TextToSpeechSkills
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MCP for speech generation

Give LLM agents a safe text-to-speech tool

The TextToSpeechSkills MCP server lets agents prepare speech without guessing your billing rules or voice settings. They can validate markup, pick approved templates, preview credit use, create jobs, and return audio URLs through a narrow tool surface.

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Who is this for?

The TextToSpeechSkills MCP server gives LLM apps a controlled way to create speech. Instead of asking an agent to improvise API calls, you install a focused tool surface for validating expression markup, listing approved voice templates, previewing credit use, creating speech jobs, and retrieving audio URLs. The workflow is useful for non-technical users because setup is mostly copy and paste: create a scoped key, install the MCP command, choose allowed templates, and ask the LLM app to generate audio. Billing controls and keys remain separate from the prompt.

Easy LLM setup

LLM-ready even for non-technical teams

Connect it by copying one MCP command into your LLM app settings. The agent gets speech tools immediately, while keys and billing controls stay scoped.

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

Small tool surface

Agents get focused speech tools instead of broad account access, which makes reviews and permissions easier.

Templates over prompts

Approved templates keep brand voices steady while still letting agents add local expression tags.

Credit-aware generation

Usage previews and workspace permissions help teams keep automated audio generation under control.

When this helps

People connecting LLM apps to speech generation with MCP usually need a repeatable path for writing, review, generation, billing, and reuse. The most important jobs here are small tool surface, templates over prompts, credit-aware generation. 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 TTS MCP server, MCP voice tools, LLM text-to-speech, 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 TTS MCP Server?

People connecting LLM apps to speech generation with MCP 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?

Connect it by copying one MCP command into your LLM app settings. The agent gets speech tools immediately, while keys and billing controls stay scoped. 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.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