MCPInstall

deepgram-js-text-to-speech

by deepgram OfficialMedia & Creative

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".

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/deepgram/deepgram-js-sdk --skill deepgram-js-text-to-speech
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads deepgram-js-text-to-speech automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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)

  1. In-repo reference: reference.md → Speak V1 Audio for REST; WSS behavior lives in src/CustomClient.ts and src/api/resources/speak/resources/v1/client/{Client,Socket}.ts.
  2. Canonical OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
  3. Canonical AsyncAPI (WSS): https://developers.deepgram.com/asyncapi.yaml
  4. Context7: library ID /llmstxt/developers_deepgram_llms_txt
  5. Product docs:

Gotchas

  1. REST returns binary, not JSON. Treat the result like a streamed/binary body.
  2. Use the custom client wrapper. src/CustomClient.ts patches binary WebSocket handling; the generated socket assumes JSON too aggressively.
  3. createConnection() is lazy. Register handlers, then call connect() and waitForOpen().
  4. Send Flush after your text. Without sendFlush({ type: "Flush" }), trailing audio may not be emitted promptly.
  5. Streaming text is structured JSON. Send { type: "Speak", text }, not a raw string.
  6. Audio payload shape varies by runtime. The same handler may receive string, ArrayBuffer, or Blob.
  7. 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).

FAQ

What does the deepgram-js-text-to-speech skill do?

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".

How do I install deepgram-js-text-to-speech?

Run npx skills add https://github.com/deepgram/deepgram-js-sdk --skill deepgram-js-text-to-speech in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/deepgram-js-text-to-speech/ (personal) or .claude/skills/deepgram-js-text-to-speech/ (project).

Which AI agents can use deepgram-js-text-to-speech?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is deepgram-js-text-to-speech safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains deepgram-js-text-to-speech?

It is published by deepgram in deepgram/deepgram-js-sdk, and it is an official skill from the maker of the technology it covers. It has 62 recorded installs.

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