Convert text to MP3 speech audio in 50+ languages. x402 micropayment.
Convert text to MP3 speech audio in 50+ languages. x402 micropayment. That is what the text to speech api mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
Convert text to speech audio -- 20+ languages, base64 MP3 output. Google TTS engine, fast and reliable. Pay-per-call via x402 (USDC on Base L2) -- no API key, no signup, no rate-limit wall.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
The server publishes 1 tool. What each one is for:
media_text_to_speech — POSTPlenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Text To Speech API's toolset — media_text_to_speech — is a fair guide to whether it matches your workflow. It is maintained by Br0ski777; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| media_text_to_speech | POST |
{
"mcpServers": {
"text-to-speech": {
"url": "https://text-to-speech.api.klymax402.com/mcp"
}
}
}Configuration as documented by the project. Restart the client after saving.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.