# Connect n8n to Lark (Feishu)

Source: https://langbot.app/docs/en/recipes/n8n/lark

Step-by-step guide to running your n8n app as a Lark (Feishu) bot with LangBot: n8n setup, bot credentials, networking, testing and troubleshooting.

This recipe puts your n8n app behind a Lark (Feishu) bot. LangBot receives messages from Lark (Feishu), runs them through a pipeline, and sends the answer back, so you do not write any platform code.

n8n runs the workflow; LangBot handles the chat platform, sessions and delivery and calls your workflow through a webhook for every message.

## What you need

- A running LangBot instance: [LangBot Cloud](https://space.langbot.app/cloud) (no server needed) or a [self-hosted deployment](https://langbot.app/docs/en/deploy/langbot/docker.md) with Docker or `uvx langbot`.
- A n8n account or instance that LangBot can reach over the network.
- A Feishu or Lark custom app (`app_id` and `app_secret`). The one-click setup in LangBot can create and authorize it for you.

## Networking

The default WebSocket long connection needs no public IP. Where long connection is unavailable (for example some Lark international setups), webhook mode requires a public HTTPS address; LangBot Cloud includes one.

## 1. Prepare n8n

1. Start the workflow with a **Webhook** or **On chat message** trigger. Set **Response Mode** to **Streaming** if you want streamed replies.
2. Answer with an **AI Agent** node (streaming) or a **Respond to Webhook** node whose response key matches LangBot's output key.
3. Click **Active** to enable the workflow and copy its production webhook URL.

## 2. Create a pipeline

Open **Pipelines** in the LangBot WebUI, create a pipeline (or edit the default one) and set **AI** as follows. If the runner is not listed, install the official runner plugin from **Plugins** or the [LangBot Space marketplace](https://space.langbot.app/market).

| Field               | Value                                                      |
| ------------------- | ---------------------------------------------------------- |
| Runner              | **n8n** (official n8n workflow runner plugin)              |
| Webhook URL         | The workflow's production webhook URL                      |
| Authentication Type | None, Basic Auth, JWT or Header, matching the trigger node |

## 3. Create the Lark (Feishu) bot

1. Create a bot with the **Lark** adapter, select the platform domain (Feishu or Lark) and use **One-Click Setup**, or enter `app_id` and `app_secret` manually.
2. Add the message permissions and event subscriptions from the guide (and the card permissions if you want streaming cards), then publish an app version.

## 4. Bind and test

Open the bot, select the pipeline you created, save and make sure the bot is enabled.

Search for the bot in Feishu/Lark, send it a direct message, then add it to a group and mention it.

## Troubleshooting

- Empty replies: the key in **Respond to Webhook** must match the output key configured in LangBot.
- The test URL only works while the n8n editor is listening; use the production URL of an active workflow.
- No messages arrive: confirm the app version is published and the event subscription uses the same mode (long connection or webhook) as LangBot.
- Check **Monitoring** in the WebUI: every message, pipeline run and error is recorded there.

## FAQ

### Do I need a server with a public IP for Lark (Feishu)?

Not necessarily. The default WebSocket long connection needs no public IP. Where long connection is unavailable (for example some Lark international setups), webhook mode requires a public HTTPS address; LangBot Cloud includes one.

### Does the Lark (Feishu) bot support streaming replies?

Yes. Enable streaming on the bot; the AI back end must also stream. See the [platform feature matrix](https://langbot.app/docs/en/insight/platform-features.md) for details.

### Can the same n8n setup serve other platforms too?

Yes. A pipeline can be bound to many bots, so one configuration can answer on several platforms at once.

## Related guides

- [Full Lark (Feishu) setup guide](https://langbot.app/docs/en/usage/platforms/lark.md)
- [Full n8n runner guide](https://langbot.app/docs/en/usage/pipelines/n8n.md)
- Other AI back ends on Lark (Feishu): [Dify](https://langbot.app/docs/en/recipes/dify/lark.md) · [Coze](https://langbot.app/docs/en/recipes/coze/lark.md) · [Langflow](https://langbot.app/docs/en/recipes/langflow/lark.md) · [DeepSeek](https://langbot.app/docs/en/recipes/deepseek/lark.md) · [OpenAI (ChatGPT models)](https://langbot.app/docs/en/recipes/openai/lark.md)
- n8n on other platforms: [Telegram](https://langbot.app/docs/en/recipes/n8n/telegram.md) · [Discord](https://langbot.app/docs/en/recipes/n8n/discord.md) · [Slack](https://langbot.app/docs/en/recipes/n8n/slack.md) · [DingTalk](https://langbot.app/docs/en/recipes/n8n/dingtalk.md) · [WeCom (internal app)](https://langbot.app/docs/en/recipes/n8n/wecom.md) · [WeCom Intelligent Bot](https://langbot.app/docs/en/recipes/n8n/wecombot.md)