Text-to-Speech
Text to SpeechTTS
Providers using this tag (67)
Ranked by API Evangelist rating — Exemplar and Strong are expanded by default.
Exemplar 1 Complete, well-documented, and agent-ready
Strong 8 Solid coverage with minor gaps
Developing 16 Usable, with meaningful gaps to close
Thin 23 Limited public surface area
Emerging 17 Early or largely undocumented
APIs with this tag (66)
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 3 Complete, well-documented, and agent-ready
Strong 10 Solid coverage with minor gaps
Developing 14 Usable, with meaningful gaps to close
Thin 23 Limited public surface area
Emerging 14 Early or largely undocumented
Companies reaching this through an API (23)
These companies publish an API, specification or operation carrying “Text-to-Speech” 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
Where this tag sits
Related tags
Where this tag comes from
Markets provisional
Kin Score markets whose measured providers carry this tag. Share is the fraction of the market's measured providers that carry it — it describes the market, not this tag.
| Market | Share of the market's providers |
|---|---|
| Speech and Voice AI | 43% |
Cohort brief
Auto-generatedThe 67 providers in the APIs.io catalog tagged Text-to-Speech, 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 | 42.3 | 23.2 | +19.1 | 67 |
| Contract Quality | 36 | 17.2 | +18.8 | 67 |
| Access Clarity | 39.2 | 23.9 | +15.3 | 67 |
| Discoverability | 68.3 | 57.9 | +10.4 | 67 |
| Operational Transparency | 19.2 | 13 | +6.2 | 67 |
| Contract Governance | 8 | 6.5 | +1.5 | 67 |
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) | 25% | 13% | +12 |
| MCP server (first-party) | 27% | 12% | +15 |
| Agent Skills | 0% | 0% | 0 |
| OAuth scopes | 6% | 11% | -5 |
| Security | 100% | 98% | +2 |
| Arazzo workflows | 3% | 2% | +1 |
| Governance rules | 22% | 16% | +6 |
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 ElevenLabs 80.4
- 2 Amazon Polly 65.2
- 3 SLNG 59.6
- 4 AutoContent API 59
- 5 Bluma 58.6
- 6 Speko 56.5
- 7 Venice.ai 56.3
- 8 Captions 54.6
- 9 StepFun 54.4
- 10 Google Gemini 53.5
- 1 AutoContent API 66.1
- 2 Sarj AI Developer API 65.6
- 3 Speko 61
- 4 ElevenLabs 53.5
- 5 Bluma 50.9
- 6 HeyGen 48.8
- 7 Creatify 44.8
- 8 Puppetry 43.6
- 9 Venice.ai 43.2
- 10 useapi.net 36.8
Coverage caveat. 51 of 67 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 24 October 2026, across 31984 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.