README

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:
shell
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:
shell
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:
shell
make run_cli

For more information, see DEVELOPMENT.md.

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

Top issues

Discussions

Latest release

What's Changed
 🐛 Bug Fixes
 fix(deps): backport filelock 4 upgrade to 1.13.1 by @Adam-Aghili in https://github.com/langflow-ai/langflow/pull/15966
 fix: confine Git loader files to repository by @erichare in https://github.com/langflow-ai/langflow/pull/15972
 fix(oracle): confine loader local file access by @erichare in https://github.com/langflow-ai/langflow/pull/15973
 fix(security): protect MCP component reserved fields by @erichare in https://github.com/langflow-ai/langflow/pull/15974
 fix(security): isolate MCP batch login and request state by @erichare in https://github.com/langfl