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langflow-ai/langflow

Analysis updated 2026-06-20

147,774PythonAudience · developerComplexity · 3/5LicenseSetup · moderate

TLDR

Langflow is a visual drag-and-drop platform for building AI agents and workflows, letting you connect LLMs, tools, and databases on a canvas and instantly deploy them as APIs or MCP tools.

Mindmap

mindmap
  root((repo))
    What It Does
      Visual agent builder
      Drag and drop canvas
      Flow to API export
    Key Features
      Multi-agent support
      MCP server deploy
      Interactive playground
    Tech Stack
      Python backend
      Docker support
      Desktop app
    Integrations
      All major LLMs
      Vector databases
      LangSmith tracing
    Audience
      AI developers
      No-code builders
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What do people build with it?

USE CASE 1

Build a customer support chatbot by visually connecting an LLM, a vector database, and your company docs on a canvas.

USE CASE 2

Create a multi-step AI workflow and expose it as a REST API other applications can call.

USE CASE 3

Prototype different AI agent designs quickly by swapping components without rewriting code.

USE CASE 4

Deploy a flow as an MCP server so it becomes a tool that AI assistants like Claude can call directly.

What is it built with?

PythonReact FlowDocker

How does it compare?

langflow-ai/langflow521xueweihan/hellogithubytdl-org/youtube-dl
Stars147,774155,080140,207
LanguagePythonPythonPython
Setup difficultymoderateeasyeasy
Complexity3/51/52/5
Audiencedevelopergeneralgeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires Python 3.10-3.13 and uv or Docker, a Desktop app for Windows and macOS bundles all dependencies.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice (MIT).

In plain English

Langflow is a platform for building and deploying AI-powered agents and workflows. The basic problem it tackles is that wiring up large language models, tools, and data sources into a working agent normally takes a lot of custom code, and that experimenting with different combinations is slow. Langflow gives you a visual authoring experience on top of that work so that you can drag and connect components on a canvas, run them, and turn the result into something other applications can call. According to the README, Langflow comes with batteries included and supports all major LLMs, vector databases, and a growing library of AI tools. Highlight features listed include a visual builder interface for quickly getting started and iterating, source-code access in Python so you can customize any component, an interactive playground that lets you test and refine flows with step-by-step control, multi-agent orchestration with conversation management and retrieval, the option to deploy a flow as an API or export it as JSON for Python apps, and the option to deploy a flow as an MCP server so the flow becomes a tool for MCP clients. There are observability integrations with LangSmith and LangFuse, and the README also mentions enterprise-ready security and scalability. You can install Langflow as a Python package via uv (it requires Python 3.10 to 3.13), run it from source with make, or run it in Docker on port 7860. There is also a Langflow Desktop application for Windows and macOS that bundles all dependencies. You would use Langflow when you want to prototype an agent or chain visually, share it as a working API or MCP tool, and avoid managing too much custom infrastructure. The project is open source under the MIT license, written primarily in Python, and lists topics like agents, multi-agent, large language models, and react-flow.

Copy-paste prompts

Prompt 1
Using Langflow, design a flow that takes a PDF as input, chunks and embeds it into a vector database, and answers user questions about it.
Prompt 2
Show me how to install Langflow with uv on Python 3.11 and create my first working agent flow that calls OpenAI.
Prompt 3
Write a Python script that calls the Langflow REST API to run a flow named my-workflow and passes it a user message, then prints the response.
Prompt 4
Help me export a Langflow flow as JSON and load it into a Python app using the Langflow Python package.
Prompt 5
What Langflow components do I need to build a ReAct agent that can search the web and return a summarized answer?

Frequently asked questions

What is langflow?

Langflow is a visual drag-and-drop platform for building AI agents and workflows, letting you connect LLMs, tools, and databases on a canvas and instantly deploy them as APIs or MCP tools.

What language is langflow written in?

Mainly Python. The stack also includes Python, React Flow, Docker.

What license does langflow use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice (MIT).

How hard is langflow to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is langflow for?

Mainly developer.

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