---
title: n8n Integration
description: "How to trace n8n workflows in Langfuse, giving you observability over the LLM steps you build in the fair-code workflow automation platform."
seoTitle: n8n and Langfuse
sidebarTitle: n8n
logo: /images/integrations/n8n_icon.svg
---

# Integration: n8n

> [n8n](https://github.com/n8n-io/n8n) is a fair-code licensed workflow automation platform.

## Prompt Management Integration

  ![n8n node for
  langfuse](/images/docs/prompt-management-node-in-n8n-workflow.png)

Langfuse Prompt Management is available via an n8n node. Learn more in the [n8n Node documentation](/docs/prompts/n8n-node).

## Tracing Integration

### Officially Supported

Currently, there is no native n8n tracing integration. Please upvote the related GitHub discussion [here](https://github.com/orgs/langfuse/discussions/4397) if you are interested in this.

### Workarounds

While there is no native integration, there are several ways to trace your n8n AI workflows in Langfuse.

#### Using OpenRouter with Broadcast

You can use [OpenRouter](https://openrouter.ai/) as your LLM provider in n8n, and send traces to Langfuse using OpenRouter's [Broadcast feature](/integrations/gateways/openrouter#broadcast).

#### Community Supported

  ![n8n workflow with OpenAI model traced in
  Langfuse](/images/docs/n8n-nodes-openai-langfuse-workflow.png)

[@rorubyy](https://github.com/rorubyy) has created a n8n node for that wraps OpenAI models and sends tracing data to Langfuse. You can find it here: [rorubyy/n8n-nodes-openai-langfuse](https://github.com/rorubyy/n8n-nodes-openai-langfuse)

Alternatively, [@rwb-truelime](https://github.com/rwb-truelime) has developed [n8n-langfuse-shipper](https://github.com/rwb-truelime/n8n-langfuse-shipper), a Python project that ships n8n execution data to Langfuse using the OTEL (OpenTelemetry) API. This approach provides a broader integration by capturing workflow execution data from n8n and forwarding it to Langfuse for observability and tracing.

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/integrations/no-code/n8n.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.