Langflow vs n8n

Langflow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.

✨ Highlight features

• Visual builder interface to quickly get started and iterate.
• Source code access lets you customize any component using Python.
• Interactive playground to immediately test and refine your flows with step-by-step control.
• Multi-agent orchestration with conversation management and retrieval.
• Deploy as an API or export as JSON for Python apps.
• Deploy as an MCP server and turn your flows into tools for MCP clients.
• Observability with LangSmith, LangFuse and other integrations.
• Enterprise-ready security and scalability.

🖥️ Langflow Desktop

Langflow Desktop is the easiest way to get started with Langflow. All dependencies are included, so you don't need to manage Python environments or install packages manually.
Available for Windows and macOS.

📥 Download Langflow Desktop

⚡️ Quickstart

Install locally (recommended)

Requires Python 3.10–3.14 and uv (recommended package manager).

Install

From a fresh directory, run:

uv pip install langflow -U

The latest Langflow package is installed.
For more information, see Install and run the Langflow OSS Python package.

Run

Official release packages and tagged source archives disable automatic login by default. Set LANGFLOW_SUPERUSER_PASSWORD before starting Langflow, then sign in with the username langflow (or your configured LANGFLOW_SUPERUSER). Development branches retain automatic login by default. See authentication configuration.

To start Langflow, run:

uv run langflow run

Langflow starts at http://127.0.0.1:7860.

That's it! You're ready to build with Langflow! 🎉

📦 Other install options

Run from source

If you've cloned this repository and want to contribute, run this command from the repository root:

make run_cli

For more information, see DEVELOPMENT.md.

Docker

Set and export a strong password before starting the container (Bash):

read -rsp "Langflow administrator password: " LANGFLOW_SUPERUSER_PASSWORD; echo
export LANGFLOW_SUPERUSER_PASSWORD
docker run -p 7860:7860 -e LANGFLOW_SUPERUSER_PASSWORD langflowai/langflow:latest

Langflow is available at http://localhost:7860/. Sign in as langflow with the password you entered. Official Docker images require authentication by default.
If you already have an auto-login installation, follow the upgrade instructions before switching defaults.
For configuration options, see the Docker deployment guide.

🛡️ Security

For security information, see our Security Policy.

🚀 Deployment

Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to deploy Langflow, see our Langflow deployment guides.

⭐ Stay up-to-date

Star Langflow on GitHub to be instantly notified of new releases.

👋 Contribute

We welcome contributions from developers of all levels. If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.

❤️ Contributors

n8n – The Platform for AI Agents and Workflow Automation

Fair-code platform to build and deploy AI agents and workflows. Combine a visual canvas with custom code, run it self-hosted or in the cloud, and connect to 1500+ integrations. AI automation you can trust with real work, from prototype to production.

Key Capabilities

• AI-Native Automation Platform: Build and operationalize AI workflows and multi-step agents using your own data, models, and tools
• Model Flexibility, No Lock-In: Connect to OpenAI, Anthropic, Google, or open-source models and switch providers without changing your architecture
• From Prototype to Production: Design multi-step AI workflows with logic, tool use, human approvals, and full observability
• Code When You Need It: Combine visual building with JavaScript, Python, and npm packages for advanced AI workflows
• Enterprise-Ready AI: Self-host or deploy securely with role-based access, audit trails, and support for sensitive data
• Leverage What Already Exists: 1500+ integrations and 9,000+ workflow templates to connect AI with your existing systems

Quick Start

Try n8n instantly with our install script (requires Docker):

curl -fsSL https://get.n8n.io | sh

Or deploy manually with Docker:

docker volume create n8n_data
docker run -it --rm --name n8n -p 5678:5678 -v n8n_data:/home/node/.n8n docker.n8n.io/n8nio/n8n

Access the editor at http://localhost:5678

Resources

• 📚 Documentation
• 🔧 1500+ Integrations
• 💡 Example Workflows
• 🤖 AI & LangChain Guide
• 👥 Community Forum
• 📖 Community Tutorials

Support

Need help? Our community forum is the place to get support and connect with other users:
community.n8n.io

License

n8n is fair-code distributed under the Sustainable Use License and n8n Enterprise License.

• Source Available: Always visible source code
• Self-Hostable: Deploy anywhere
• Extensible: Add your own nodes and functionality

Enterprise Licenses available for additional features and support.

Additional information about the license model can be found in the docs.

Contributing

Found a bug 🐛 or have a feature idea ✨? Check our Contributing Guide for a setup guide & best practices.

Join the Team

Want to shape the future of automation? Check out our job posts and join our team!

What does n8n mean?

Short answer: It means "nodemation" and is pronounced as n-eight-n.

Long answer: "I get that question quite often (more often than I expected) so I decided it is probably best to answer it here. While looking for a good name for the project with a free domain I realized very quickly that all the good ones I could think of were already taken. So, in the end, I chose nodemation. 'node-' in the sense that it uses a Node-View and that it uses Node.js and '-mation' for 'automation' which is what the project is supposed to help with. However, I did not like how long the name was and I could not imagine writing something that long every time in the CLI. That is when I then ended up on 'n8n'." - Jan Oberhauser, Founder and CEO, n8n.io