Verified startup revenue, one listing at a time.

The dataset holds 9,675 public startup listings, deduplicated to one record per slug. Every record is a startup TrustMRR itself lists on its own public marketplace pages.

No — it is a marketplace snapshot, not a census. Every record comes from TrustMRR's own public listing pages, so the population carries TrustMRR's selection bias: it skews toward indie and bootstrapped software, and toward the payment providers TrustMRR integrates with. 90.1% of listed startups report under $1,000 in verified MRR, which says more about who lists on TrustMRR than about the SaaS market as a whole. Use it as a discovery surface into that specific marketplace, not as a basis for population-level claims about startups in general.

Revenue and MRR figures come from the payment provider each startup actually uses (Stripe, RevenueCat, Superwall, Creem and others), not a founder-typed number — 58.3% of the index runs through Stripe alone. payment_provider is, as measured, a full partition of the dataset: every record carries exactly one value, unlike category or country, which are top-N terms aggregations that do not cover every record.

Yes — that is this dataset's distinctive angle versus a plain revenue directory. 22.1% of the index is flagged on_sale=true right now, each with an asking price and usually a revenue multiple and deal score. Filter on on_sale=true and sort by price_desc, multiple_asc or deal_score_desc to work the acquisition marketplace directly through the API.

Every field is a public, credential-free listing field read from TrustMRR's own public marketplace pages: slug, name, website, country, category, target audience, payment provider, verified MRR and revenue figures, traffic and growth windows, detected tech stack and marketing channels, and (for for-sale listings) asking price, multiple, deal score and listing tier. Nothing behind authentication is collected — no login, no API key, no TrustMRR account. A separate history endpoint holds each startup's daily time series; it is not embedded in this record.

payment_provider is, as measured, a full partition of the corpus — every startup has exactly one, and the ten values returned sum to the entire 9,675-record index. category is a top-N terms aggregation instead: the 12 categories shown on this page cover only 91.1% of the index, because the facet endpoint returns only the top buckets. Filter on either to narrow a search, but only treat payment_provider's breakdown as exhaustive.

Yes. Four endpoints cover it: search (full-text and faceted, with MRR, revenue, traffic, growth and marketplace filters), one startup by slug, facet counts for category, payment provider and more, and a daily history endpoint for revenue, MRR and traffic. The same four are exposed as MCP tools — datasets_trustmrr_search, datasets_trustmrr_item, datasets_trustmrr_facets and datasets_trustmrr_history — so an agent can call them directly. Reads hit the stored index and never trigger a live crawl; billing is pay-on-success.