Agent access

Built to be read by machines, too.

hyperize.ai serves every page in three forms: HTML for people, Markdown for language models, and JSON for programs. And it goes one step further: the site registers WebMCP tools, so an in-browser agent does not have to scrape this site. It can ask for a DAX 40 score, probe a website's agent readiness, or order the free Snapshot directly. This page documents the whole machine-readable surface. Everything listed here is live. No key, no registration.

Read surfaces

One site, three formats.

The same content boundary in every format. What is withheld in one is withheld in all.

Machine-readable site guide following the llms.txt convention: what Hyperize is, when to use it, and every indexable page with a one-line summary. Scoped deep indexes at /en/answers/llms.txt, /en/insights/llms.txt, /en/dax40-index/llms.txt; everything in one file at /llms-full.txt.

Every content page has a Markdown twin: append .md to the URL, or request the page with the header Accept: text/markdown. Twins carry frontmatter (title, description, canonical) and open with the page's H1.

Structured JSON at the same URL with .json appended: the DAX 40 Index inventory, every scored brand page, the Insights hub (16 articles), Methodology pages, and Answer Pages. Format hyperize/v1, same content boundary as the HTML.

XML sitemap of every indexable URL. Content pages carry a lastmod taken from the page's own dateModified; the build date is never used as a stand-in.

Explicit allowlist for search and AI assistant crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended and others). Being read and cited by assistants is the point of this site.

Every page emits schema.org JSON-LD in the initial HTML: one canonical Organization entity, DefinedTerm pages for the Hyperize vocabulary (Agent Surface, Agent Success Score, Third-Party Interception), Service, Dataset and Article where applicable.

Unknown paths return HTTP 404 with recovery links, and a Markdown body when requested with Accept: text/markdown. No soft redirects, no error pages pretending to be content.

Site tools

Four tools an agent can call. One of them acts.

Every page registers these tools on document.modelContext (the WebMCP draft standard). Agents that support it, like the ChatGPT desktop browser, call them instead of guessing through the UI. Humans see this same page; agents get the same three things a visitor wants: check a score, read the research, order the report.

get_brand_agent_success_score READ

Look up any DAX 40 brand in the Agent Success Index: measured score, both axes (AI Visibility, AI Usability), the measured bottleneck, and the link to the full evidence page.

Try:  “How does adidas score in the DAX 40 Agent Success Index, and what blocks it?”

search_insights READ

Search the published field research on how AI agents evaluate, recommend, and transact with enterprise brands.

Try:  “Find Hyperize research about agents failing at checkouts.”

check_agent_readiness READ

Instant five-check surface probe for ANY website: front door reachable, robots.txt policy for AI crawlers, llms.txt, schema.org JSON-LD, Markdown twin. Result in seconds, with DAX 40 context. A surface probe, deliberately not the measured Agent Success Score.

Try:  “Check example.com: can AI agents work with it?”

request_snapshot WRITE

The one write action on this site: order the free Agent Success Snapshot. Hyperize runs real agent tasks against the website, scores it, benchmarks it on the DAX 40, and delivers the report by email within 48 hours. Free, no commitment. Agents are expected to confirm URL and email with their user first.

Try:  “Order the free Hyperize snapshot for our website, report to my work email.”

Consequential actions stay confirmed: the one write tool submits the same form humans use, and agents are expected to confirm URL and email with their user first.

Plus six on the homepage

The English homepage registers a second surface: a personalization contract that lets a visiting agent rewrite the page for its user. The agent reads per-field length budgets, submits every text in one call, and the page stages the reveal. Changes live in that visitor's browser only; a reload restores the original.

get_adaptation_capabilities · start_personalization · write_all · write_section · show_decision_brief · reset_experience

Try it

From a terminal.

# The site guide, with a when-to-use section
curl https://www.hyperize.ai/llms.txt

# Any page as Markdown, two equivalent ways
curl https://www.hyperize.ai/en/pricing.md
curl -H "Accept: text/markdown" https://www.hyperize.ai/en/pricing

# The DAX 40 Index as JSON, then one brand's sibling
curl https://www.hyperize.ai/en/dax40-index.json
curl https://www.hyperize.ai/en/dax40-index/brands/adidas.json

# The agent-readiness surface probe (the WebMCP tool's backend)
curl "https://www.hyperize.ai/.netlify/functions/agent-readiness-probe?url=example.com"

There is no separate API beyond these read-only surfaces and the documented tools, and no key or registration. If you are building something that needs more: hello@hyperize.ai.