is just the first step; regular audits are essential to ensure the directives remain relevant and effective. This involves monitoring LLM citation patterns for your content, observing any unexpected AI-driven traffic, and proactively adjusting `llms.txt` rules. For Framer users, this might involve re-uploading updated files via their asset manager or adjusting custom code snippets. Staying informed about changes in AI crawler behavior and adapting your `llms.txt` accordingly is key to sustained AI visibility and content integrity.
llms.txt Directives for Framer Sites
| Directive | Purpose | Framer Implementation Notes |
|---|---|---|
| User-agent: * | Applies rules to all LLM bots. | Always include as a baseline to cover all known and unknown LLM agents. |
| Allow: /pages/ | Permits LLMs to access content within '/pages/'. | Crucial for most Framer sites where primary content resides under a 'pages' or similar directory. |
| Disallow: /assets/ | Prevents LLMs from indexing asset folders. | Prevents unnecessary scraping of images, videos, or design files that aren't textual content. |
| Crawl-delay: 5 | Requests a 5-second delay between LLM requests. | Helps manage server load on shared Framer hosting, preventing aggressive scraping. |
| Request-index: /specific-page.html | Suggests specific pages for indexing/citation. | Use selectively for high-value content; ensure the path is exact as served by Framer. |
Essential Framer llms.txt Setup Checklist
- Verify Framer's file upload method for static root files or use custom code for inclusion.
- Ensure `llms.txt` is accessible at `yourdomain.com/llms.txt` and not a sub-path.
- Include specific `User-agent` directives for known LLMs (e.g., 'Google-Extended', 'ChatGPT-User').
- Define `Allow` rules for all content you wish to be cited by LLMs.
- Implement `Disallow` rules for sensitive, redundant, or non-textual content.
- Regularly test `llms.txt` accessibility and conduct content attribution audits.
Steps to Publish and Maintain llms.txt on Framer
- 1Draft Your Directives
Begin by outlining your `llms.txt` directives, specifying which content LLMs can access and which they should avoid, paying close attention to Framer's URL structures.
- 2Prepare for Framer Integration
Explore Framer's site settings or custom code injection points. You may need to create a custom HTML embed on your root page that dynamically serves the `llms.txt` content or leverage a CDN if Framer doesn't support direct root file uploads.
- 3Verify Public Access
After publishing, immediately check if `yourdomain.com/llms.txt` is publicly accessible and contains the correct directives. Any error here renders the file ineffective for LLM agents.
- 4Monitor and Iterate
Regularly review your site's AI visibility and citation patterns. Adjust your `llms.txt` directives as needed based on LLM behavior updates or changes in your content strategy, then re-publish and re-verify.
More questions answered
- Can I use robots.txt instead of llms.txt for LLM directives?
- While `robots.txt` can technically carry some LLM directives, `llms.txt` is the dedicated standard. LLMs are increasingly being designed to specifically look for and respect `llms.txt`, offering more granular control and clearer intent for AI-specific indexing behavior. Using `llms.txt` ensures future-proof compliance.
- Where exactly do I upload llms.txt in Framer?
- Framer does not offer a direct root file upload for `llms.txt` like traditional servers. You typically need to host the `llms.txt` file externally (e.g., on a cloud storage service) and then use Framer's custom code embedding features to serve a redirect or include it as a custom asset, ensuring it's accessible at the root domain.
- What happens if I don't create an llms.txt for my Framer site?
- Without an `llms.txt` file, your Framer site content is left to the default crawling and indexing behaviors of LLM agents. This means you surrender control over how your content is consumed, cited, or even potentially misused by generative AI, leading to missed attribution opportunities or unwanted scraping.
- How often should I update my llms.txt on Framer?
- It's recommended to review and potentially update your `llms.txt` quarterly, or whenever there are significant changes to your website's structure, content strategy, or new major LLM models are released. AI model policies and ethical guidelines evolve rapidly, requiring timely adjustments to maintain effective control.
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