Langflow
Open SourceBuild and deploy AI agents on a visual canvas.
Published 27 September 2026Last updated 31 October 2026
Scores
Popularity3/5
Established
A visual, drag-and-drop builder for LangChain/LangGraph agents, MIT-licensed with a large plugin ecosystem. It sits alongside Dify and Flowise as one of three comparable visual AI-app builders rather than a standout leader, and visual LLM-app building itself is a narrow slice of AI tooling most developers never open.
Learning Curve2/5
Easy
The drag-and-drop canvas and playground let someone assemble a working agent or RAG flow without framework code, which is the lowest barrier to entry in this space.
Flexibility4/5
Flexible
Model-, API-, and database-agnostic with custom Python components and API/code export, though a visual canvas is inherently more constrained than writing orchestration code directly.
Performance3/5
Average
Fine for prototyping and moderate production flows, but a visual runtime adds overhead and large complex graphs are harder to optimize than hand-written pipelines.
Portability5/5
No lock-in
Open source and self-hostable with no lock-in to a single model or vector store, and flows export to portable API endpoints or Python code.
About Langflow
Langflow is an open-source, low-code platform for building AI agents and retrieval-augmented generation (RAG) workflows on a visual canvas. Developers wire components together (models, prompts, tools, vector stores, memory, and custom logic) into a flow, then run and refine it in a built-in playground. It is Python-based and agnostic to any model, API, or database, so one flow can mix hosted and local models with different vector stores.
Every flow is also an endpoint. Langflow serves flows through its own API and as MCP tools, so an application or another agent can call them directly, and a flow can be exported as JSON or extended with custom Python components when the built-in ones are not enough. It works as an MCP client too, so a flow can use tools from other MCP servers.
The project is maintained under DataStax, now part of IBM, and the code is MIT-licensed with no paid edition. It runs three ways: Langflow Desktop, a free local app for macOS and Windows; the Python package; or the official Docker image with PostgreSQL on a server you run. DataStax's hosted version was removed from its Astra platform in 2026, so there is no first-party managed Langflow, and sharing it with a team means self-hosting it.
Key Features
- Drag-and-drop canvas for composing agents and RAG pipelines, with a built-in playground
- Components for most model providers, local model runtimes, and vector stores
- Every flow served through the Langflow API, and each project exposed as an MCP server
- MCP client support, so flows can call tools from other MCP servers
- Custom Python components when the built-in ones are not enough
- Runs as the free Langflow Desktop app, a Python package, or an official Docker image
Pros
- The visual builder makes agent and RAG prototyping fast and approachable
- MIT-licensed with no paid edition, and no lock-in to one model or vector store
- Flows become API endpoints and MCP tools without extra code
- A large, active open-source community
Cons
- Visual canvases become hard to manage for very large or complex flows
- Less fine-grained control than writing a code-first framework directly
- No first-party managed cloud, so sharing it with a team means running a server
- A production setup needs PostgreSQL, a fixed secret key, and Redis once it runs more than one worker
Langflow Pricing
Open Source- MIT-licensed, with every feature and no usage limits
- Runs as Langflow Desktop, the Python package, or the Docker image on your own server
Tech Stacks with Langflow
Langflow Self-Hosted
Infrastructure
InfrastructureRun Langflow, the open-source visual builder for AI agents and RAG pipelines, in Docker on a server you control. A database keeps the flows, users, and message history (PostgreSQL by default, SQLite for a trial), and every flow your team builds becomes an API endpoint and an MCP tool that applications and other agents can call.
Tools Related to Langflow
Works well with Langflow(1)
Langflow is a visual canvas for composing LangChain-style components, giving a drag-and-drop way to build the flows LangChain expresses in code.
Integrates with Langflow(4)
Langflow ships a first-party OpenAI component for using OpenAI models directly inside a flow.
Langflow ships a first-party Anthropic component for using Claude models directly inside a flow.
Langflow includes an Ollama component for wiring locally served open models into a flow.
Langflow provides Hugging Face components for using hosted or local Hub models inside a flow.
Alternatives to Langflow(3)
Langflow is built around the model pipeline, with components for models, prompts, tools, and vector stores; n8n is a general automation tool with 500+ app integrations and an AI Agent node. Pick Langflow for agent and RAG logic, n8n when the agent has to reach many business apps.
Dify is a full LLM app platform with a workflow canvas, built-in RAG knowledge bases, team workspaces, and published web apps; Langflow is a lighter MIT-licensed canvas for wiring LangChain-style components into flows served as an API. Pick Dify for a complete product non-developers can run, Langflow to embed a pipeline in your own code.
Langflow is a free, MIT-licensed canvas for wiring models, prompts, tools, and vector stores into agent and RAG pipelines served as an API; AutoGPT pairs its workflow canvas with ready-made business Experts and a hosted subscription. Pick Langflow to build a pipeline into your own product, AutoGPT for business tasks run for you.