llms-txt
Providers using this tag (42)
Ranked by API Evangelist rating — Exemplar and Strong are expanded by default.
Exemplar 2 Complete, well-documented, and agent-ready
Strong 13 Solid coverage with minor gaps
Developing 13 Usable, with meaningful gaps to close
Thin 3 Limited public surface area
Emerging 8 Early or largely undocumented
Minimal 3 Almost no public developer surface
APIs with this tag (36)
Ranked by the provider's API Evangelist rating — the Kin Score is scored per provider, not per API, so every API of a provider shares its band. How the rating works →
Exemplar 1 Complete, well-documented, and agent-ready
Strong 8 Solid coverage with minor gaps
Developing 14 Usable, with meaningful gaps to close
Thin 7 Limited public surface area
Emerging 4 Early or largely undocumented
Minimal 2 Almost no public developer surface
Companies reaching this through an API (18)
These companies publish an API, specification or operation carrying “llms-txt” but do not classify their business under it. Listed unranked and kept out of the count above, because one tagged operation is not a statement about what a company does.
Score breakdown
Related tags
Where this tag comes from
Cohort brief
Auto-generatedThe 42 providers in the APIs.io catalog tagged llms-txt, scored on the Kin Score. Every figure below is computed from the catalog — nothing here is written.
| Facet | This cohort | Catalog | Difference | Scored |
|---|---|---|---|---|
| Developer Ergonomics | 50 | 23.2 | +26.8 | 42 |
| Access Clarity | 52 | 26.5 | +25.5 | 42 |
| Operational Transparency | 33.6 | 13.7 | +19.9 | 42 |
| Contract Quality | 34.1 | 17.6 | +16.5 | 42 |
| Discoverability | 69.9 | 58.1 | +11.8 | 42 |
| Contract Governance | 10.2 | 6.3 | +3.9 | 42 |
A facet is averaged over the members that carry it, not over the whole cohort — the “Scored” column is that count. Averaging an absent facet as zero would score our own coverage gaps as the providers’ posture.
| Artifact | This cohort | Catalog | Difference |
|---|---|---|---|
| MCP server (any) | 57% | 14% | +43 |
| MCP server (first-party) | 62% | 12% | +50 |
| Agent Skills | 0% | 0% | 0 |
| OAuth scopes | 24% | 11% | +13 |
| Security | 95% | 98% | -3 |
| Arazzo workflows | 0% | 2% | -2 |
| Governance rules | 0% | 14% | -14 |
mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.
- 1 Cracked API 70.3
- 2 TranscriptFetch 67.6
- 3 Statable Stats API 65.9
- 4 Agent Ready 63.5
- 5 RoxyAPI 63.5
- 6 The Ainglish Project 61.9
- 7 APIVerve 60.8
- 8 Autoderm – AI Dermatology API 60.5
- 9 AI for Database 60.2
- 10 Adanos Market Sentiment API 59.7
- 1 Agent Ready 72.9
- 2 Cracked API 68.5
- 3 TranscriptFetch 58.1
- 4 Statable Stats API 57.6
- 5 The Ainglish Project 57
- 6 Loa Healthcare Pricing API 55.9
- 7 BudgetPixel 55.3
- 8 anew 50.6
- 9 APIVerve 50
- 10 Agent Disco 49.1
Coverage caveat. 30 of 42 scored members had under half their catalog-attributable points satisfied at all (catalog_earned / catalog_max < 0.5). They are INCLUDED in the mean above. A large share here means the cohort mean is partly a measurement of how far our enrichment reached, not only of how these providers publish.Generated from the catalog build of 5 October 2026, across 29093 providers, using the same computation served by the APIs.io cohort API. Briefs are published for rosters of 5 or more scored providers; below that a distribution is not meaningful.
Work with this as data
Every tag here is available over the APIs.io API and to AI agents over MCP.