Langflow

Langflow is a visual builder for AI agents and RAG pipelines, built on LangChain. You design flows on a drag-and-drop canvas. Developers can edit Python components directly inside the flow. Every flow can be exposed as a REST API, an MCP server, or an OpenAI-compatible endpoint. An API is a way for apps to talk to each other. It installs via pip, Docker, or a desktop app. It is MIT licensed with over 149,000 GitHub stars. See langflow.org for current details.

Key Features

1. Drag-and-drop canvas

Design AI flows by dragging components onto a canvas. Connect models, prompts, and tools visually. You see the whole pipeline at once.

2. Editable Python components

Developers can open any component and edit its Python code. It gives code-level control inside a visual tool. Non-coders can ignore this part.

3. API and MCP endpoints

Every flow can be shared as a REST API, an MCP server, or an OpenAI-compatible endpoint. Other apps can call your flow directly.

4. Easy install

Install Langflow with pip, Docker, or the desktop app. Setup takes minutes on most machines. You can start building right away.

5. MIT open source

Langflow is MIT licensed open source. After DataStax acquired it in 2025, and IBM absorbed DataStax, it stays MIT licensed. The code remains free.

6. Langflow Store

Share flows by exporting them as JSON files. The Langflow Store lets you browse flows from other users. Reuse saves hours of building.

Frequently Asked Questions (FAQ)

Is Langflow still open source after the acquisition?

Yes. DataStax acquired Langflow in 2025 and DataStax is now part of IBM, but Langflow stays MIT licensed open source.

Who should use Langflow vs Flowise?

Choose Langflow if you are a developer who wants editable Python and API endpoints. Choose Flowise for quicker no-code prototyping by business users.

Do I need to know Python?

No, but it helps. You can build flows visually without Python, and edit components in Python only when you want extra control.

How do I share a flow?

Export any flow as a JSON file and send it to others. You can also publish flows to the Langflow Store.

How popular is Langflow?

It has over 149,000 GitHub stars — one of the most popular open-source AI builders, with plenty of examples and help.

Conclusion

Langflow suits developers building AI agents and RAG pipelines on LangChain. Its canvas, editable Python, and API endpoints turn ideas into working services. It is MIT open source with an easy install via pip, Docker, or desktop. Over 149,000 GitHub stars show how widely it is trusted. Check langflow.org for current docs, since features change fast.