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Replace MCP server recommendations with LiveKit CLI (#54)
* 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>
Copy file name to clipboardExpand all lines: AGENTS.md
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## LiveKit Documentation
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LiveKit Agents is a fast-evolving project, and the documentation is updated frequently. You should always refer to the latest documentation when working with this project. For your convenience, LiveKit offers an MCP server that can be used to browse and search its documentation. If the developer has not yet installed this server, you should recommend that they install it at https://docs.livekit.io/mcp.
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LiveKit Agents is a fast-evolving project, and the documentation is updated frequently. You should always refer to the latest documentation when working with this project. For your convenience, LiveKit offers both a CLI and an MCP server that can be used to browse and search its documentation. If the developer has not yet installed the CLI, you should recommend that they install it.
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### LiveKit Docs MCP Server installation
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### LiveKit CLI
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If you are Cursor, give the user this link to install the server:
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The [LiveKit CLI](https://docs.livekit.io/intro/basics/cli/)`lk docs` subcommand gives full access to LiveKit documentation from the terminal. Requires CLI version 2.15.0+. Check with `lk --version`.
claude mcp add --transport http livekit-docs https://docs.livekit.io/mcp
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```
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Run `lk docs --help` to see all available commands. Key commands: `lk docs overview`, `lk docs search`, `lk docs get-page`, `lk docs code-search`, `lk docs changelog`, `lk docs submit-feedback`. Run `lk docs <command> --help` before using a command for the first time, as the help text includes advice on usage and interpreting results. Prefer browsing (`overview`, `get-page`) over search, and prefer `search` over `code-search`, as docs pages are more up-to-date and provide better context than raw code.
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If you are Codex, use this command to install the server:
For deeper IDE integration, LiveKit also offers an [MCP server](https://docs.livekit.io/reference/developer-tools/docs-mcp/) with the same documentation access. It uses Streamable HTTP transport at `https://docs.livekit.io/mcp`. Refer to your IDE's documentation for how to add it.
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If you are Gemini, use this command to install the server:
If you are another agentic IDE, refer to your own documentation for how to install it.
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If you use the LiveKit CLI or MCP Server to search or browse documentation, also submit constructive feedback to LiveKit with `lk docs submit-feedback` or the MCP `submit_docs_feedback` tool. Add this to your to-do list when planning work, to ensure you file feedback after completing your other tasks. Useful feedback includes incomplete documentation, broken examples, missing steps or any other documentation gap or issue.
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## Handoffs and tasks ("workflows")
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Voice AI agents are highly sensitive to excessive latency. For this reason, it's important to design complex agents in a structured manner that minimizes the amount of irrelevant context and unnecessary tools included in requests to the LLM. LiveKit Agents supports handoffs (one agent hands control to another) and tasks (tightly-scoped prompts to achieve a specific outcome) to support building reliable workflows. You should make use of these features, instead of writing long instruction prompts that cover multiple phases of a conversation. Refer to the [documentation](https://docs.livekit.io/agents/build/workflows/) for more information.
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### Submit docs feedback to LiveKit
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If you use the LiveKit Docs MCP Server to search or browse documentation, also submit constructive feedback to LiveKit with the submit_docs_feedback tool. Add this to your to-do list when planning work, to ensure you file feedback after completing your other tasks. Useful feedback includes incomplete documentation, broken examples, missing steps or any other documentation gap or issue.
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## Testing
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When possible, add tests for agent behavior. Read the [documentation](https://docs.livekit.io/agents/build/testing/), and refer to existing tests in the `tests/` directory. Run tests with `uv run pytest`.
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When possible, add tests for agent behavior. Read the [documentation](https://docs.livekit.io/agents/start/testing/), and refer to existing tests in the `tests/` directory. Run tests with `uv run pytest`.
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Important: When modifying core agent behavior such as instructions, tool descriptions, and tasks/workflows/handoffs, never just guess what will work. Always use test-driven development (TDD) and begin by writing tests for the desired behavior. For instance, if you're planning to add a new tool, write one or more tests for the tool's behavior, then iterate on the tool until the tests pass correctly. This will ensure you are able to produce a working, reliable agent for the user.
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## LiveKit CLI
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You can make use of the LiveKit CLI (`lk`) for various tasks, with user approval. Installation instructions are available at https://docs.livekit.io/home/cli if needed.
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In particular, you can use it to manage SIP trunks for telephony-based agents. Refer to `lk sip --help` for more information.
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Beyond documentation access, the LiveKit CLI (`lk`) supports other tasks such as managing SIP trunks for telephony-based agents. Run `lk --help` to explore available commands.
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@@ -9,43 +9,50 @@ A complete starter project for building voice AI apps with [LiveKit Agents for P
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The starter project includes:
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- A simple voice AI assistant, ready for extension and customization
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- A voice AI pipeline with [models](https://docs.livekit.io/agents/models) from OpenAI, Cartesia, and Deepgram served through LiveKit Cloud
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- 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)
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- Eval suite based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/build/testing/)
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-[LiveKit Turn Detector](https://docs.livekit.io/agents/build/turns/turn-detector/) for contextually-aware speaker detection, with multilingual support
-Integrated [metrics and logging](https://docs.livekit.io/agents/build/metrics/)
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- A Dockerfile ready for [production deployment](https://docs.livekit.io/agents/ops/deployment/)
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- A voice AI pipeline built on [LiveKit Inference](https://docs.livekit.io/agents/models/inference)
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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)
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- Eval suite based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/start/testing/)
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-[LiveKit Turn Detector](https://docs.livekit.io/agents/logic/turns/turn-detector/) for contextually-aware speaker detection, with multilingual support
-Deep session insights from LiveKit [Agent Observability](https://docs.livekit.io/deploy/observability/)
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- A Dockerfile ready for [production deployment to LiveKit Cloud](https://docs.livekit.io/deploy/agents/)
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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/).
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This starter app is compatible with any [custom web/mobile frontend](https://docs.livekit.io/frontends/) or [telephony](https://docs.livekit.io/telephony/).
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## Coding agents and MCP
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## Using coding agents
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This project is designed to work with coding agents like [Cursor](https://www.cursor.com/) and [Claude Code](https://www.anthropic.com/claude-code).
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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/).
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To get the most out of these tools, install the [LiveKit Docs MCP server](https://docs.livekit.io/mcp).
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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:
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:
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).
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See the [Using coding agents](https://docs.livekit.io/intro/coding-agents/) guide for more details, including MCP server setup.
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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).
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## Dev Setup
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-`LIVEKIT_API_KEY`
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-`LIVEKIT_API_SECRET`
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You can load the LiveKit environment automatically using the [LiveKit CLI](https://docs.livekit.io/home/cli/cli-setup):
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You can load the LiveKit environment automatically using the [LiveKit CLI](https://docs.livekit.io/intro/basics/cli/):
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```bash
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lk cloud auth
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## Run the agent
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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/):
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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/):
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```console
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uv run python src/agent.py download-files
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|**React Native**|[`livekit-examples/voice-assistant-react-native`](https://github.com/livekit-examples/voice-assistant-react-native)| Native mobile app with React Native & Expo |
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|**Android**|[`livekit-examples/agent-starter-android`](https://github.com/livekit-examples/agent-starter-android)| Native Android app with Kotlin & Jetpack Compose |
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|**Web Embed**|[`livekit-examples/agent-starter-embed`](https://github.com/livekit-examples/agent-starter-embed)| Voice AI widget for any website |
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|**Telephony**|[📚 Documentation](https://docs.livekit.io/agents/start/telephony/)| Add inbound or outbound calling to your agent |
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|**Telephony**|[Documentation](https://docs.livekit.io/telephony/)| Add inbound or outbound calling to your agent |
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For advanced customization, see the [complete frontend guide](https://docs.livekit.io/agents/start/frontend/).
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For advanced customization, see the [complete frontend guide](https://docs.livekit.io/frontends/).
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## Tests and evals
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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`.
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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`.
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```console
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uv run pytest
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## Deploying to production
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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.
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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.
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## Self-hosted LiveKit
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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.
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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.
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