Google and a Linux Foundation working group published Agentic Resource Discovery in 2026, an open specification for telling agents what a site offers in one machine-readable file at /.well-known/ai-catalog.json. turva.dev now serves one. This is the log of adding it, and of why the change could not move the scanner score either way.
What the file says
The manifest is a small envelope with a specVersion, a host block, and an entries array. Each entry names one agentic resource with an identifier, a type, a url, and a description. turva.dev publishes four entries, and every one points at a surface that already resolves: the MCP server card, the A2A agent card, the OpenAPI description, and the agent skills index. Nothing in the catalog is aspirational. If a line names a resource, that resource answers.
Why it is additive
The catalog is a new file and a new route. It does not change a single existing surface, so it cannot lower a score, and because neither independent scanner checks for ai-catalog.json yet, it cannot raise one either. turva.dev already reads 100/100 on startuphub.ai and Level 5 on isitagentready.com, and it read the same after this change. The point of publishing now is not the number. It is that a Google-backed discovery standard exists, and a site that sells agent-readiness should serve the surface before its buyers ask for it.
Discovery, not ranking
An ai-catalog.json is easy to misread as another search file. It is not. It indexes the agentic resources a site exposes so an agent can find them and call each one through its own protocol. Google confirmed in 2026 that llms.txt does not affect its search results, and the same holds here. Agent-readiness and search ranking remain different things, and neither should be sold as the other.
Honest about adoption
In a public census in June 2026, none of the companies named as contributors to the specification yet served a discoverable ai-catalog.json. The specification is an early draft and adoption is near zero. That is the honest frame for this post. turva.dev is early rather than late, and being early on a verifiable standard is a position worth holding when the work is open source and readable line by line at codeberg.org/erekola/turva-worker.
For an audit of a site’s discovery surface, contact [email protected].
Related
- Agentic Resource Discovery and ai-catalog.json
- The /.well-known directory for agents
- MCP server cards explained
Originally published at https://turva.dev/blog/publishing-an-ai-catalog
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