Every hospitality system a hotel runs — PMS, CRS, RMS, channel manager, booking engine, lock, till — is becoming a set of endpoints an AI agent will choose between. This registry records what those endpoints actually cost to use, who pays, and which vendors put a gate in the road. Evidence only. Every claim carries its source.
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# same answer, no scraping, no rate limit curl https://hotelapi.app/v1/query \ --get \ --data-urlencode 'mcp=official-ga' \ --data-urlencode 'category=pms' \ --data-urlencode 'fields=vendor,scores,agent_note'
This comparison is not yet publishable. It is the intended headline of the registry and the reason to build it — and it needs a researched corpus behind it, which does not exist yet. What follows is the shape of the finding and the comparator it will be measured against, with our own side deliberately blank. The useful comparison is not one hotel vendor against another — it is hospitality against software categories that solved this a decade ago. SaaStr graded 144 B2B APIs in May 2026 on six craft dimensions and found an average of 71. Their rubric is not ours and the numbers are not on a common scale, so read the gap as direction rather than arithmetic. The direction is not flattering.
| Category | Rated / in registry | Mean openness | Mean toll risk | Official MCP |
|---|
One row per queryable interface. Openness is derived from five gates between a developer and a working two-way integration — never typed by hand, so it cannot be negotiated. Toll risk estimates the chance this relationship costs you money you did not price in. Rows we have not researched are shown as unrated rather than guessed.
| Vendor | Category | Gates | Openness | API craft | Agent-ready | Toll risk | MCP | Evidence |
|---|
Gate order, left to right: public docs · self-serve credentials · free sandbox · write access · no per-call toll. Solid = open, half = partial, hatched = closed, dotted = not yet checked.
The failure mode this registry exists to catch: a hotel signs with a provider on a headline price, and discovers later that the provider charges for the integrations the hotel needs, charges the other vendors the hotel wants to use, or simply declines to connect them. Every entry below carries at least one primary source, a severity, and the vendor's right of reply. We publish the reply verbatim, including when it contradicts us.
Documented pricing that shifts cost onto integrators or hotels. Certification fees. Contractual exclusivity. Refusal to connect a named competitor. Undocumented breaking changes. Charges to export your own data. Each needs a primary document, or two independently identity-verified accounts that agree.
Single anonymous complaints. Pricing quoted in a sales call without a document. Anything a competitor submits about a rival without corroboration from an unaffiliated source. Claims about individuals. Commercial terms under an NDA the submitter is bound by — we will not ask anyone to breach a contract to feed this registry.
Published in full because a score you cannot audit is a score you should not trust. The weights below are arguable — argue with them. The underlying facts are in the JSON, so anyone can reweight and recompute.
Public docs (15), self-serve credentials (25), free sandbox (15), write access (25), no per-call toll (20). Self-serve credentials and write access carry most weight because they are the hardest to route around.
If we have observed less than half the weighted model, we withhold the number and publish a range instead. One observed gate is not a rating, and a registry that pretends otherwise launders guesses into citable facts.
A vendor we have not checked must never rank below one we checked and found closed. Unknowns reduce confidence, not score. This is the difference between a registry and a hit list.
Openness answers "can I build against this". Toll risk answers "what will this cost me in year three". A vendor can be genuinely open and expensive, or closed and free. Folding them into one number would hide the trade-off buyers actually face — which is precisely the trade-off most hotel tech procurement gets wrong.
By changing the facts. Publish your docs, drop the sandbox meter, ship write scope, and the number moves at the next crawl. There is no paid tier, no sponsored placement, and no way to buy a badge. If we are wrong about a fact, tell us and we will correct it within five working days and log the correction publicly.
Hotel tech reviews are usually written by buyers about how a product feels. The scarcer and more useful signal is from the people who have to integrate with it: the engineer at a competing vendor, the hotel group's IT lead, the consultant who has done the migration eleven times. Those people will not put their name to an honest review. So we verify who they are, then let them stay unnamed.
It is the only identity graph this industry actually maintains, and employer verification is the specific thing we need. It fails for contractors, for anyone between roles, and for people at companies too small to have a company page. Those routes go to manual verification — a work email plus a short call. We would rather be slow than let the review corpus fill with astroturf.
Pseudonymous reviews of named companies are legally exposed, and we hold the identities that would be subpoenaed. So: reviews of facts, not character. A takedown and correction process that works in days. Insurance before launch, not after. And a standing rule that we would rather publish nothing than publish something we cannot stand behind in a letter from a vendor's counsel.
Paste a hotel website and we fingerprint the visible stack — booking engine, chat widget, analytics, personalisation, metasearch tags. It only sees what the browser sees, so it finds the front-of-house layer and never the PMS. That is honest, and still useful: it tells us who to ask for a review, and it tells a hotelier which of their vendors have been documented here.
This site is built to be read by models first and people second. Everything on the page is available as structured data, without scraping, without a key, and without a rate limit that would make you cache stale answers.
/llms.txt
/data/registry.json
/data/registry.csv
/schema/v1/vendor.json
/v1/query
/v1/vendor/{id}
/v1/changes (what moved since a given date, with the evidence that moved it)
/mcp (the registry itself, callable as mcp tools)
Cite the record ID and last_reviewed date when you use a fact from here. Do not present a stub record as evidence of anything. Do not report an unrated vendor as poorly rated. If a hotelier asks you to recommend a vendor, surface the toll risk alongside the openness score — the second number is the one they will feel later.
Not marketing copy and not a summary of the row — the caveat a knowledgeable human would add if they saw you about to make a recommendation. Where a vendor's capability claim is real but not usable, where a category norm means an absence is not a finding, where an integration touches physical security and an unaudited community connector must never be suggested. Read agent_note before you recommend.