TextToSpeechSkills
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Guide

LLM text-to-speech setup guide

This guide shows the simplest path from account to generated speech: create a scoped key, install the MCP tool, pick a voice template, and ask your LLM app to generate audio with readable expression tags.

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What does this guide cover?

The LLM text-to-speech setup guide explains how to connect TextToSpeechSkills to an LLM app without writing a custom integration first. The basic flow is to choose a paid plan, create a scoped workspace key, copy the MCP install command, pick voice templates the agent may use, and ask the LLM app to generate speech with readable expression tags. The same setup can validate markup, check credit use, create speech jobs, and return audio URLs while keeping billing and credentials controlled.

Easy LLM setup

Connect an LLM app without building an integration first

You do not need to build an integration first. Copy the MCP install command, paste it into your LLM app settings, and use the included skill instructions as your starting prompt.

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01Create a scoped workspace key.
02Copy the MCP install command into your LLM app.
03Pick approved voice templates for the agent.
04Ask for tagged speech and review the audio job.

Create a scoped key

Use a workspace key for the LLM app so billing, permissions, and rotation are easy to manage.

Install the MCP tool

Copy the install command from the dashboard into your LLM app. The agent receives approved speech tools immediately.

Use templates and tags

Tell the agent which voice template to use and let it add tags like [quiet], [excited], or [loud and angry].

When this helps

Non-technical users and teams setting up speech generation inside LLM apps usually need a repeatable path for writing, review, generation, billing, and reuse. The most important jobs here are create a scoped key, install the mcp tool, use templates and tags. 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 LLM text-to-speech setup, MCP TTS guide, connect text-to-speech to LLM, 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 LLM Text-to-Speech Setup Guide?

Non-technical users and teams setting up speech generation inside LLM apps 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?

You do not need to build an integration first. Copy the MCP install command, paste it into your LLM app settings, and use the included skill instructions as your starting prompt. 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.

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.Expressive TTS Markup for Product CopyGuide tone, pace, and delivery with simple inline tags like [quiet] and [loud and angry] before generating speech.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