// Find the right Deepgram documentation for any task. Use whenever someone needs help locating docs, understanding which API to use, or wants to ask questions about Deepgram. Covers all product areas: speech-to-text, text-to-speech, voice agents, audio intelligence, and self-hosted deployments.
| name | docs |
| description | Find the right Deepgram documentation for any task. Use whenever someone needs help locating docs, understanding which API to use, or wants to ask questions about Deepgram. Covers all product areas: speech-to-text, text-to-speech, voice agents, audio intelligence, and self-hosted deployments. |
Find the right docs for what you're building with Deepgram.
Have a question? Get answers from Deepgram's AI assistant at https://developers.deepgram.com/ask-ai.
Transcribe audio and video into text. Deepgram ships two actively maintained, next-gen model families — pick the one that matches your use case.
/v1/listen) — general-purpose transcription (captions, subtitles, batch files, live streams). Rich feature set including intelligence overlays (diarize, summarize, sentiment, topics, intents)./v2/listen) — conversational-audio transcription for voice agents and interactive assistants. Built-in turn-taking (EOT events, mid-session reconfig).Docs:
Convert text into natural-sounding speech.
Build conversational voice agents powered by Deepgram.
Analyze text and audio for sentiment, topics, intents, summaries, and more.
Run Deepgram on your own infrastructure.
Full reference for all Deepgram REST and WebSocket APIs.
For language-idiomatic code patterns (imports, async idioms, error handling, type shapes), install the Deepgram SDK's own skills. Every Deepgram SDK publishes 7 product skills plus a maintainer skill:
npx skills add deepgram/deepgram-python-sdk # Python
npx skills add deepgram/deepgram-js-sdk # JavaScript / TypeScript
npx skills add deepgram/deepgram-java-sdk # Java
npx skills add deepgram/deepgram-go-sdk # Go
npx skills add deepgram/deepgram-rust-sdk # Rust
npx skills add deepgram/deepgram-swift-sdk # Swift
npx skills add deepgram/deepgram-kotlin-sdk # Kotlin
npx skills add deepgram/deepgram-dotnet-sdk # C# / .NET
npx skills add deepgram/deepgram-browser-sdk # Browser TypeScript
api — consolidated REST + WebSocket API referencerecipes — minimal runnable feature snippets per languageexamples — full integration examples with third-party platformsstarters — runnable starter apps (framework × feature)setup-mcp — Deepgram MCP server installationFor direct documentation querying from your AI coding tool, use /deepgram:mcp to set up the Deepgram MCP server.
Deepgram API reference for speech-to-text, text-to-speech, voice agents, audio intelligence, and account management. Use whenever building with Deepgram APIs — REST or WebSocket. Covers authentication, all endpoints, query parameters, request/response schemas, and WebSocket message formats. Reference files are organized by domain: listen (STT), speak (TTS), agent (voice agents), read (text/audio intelligence), models, projects, auth, and self-hosted.
Find working Deepgram integration examples with third-party platforms and frameworks. Use whenever someone wants to integrate Deepgram with Twilio, LiveKit, LangChain, Vercel AI SDK, Discord, Vonage, Pipecat, Expo, FastAPI, Cloudflare Workers, Slack, Telegram, LlamaIndex, Zoom, Next.js, Nuxt, Django, SvelteKit, NestJS, Spring Boot, CrewAI, Riverside, SignalWire, and more. Examples are full runnable integration demos, not minimal feature snippets.
Find focused, runnable Deepgram recipes for a specific feature × language. Use whenever someone wants a minimal working code snippet for ONE feature (transcribe URL, diarize, smart-format, voice agent connect, etc.) rather than a full starter app. Recipes are under 50 lines, read DEEPGRAM_API_KEY from env, and ship with a runnable example_test. Covers Python, JavaScript, Go, .NET, Java, Rust, and the Deepgram CLI.
Clone a ready-to-run Deepgram demo app and start building on top of it. Use whenever someone wants a quick working demo, needs to prototype with Deepgram, or is starting a new project that uses speech-to-text, text-to-speech, voice agents, audio intelligence, or live streaming. Match the user's language, framework, and desired Deepgram feature to the right starter.
Replace with description of the skill and when to use it.
Set up the Deepgram MCP server for your AI coding tool. Checks whether the Deepgram CLI (dg/deepctl) is installed: if so, uses the local CLI MCP server (dg mcp) for full tool access; otherwise offers the hosted documentation MCP or suggests installing the CLI. Use whenever someone wants to install Deepgram's agentic tools, set up the MCP server, or connect their editor to Deepgram.