n8n-nodes-mlflow

An n8n community node that integrates OpenAI-compatible chat models with MLflow Tracing, giving you full observability into every LLM call directly from your n8n workflows.

npm package: https://www.npmjs.com/package/n8n-nodes-mlflow

Features

• Support for OpenAI-compatible chat models (e.g., gpt-4.1-mini, gpt-4o, and any LiteLLM/LocalAI endpoint)
• Automatic MLflow tracing for every LLM request and response
• Chat session grouping — traces are linked by sessionId for multi-turn conversation tracking
• Custom metadata injection: sessionId, userId, and arbitrary structured JSON
• Compatible with self-hosted MLflow and Databricks-hosted MLflow

n8n is a fair-code licensed workflow automation platform.

Installation
Credentials
Operations
Compatibility
Resources
Version history

Installation

Follow the installation guide in the official n8n documentation for community nodes.

Community Nodes (Recommended)

For n8n v0.187+, install directly from the UI:

1. Go to Settings → Community Nodes
2. Click Install
3. Enter n8n-nodes-mlflow in the npm package name field
4. Agree to the risks of using community nodes
5. Select Install

Docker Installation

A preconfigured Docker setup is available in the docker/ directory:

1. Build the Docker image

   cd docker
   docker build --progress=plain -f docker/Dockerfile -t n8n-nodes-mlflow .
   

2. Run the container

   docker run -it --rm \
     --name n8n-mlflow \
     -p 5678:5678 \
     -e GENERIC_TIMEZONE="America/New_York" \
     -e TZ="America/New_York" \
     -e N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS=true \
     -e N8N_RUNNERS_ENABLED=true \
     -v n8n_data:/home/node/.n8n \
     n8n-nodes-mlflow:latest
   

You can now access n8n at http://localhost:5678

Manual Installation

# Go to your n8n installation directory
cd ~/.n8n
# Install the node
npm install n8n-nodes-mlflow
# Restart n8n to apply the node
n8n start

Credentials

This credential authenticates your OpenAI-compatible LLM endpoint and configures where MLflow traces are sent.

OpenAI Settings

Field	Required	Description	Example
OpenAI API Key	Yes	API key for your OpenAI-compatible endpoint	sk-abc123...
OpenAI Base URL	No	Override the default endpoint base URL	https://api.openai.com/v1

MLflow Settings

Field	Required	Description	Example
MLflow Tracking URI	Yes	Your MLflow tracking server URI	http://localhost:5000 or databricks
MLflow Experiment ID	Yes	Experiment ID where traces will be logged	1234567890

Databricks users: Set the Tracking URI to databricks and provide your Databricks personal access token as the MLflow Tracking Token.

Operations

The node exposes MLflow tracing fields that attach structured context to every trace span logged to your MLflow experiment.

MLflow Tracing Fields

Field	Type	Description
sessionId	string	Groups related traces into a single chat session (mlflow.trace.session)
userId	string	Identifies the end user making the request (mlflow.trace.user)
customMetadata	object	Arbitrary JSON attached to the trace as span metadata

Example Setup

Field	Example Value
Session ID	{{$json.sessionId}}
User ID	test-user
Custom Metadata (JSON)	Any JSON value

Visual Examples

1. Node Configuration UI: Sample n8n workflow using the OpenAI MLflow node.

2. Workflow Setup: A typical workflow using this node.

3. n8n Chat: An example chat interaction in n8n.

4. MLflow Trace: The resulting trace logged in MLflow.

5. MLflow Session Grouping: Traces grouped by chat session in MLflow.

Compatibility

• Requires n8n version 1.0.0 or later
• Requires Node.js >= 20.15
• Compatible with:
  • OpenAI official API (https://api.openai.com)
  • Any OpenAI-compatible LLM (e.g. via LiteLLM, LocalAI, Azure OpenAI)
  • Databricks-hosted MLflow, and self-hosted MLflow instances

Resources

• n8n Community Node Docs
• MLflow Tracing Documentation
• MLflow GitHub
• n8n Community Forum

Version History

• v0.1.0 — Initial release with OpenAI + MLflow tracing integration, session grouping, and custom metadata support

License

Apache 2.0 © 2025