LLM
LLMsLarge Language ModelLarge Language ModelsLLM
Providers using this tag (332)
Ranked by API Evangelist rating — Exemplar and Strong are expanded by default.
Exemplar 9 Complete, well-documented, and agent-ready
Strong 26 Solid coverage with minor gaps
Developing 94 Usable, with meaningful gaps to close
Thin 113 Limited public surface area
Emerging 46 Early or largely undocumented
Minimal 43 Almost no public developer surface
Unrated 1 Not yet scored
APIs with this tag (150)
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 11 Complete, well-documented, and agent-ready
Strong 21 Solid coverage with minor gaps
Developing 43 Usable, with meaningful gaps to close
Thin 52 Limited public surface area
Emerging 20 Early or largely undocumented
Minimal 3 Almost no public developer surface
Companies reaching this through an API (65)
These companies publish an API, specification or operation carrying “LLM” 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.
Show all 65 companies ↓
Score breakdown
Where this tag sits
Related tags
Where this tag comes from
Cohort brief
Auto-generatedThe 327 providers in the APIs.io catalog tagged LLM, 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 | 41.6 | 23.2 | +18.4 | 327 |
| Contract Quality | 33.5 | 17.6 | +15.9 | 327 |
| Operational Transparency | 24.5 | 13.7 | +10.8 | 327 |
| Access Clarity | 35.7 | 26.5 | +9.2 | 327 |
| Discoverability | 65.3 | 58.1 | +7.2 | 327 |
| Contract Governance | 7.9 | 6.3 | +1.6 | 327 |
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) | 27% | 14% | +13 |
| MCP server (first-party) | 25% | 12% | +13 |
| Agent Skills | 0% | 0% | 0 |
| OAuth scopes | 7% | 11% | -4 |
| Security | 98% | 98% | 0 |
| Arazzo workflows | 4% | 2% | +2 |
| Governance rules | 23% | 14% | +9 |
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 OpenAI 84.8
- 2 Anthropic 79.4
- 3 Kong 73.2
- 4 Dust 73
- 5 Arcade 72.9
- 6 Hugging Face 68
- 7 NVIDIA NIM 68
- 8 S&P Global 66.9
- 9 AlphaAI 66.7
- 10 AIMLAPI 65.2
- 1 S&P Global 66.2
- 2 Patronus Protect 66.2
- 3 AlphaAI 66
- 4 Speko 60.5
- 5 Perplexity 60.4
- 6 Coval 59.8
- 7 OpenAI 57.1
- 8 Exa 57.1
- 9 AIMLAPI 55.1
- 10 APIClaw 54.4
Work with this as data
Every tag here is available over the APIs.io API and to AI agents over MCP.