TextToSpeechSkills
Start test plan

Built for shipping teams

A text-to-speech platform shaped around developer workflows

TextToSpeechSkills focuses on the parts developers repeatedly ask for after the demo works: clean API calls, predictable jobs, scoped keys, workspace billing, reusable templates, and agent integrations that can be installed quickly.

See LLM setupExplore product

Who is this for?

TextToSpeechSkills is a developer-first text-to-speech platform for teams that want clean API access, expression markup, reusable voice templates, MCP tools, installable skills, async jobs, workspace billing, and visible credit usage. The product is designed around outcomes instead of public engine selection. A team can create speech in the UI, call the API from a product, or connect an LLM app through MCP. This makes it a practical option for builders who want voice output that is easier to automate, review, and budget.

Easy LLM setup

LLM-ready even for non-technical teams

Non-technical users can start from the guide: create a key, copy the MCP command, choose a voice template, and ask their LLM app to generate audio.

Read setup guide
01Create a scoped key
02Install MCP
03Choose a voice template
04Generate audio from chat

No public engine choices to manage

Your app sends the outcome it needs. Routing stays server-side so customer-facing screens stay simple.

Billing that matches usage

Credits, optional packs, and workspace billing make speech generation easier to forecast as usage grows.

API, MCP, and skills together

Human builders and LLM agents can share the same validated speech workflow from launch.

When this helps

Builders comparing developer-first text-to-speech platforms usually need a repeatable path for writing, review, generation, billing, and reuse. The most important jobs here are no public engine choices to manage, billing that matches usage, api, mcp, and skills together. Those are the moments where voice becomes part of real work instead of a one-off export.

How the workflow works

Start with readable text, add expression tags when tone matters, choose an approved voice template, and create a speech job through the UI, API, or MCP. The same pattern works for text-to-speech alternative, developer TTS, voice API alternative, which makes it easier for humans and LLM apps to share one process without exposing internal routing or credentials.

Before you roll it out

Decide which templates are approved, which expression tags are allowed, who can create workspace keys, and which usage limits are acceptable. Those choices keep automated voice generation useful without letting it sprawl from the first paid Test plan through Pro, Scale, and Business usage.

Common questions

What teams usually ask before starting

These are the practical details that matter before a team adds speech generation to a real workflow.

Who should use Developer-First Text to Speech Alternative?

Builders comparing developer-first text-to-speech platforms should use this page when they want generated speech that is easy to review, consistent across prompts, and simple to connect to LLM tools. The core workflow combines expression tags, voice templates, credit previews, and job-based generation.

Can a non-technical user connect this to an LLM app?

Non-technical users can start from the guide: create a key, copy the MCP command, choose a voice template, and ask their LLM app to generate audio. The setup guide keeps the first path short while still giving developers a clean API when the workflow moves into a product backend.

How does pricing stay predictable?

Every paid plan uses credits. Teams can add credit packs when needed, and workspaces on Pro and higher add central billing for $2 per user per month.

Related reading

Keep exploring TextToSpeechSkills

Use these guides to move from a first audio test to a repeatable workflow for your team.

LLM Text-to-Speech Setup GuideA simple guide for connecting TextToSpeechSkills to LLM apps with MCP, scoped keys, voice templates, and expression tags.Text-to-Speech MCP for LLM AppsConnect LLM apps to expressive text-to-speech with MCP tools for tags, voice templates, credit previews, jobs, and audio URLs.Text-to-Speech Skills for LLM WorkflowsInstall text-to-speech skills that teach LLM apps how to use expression tags, saved voices, MCP tools, and speech jobs safely.TTS MCP ServerInstall an MCP server that lets LLM agents validate expression markup, check credit use, use voice templates, and create speech jobs.How to Add Text-to-Speech to an LLM AppA practical launch guide for adding text-to-speech to LLM apps with expression tags, voice templates, MCP setup, jobs, and team billing.Expression Tags for Better AI Voice OutputLearn how expression tags make text-to-speech scripts easier to review, automate, and reuse across LLM apps, creators, games, and support flows.

API playground

Plain JSON in, speech job out

{
  "text": "[quiet] hello. [loud and angry] how are you?",
  "voice_template": "vt_calm_narrator_v1",
  "generation_mode": "instant",
  "format": "mp3"
}
202 queued for polling200 audio ready

MCP install

Agent tools included at launch

Claude Desktoppnpm --package texttospeechskills dlx tts-skills-mcp
Codexpnpm --package texttospeechskills dlx tts-skills-mcp
Cursorpnpm --package texttospeechskills dlx tts-skills-mcp
Skills helperpnpm --package texttospeechskills dlx tts-skills tags