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Replace MCP server recommendations with LiveKit CLI (#54)

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* Use deepgram

* Switch Deepgram STT to nova-3 multi

* Replace MCP server recommendations with LiveKit CLI

Rewrite AGENTS.md and README.md to lead with the LiveKit CLI (`lk docs`)
as the primary way to give coding agents LiveKit documentation access.
The MCP server is retained as a secondary option for deeper IDE
integration.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Consolidate bottom CLI section to match node starter

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Update docs URLs to match new site structure

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Port remaining URL and content updates from Node starter PR

Updates docs URLs to match new site structure:
- /agents/build/ -> /agents/logic/ and /agents/start/
- /home/cloud/ -> /transport/media/
- /home/self-hosting/ -> /transport/self-hosting/local/
- /agents/ops/deployment/ -> /deploy/agents/
- Metrics/logging -> Agent Observability
- Voice pipeline description updated

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Ben Cherry
2026-03-11 09:24:23 -07:00
committed by GitHub
co-authored by Claude Opus 4.6
parent a7d870919a
commit 2c53ee3d15
2 changed files with 53 additions and 57 deletions
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README.md
+39 -32
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@@ -9,43 +9,50 @@ A complete starter project for building voice AI apps with [LiveKit Agents for P
The starter project includes:
- A simple voice AI assistant, ready for extension and customization
- A voice AI pipeline with [models](https://docs.livekit.io/agents/models) from OpenAI, Cartesia, and Deepgram served through LiveKit Cloud
- Easily integrate your preferred [LLM](https://docs.livekit.io/agents/models/llm/), [STT](https://docs.livekit.io/agents/models/stt/), and [TTS](https://docs.livekit.io/agents/models/tts/) instead, or swap to a realtime model like the [OpenAI Realtime API](https://docs.livekit.io/agents/models/realtime/openai)
- Eval suite based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/build/testing/)
- [LiveKit Turn Detector](https://docs.livekit.io/agents/build/turns/turn-detector/) for contextually-aware speaker detection, with multilingual support
- [Background voice cancellation](https://docs.livekit.io/home/cloud/noise-cancellation/)
- Integrated [metrics and logging](https://docs.livekit.io/agents/build/metrics/)
- A Dockerfile ready for [production deployment](https://docs.livekit.io/agents/ops/deployment/)
- A voice AI pipeline built on [LiveKit Inference](https://docs.livekit.io/agents/models/inference)
with [models](https://docs.livekit.io/agents/models) from OpenAI, Cartesia, and Deepgram. More than 50 other model providers are supported, including [Realtime models](https://docs.livekit.io/agents/models/realtime)
- Eval suite based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/start/testing/)
- [LiveKit Turn Detector](https://docs.livekit.io/agents/logic/turns/turn-detector/) for contextually-aware speaker detection, with multilingual support
- [Background voice cancellation](https://docs.livekit.io/transport/media/noise-cancellation/)
- Deep session insights from LiveKit [Agent Observability](https://docs.livekit.io/deploy/observability/)
- A Dockerfile ready for [production deployment to LiveKit Cloud](https://docs.livekit.io/deploy/agents/)
This starter app is compatible with any [custom web/mobile frontend](https://docs.livekit.io/agents/start/frontend/) or [SIP-based telephony](https://docs.livekit.io/agents/start/telephony/).
This starter app is compatible with any [custom web/mobile frontend](https://docs.livekit.io/frontends/) or [telephony](https://docs.livekit.io/telephony/).
## Coding agents and MCP
## Using coding agents
This project is designed to work with coding agents like [Cursor](https://www.cursor.com/) and [Claude Code](https://www.anthropic.com/claude-code).
This project is designed to work with coding agents like [Claude Code](https://claude.com/product/claude-code), [Cursor](https://www.cursor.com/), and [Codex](https://openai.com/codex/).
To get the most out of these tools, install the [LiveKit Docs MCP server](https://docs.livekit.io/mcp).
For your convenience, LiveKit offers both a CLI and an [MCP server](https://docs.livekit.io/reference/developer-tools/docs-mcp/) that can be used to browse and search its documentation. The [LiveKit CLI](https://docs.livekit.io/intro/basics/cli/) (`lk docs`) works with any coding agent that can run shell commands. Install it for your platform:
For Cursor, use this link:
**macOS:**
[![Install MCP Server](https://cursor.com/deeplink/mcp-install-light.svg)](https://cursor.com/en-US/install-mcp?name=livekit-docs&config=eyJ1cmwiOiJodHRwczovL2RvY3MubGl2ZWtpdC5pby9tY3AifQ%3D%3D)
For Claude Code, run this command:
```
claude mcp add --transport http livekit-docs https://docs.livekit.io/mcp
```console
brew install livekit-cli
```
For Codex CLI, use this command to install the server:
```
codex mcp add --url https://docs.livekit.io/mcp livekit-docs
**Linux:**
```console
curl -sSL https://get.livekit.io/cli | bash
```
For Gemini CLI, use this command to install the server:
```
gemini mcp add --transport http livekit-docs https://docs.livekit.io/mcp
**Windows:**
```console
winget install LiveKit.LiveKitCLI
```
The project includes a complete [AGENTS.md](AGENTS.md) file for these assistants. You can modify this file your needs. To learn more about this file, see [https://agents.md](https://agents.md).
The `lk docs` subcommand requires version 2.15.0 or higher. Check your version with `lk --version` and update if needed. Once installed, your coding agent can search and browse LiveKit documentation directly from the terminal:
```console
lk docs search "voice agents"
lk docs get-page /agents/start/voice-ai-quickstart
```
See the [Using coding agents](https://docs.livekit.io/intro/coding-agents/) guide for more details, including MCP server setup.
The project includes a complete [AGENTS.md](AGENTS.md) file for these assistants. You can modify this file to suit your needs. To learn more about this file, see [https://agents.md](https://agents.md).
## Dev Setup
@@ -74,7 +81,7 @@ Sign up for [LiveKit Cloud](https://cloud.livekit.io/) then set up the environme
- `LIVEKIT_API_KEY`
- `LIVEKIT_API_SECRET`
You can load the LiveKit environment automatically using the [LiveKit CLI](https://docs.livekit.io/home/cli/cli-setup):
You can load the LiveKit environment automatically using the [LiveKit CLI](https://docs.livekit.io/intro/basics/cli/):
```bash
lk cloud auth
@@ -85,7 +92,7 @@ lk app env -w -d .env.local
## Run the agent
Before your first run, you must download certain models such as [Silero VAD](https://docs.livekit.io/agents/build/turns/vad/) and the [LiveKit turn detector](https://docs.livekit.io/agents/build/turns/turn-detector/):
Before your first run, you must download certain models such as [Silero VAD](https://docs.livekit.io/agents/logic/turns/vad/) and the [LiveKit turn detector](https://docs.livekit.io/agents/logic/turns/turn-detector/):
```console
uv run python src/agent.py download-files
@@ -121,13 +128,13 @@ Get started quickly with our pre-built frontend starter apps, or add telephony s
| **React Native** | [`livekit-examples/voice-assistant-react-native`](https://github.com/livekit-examples/voice-assistant-react-native) | Native mobile app with React Native & Expo |
| **Android** | [`livekit-examples/agent-starter-android`](https://github.com/livekit-examples/agent-starter-android) | Native Android app with Kotlin & Jetpack Compose |
| **Web Embed** | [`livekit-examples/agent-starter-embed`](https://github.com/livekit-examples/agent-starter-embed) | Voice AI widget for any website |
| **Telephony** | [📚 Documentation](https://docs.livekit.io/agents/start/telephony/) | Add inbound or outbound calling to your agent |
| **Telephony** | [Documentation](https://docs.livekit.io/telephony/) | Add inbound or outbound calling to your agent |
For advanced customization, see the [complete frontend guide](https://docs.livekit.io/agents/start/frontend/).
For advanced customization, see the [complete frontend guide](https://docs.livekit.io/frontends/).
## Tests and evals
This project includes a complete suite of evals, based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/build/testing/). To run them, use `pytest`.
This project includes a complete suite of evals, based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/start/testing/). To run them, use `pytest`.
```console
uv run pytest
@@ -145,11 +152,11 @@ Once you've started your own project based on this repo, you should:
## Deploying to production
This project is production-ready and includes a working `Dockerfile`. To deploy it to LiveKit Cloud or another environment, see the [deploying to production](https://docs.livekit.io/agents/ops/deployment/) guide.
This project is production-ready and includes a working `Dockerfile`. To deploy it to LiveKit Cloud or another environment, see the [deploying to production](https://docs.livekit.io/deploy/agents/) guide.
## Self-hosted LiveKit
You can also self-host LiveKit instead of using LiveKit Cloud. See the [self-hosting](https://docs.livekit.io/home/self-hosting/) guide for more information. If you choose to self-host, you'll need to also use [model plugins](https://docs.livekit.io/agents/models/#plugins) instead of LiveKit Inference and will need to remove the [LiveKit Cloud noise cancellation](https://docs.livekit.io/home/cloud/noise-cancellation/) plugin.
You can also self-host LiveKit instead of using LiveKit Cloud. See the [self-hosting](https://docs.livekit.io/transport/self-hosting/local/) guide for more information. If you choose to self-host, you'll need to also use [model plugins](https://docs.livekit.io/agents/models/#plugins) instead of LiveKit Inference and will need to remove the [LiveKit Cloud noise cancellation](https://docs.livekit.io/transport/media/noise-cancellation/) plugin.
## License