Langflow

Visual Python framework for building, testing, and serving AI agents and retrieval workflows with reusable components.

Assemble a flow, test it with representative inputs, and connect the required model and retrieval services.

Access and pricing: The framework is open source. Deployment, model providers, retrieval services, and hosted support can create separate costs.

What it does well

The official site describes Langflow as a low-code builder for AI apps and agents, and for deploying MCP servers. It supports major language models and vector databases, lets you run a single agent or a group of agents, and gives them your components as tools. Flows are visual and reusable, you can customise them with Python, and they can be exposed as an API.

Who gets the most from it

People comfortable with a little Python who want to see their pipeline drawn out as a flow, test it, and then serve it. Pre-built flows and components give a starting point so you are not building from nothing.

Getting started in 10 minutes

Based on documentation, the site offers a desktop download, a free cloud account and a self-deploy route. Open a pre-built flow, swap in your own model credentials, run it with a representative input and inspect each step before wiring in real data.

Limits to check before you commit

The page says the same Langflow runs in open-source and cloud form, but model providers, retrieval services and any hosted support can add separate costs. The visible page did not state a licence, so check the GitHub repository.