Langflow
Visual low-code builder for AI agents and RAG workflows
Founded
2023
Starting Price
Free
Category
Workflow Automation
Last updated February 26, 2026
About Langflow
Langflow is an open-source, low-code platform for visually building and deploying AI-powered agents and workflows. Its drag-and-drop canvas connects LLMs, vector stores, prompts, and data sources without writing glue code, while still allowing full Python customization. Every flow can be deployed as a REST API or MCP server, making it easy to integrate AI capabilities into any application.
Pros & Cons
Pros
- Fully open-source and free to self-host with no license costs
- Intuitive drag-and-drop canvas accelerates AI prototyping
- Supports multi-agent systems and RAG pipelines out of the box
- Every workflow deployable as a REST API or MCP server instantly
- Python customization available for any component
Key Features
Visual Drag-and-Drop Canvas
Build AI workflows by connecting components on an intuitive canvas — no boilerplate code required. Link LLMs, retrievers, prompts, and databases in minutes.
Multi-Agent Orchestration
Design and run multi-agent systems where multiple AI assistants collaborate, with built-in conversation management and retrieval support.
RAG Pipeline Builder
Construct Retrieval Augmented Generation pipelines that combine your proprietary data with language models for accurate, context-aware responses.
API & MCP Server Deployment
Deploy any flow as a REST API or as a Model Context Protocol (MCP) server, turning workflows into reusable tools for any framework or stack.
Interactive Playground
Test and refine flows step-by-step in the built-in playground with immediate feedback before deploying to production.
Python Customization
Access and modify the Python source code of any component for full transparency and control over custom logic and non-standard integrations.
Pricing
Open Source
Free/forever
- Full visual flow builder
- Self-hosted deployment
- All core components and integrations
- REST API & MCP server export
- Community support
Best For
RAG Chatbot Development
Rapidly build document Q&A chatbots that retrieve from your own knowledge base by connecting a vector store, embeddings model, and LLM on the visual canvas.
AI Agent Prototyping
Design and test multi-step AI agents with tool use and memory without writing orchestration code, then export to a production API when ready.
Internal Workflow Automation
Automate internal processes by chaining LLM calls with data sources, APIs, and custom Python logic into a single deployable flow.
AI Education and Research
Teach or learn AI concepts like prompt chaining, retrieval, and agent patterns using the visual interface as an interactive sandbox.
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