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CloudflareNelson DuarteAnnouncement
Cloudflare AI Search: give your agents a search engine for your data
Summary
Cloudflare introduced developer experience improvements and a preview pricing model for Cloudflare AI Search. Previously, users had to manually connect separate Cloudflare primitives like Workers AI, AI Gateway, Vectorize, R2, and Browser Run to build a search solution. The platform now automates crawling, ingestion, embedding, and retrieval across structured and unstructured data sources. Developers can index sites without sitemaps using link discovery, expose public /search and /mcp endpoints across namespaces, bind search instances directly to Workers, or secure endpoints with Cloudflare Access. Cloudflare uses this system for developer documentation, its corporate blog, and the Cloudflare Dev Stack MCP server to supply coding agents with cited documentation.
Context
Building search solutions previously required developers to stitch together multiple Cloudflare primitives manually, including Workers AI, AI Gateway, Vectorize, R2, and Browser Run.
Approach / What changed
Cloudflare automated the crawling, ingestion, embedding, and retrieval pipeline within AI Search, adding sitemap-free discovery parsing, public /search and /mcp namespace endpoints, custom domain support, and direct Worker bindings.
Takeaways
Embedding and reranking are included for free when using default or select models from the Workers AI catalog.
Namespaces can expose public /search and Model Context Protocol (/mcp) endpoints without authentication, which can be branded with custom domains or secured via Cloudflare Access.
The crawler operates via Browser Run under the Cloudflare-AI-Search bot identity, respecting site bot policies and robots.txt files.
Source and freshness
- Source
- blog.cloudflare.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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