mcpbeat

Deepgram Js Text To Speech

deepgram/deepgram-js-text-to-speech

Use when writing or reviewing JavaScript/TypeScript in this repo that calls Deepgram Text-to-Speech v1 (`/v1/speak`) for audio synthesis. Covers one-shot REST via `client.speak.v1.audio.generate` and streaming WebSocket via `client.speak.v1.createConnection()` / `connect()`. Use `deepgram-js-voice-agent` when you need full-duplex STT + LLM + TTS instead of one-way synthesis. Triggers include "TTS", "text to speech", "speak", "aura", "streaming TTS", and "speak.v1".

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
269
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/deepgram/deepgram-js-sdk --skill deepgram-js-text-to-speech

The instruction itself

11 sections, as written by the author

Using Deepgram Text-to-Speech (JavaScript / TypeScript SDK)

Convert text to audio with one-shot REST generation or low-latency streaming synthesis via /v1/speak.

When to use this product

  • REST (client.speak.v1.audio.generate) — render finished text into an audio response. Best for downloadable files, pre-generated prompts, batch synthesis.
  • WebSocket (client.speak.v1.createConnection() / connect()) — stream text in and receive audio out with lower latency. Best when an LLM is still producing tokens.

Use a different skill when:

  • You need the agent to also listen, think, and handle barge-in → deepgram-js-voice-agent.

Authentication

require("dotenv").config();

const { DeepgramClient } = require("@deepgram/sdk");

const deepgramClient = new DeepgramClient({
  apiKey: process.env.DEEPGRAM_API_KEY,
});

The repo examples use require("../dist/cjs/index.js"), but application code should normally import from @deepgram/sdk.

Quick start — REST (one-shot)

From examples/10-text-to-speech-single.ts:

const data = await deepgramClient.speak.v1.audio.generate({
  text: "Hello, this is a test of Deepgram's text-to-speech API.",
  model: "aura-2-thalia-en",
  encoding: "linear16",
  container: "wav",
});

console.log("Audio generated successfully", data);

generate(...) returns a BinaryResponse, not JSON. See examples/25-binary-response.ts for .stream(), .arrayBuffer(), .blob(), and .bytes() handling.

Quick start — WebSocket (streaming)

From examples/11-text-to-speech-streaming.ts:

const deepgramConnection = await deepgramClient.speak.v1.createConnection({
  model: "aura-2-thalia-en",
  encoding: "linear16",
});

deepgramConnection.on("message", (data) => {
  if (typeof data === "string" || data instanceof ArrayBuffer || data instanceof Blob) {
    console.log("Audio received");
  } else if (data.type === "Flushed") {
    deepgramConnection.close();
  }
});

deepgramConnection.connect();
await deepgramConnection.waitForOpen();

deepgramConnection.sendText({ type: "Speak", text: "Hello from streaming TTS." });
deepgramConnection.sendFlush({ type: "Flush" });

Key parameters / API surface

  • REST & WSS: model, encoding, sample_rate, container, bit_rate, callback, callback_method, tag, mip_opt_out.
  • REST response surface (examples/25-binary-response.ts): response.stream(), response.arrayBuffer(), response.blob(), response.bytes(), response.bodyUsed.
  • WSS client messages (src/api/resources/speak/resources/v1/client/Socket.ts): sendText(...), sendFlush(...), sendClear(...), sendClose(...).
  • WSS server events: binary audio payloads plus Metadata, Flushed, Cleared, Warning.

Limitations

Unlike the Python SDK, this repo does not include a hand-written TextBuilder helper. If you want incremental token buffering before sendText(...), build that helper in your application layer.

API reference (layered)

  • In-repo reference: reference.mdSpeak V1 Audio for REST; WSS behavior lives in src/CustomClient.ts and src/api/resources/speak/resources/v1/client/{Client,Socket}.ts.
  • Canonical OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
  • Canonical AsyncAPI (WSS): https://developers.deepgram.com/asyncapi.yaml
  • Context7: library ID /llmstxt/developers_deepgram_llms_txt
  • Product docs:
  • https://developers.deepgram.com/reference/text-to-speech/speak-request
  • https://developers.deepgram.com/reference/text-to-speech/speak-streaming
  • https://developers.deepgram.com/docs/tts-models

Gotchas

  • REST returns binary, not JSON. Treat the result like a streamed/binary body.
  • Use the custom client wrapper. src/CustomClient.ts patches binary WebSocket handling; the generated socket assumes JSON too aggressively.
  • createConnection() is lazy. Register handlers, then call connect() and waitForOpen().
  • Send Flush after your text. Without sendFlush({ type: "Flush" }), trailing audio may not be emitted promptly.
  • Streaming text is structured JSON. Send { type: "Speak", text }, not a raw string.
  • Audio payload shape varies by runtime. The same handler may receive string, ArrayBuffer, or Blob.
  • Pick encoding/container/sample rate that match your sink. Mismatches show up as static, silence, or unplayable files.

Example files in this repo

  • examples/10-text-to-speech-single.ts
  • examples/11-text-to-speech-streaming.ts
  • examples/25-binary-response.ts

Central product skills

For cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:

npx skills add deepgram/skills

This SDK ships language-idiomatic code skills; deepgram/skills ships cross-language product knowledge (see api, docs, recipes, examples, starters, setup-mcp).

How to use it

Copy the folder

Take deepgram/deepgram-js-text-to-speech from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference npx. Without those the skill loads but fails at the first command.