Hiveflow
Visual workflow orchestration for AI agents and automation
Langflow
Visual builder for AI agents and workflows with API deployment
Build and deploy AI-powered agents and workflows using a visual interface, Python customization, and built-in API/MCP servers. Supports major LLMs, vector databases, and multi-agent orchestration.
Overview
What is Langflow?
Langflow is a low-code platform for building and deploying AI-powered agents and workflows. It bridges visual development with code-level control, enabling developers to rapidly prototype and ship production-ready AI applications.
Core Capabilities
The platform features a drag-and-drop visual builder for assembling AI workflows, with full Python source code access for customizing any component. An interactive playground lets you test flows step-by-step before deployment. Langflow supports multi-agent orchestration with conversation management and retrieval, and integrates with all major LLMs and vector databases.
Deployment & Integration
Every workflow can be deployed as a REST API or exported as JSON for Python applications. Langflow also supports MCP (Model Context Protocol) server deployment, turning flows into tools for MCP clients. Built-in observability integrations include LangSmith and LangFuse. The platform runs on Python 3.10–3.13 and can be deployed via Docker to all major cloud providers. Released under the MIT license, Langflow is designed for both rapid experimentation and enterprise-scale production use.
Highlights
Visual builder with Python source code access for full customization
Deploy workflows as REST APIs or MCP servers for any framework
Multi-agent orchestration with conversation management and retrieval
Built-in observability via LangSmith, LangFuse, and other integrations
Pros
- Low-code visual interface accelerates prototyping and iteration
- Full Python customization for components without vendor lock-in
- Native API and MCP server deployment for flexible integration
- MIT license with Docker support for self-hosted deployments
Considerations
- Requires Python 3.10–3.13 and uv package manager setup
- Visual abstractions may add complexity for simple scripting tasks
- Recent CVE advisories require staying current with updates
- Windows Desktop upgrade path has known issues in version 1.6.0
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Fit guide
Great for
- Teams needing rapid AI workflow prototyping with visual tools
- Developers building multi-agent systems with conversation management
- Organizations requiring self-hosted, open-source AI orchestration
- Projects integrating AI workflows into existing Python applications
Not ideal when
- Teams without Python development experience or infrastructure
- Projects requiring non-Python runtime environments exclusively
- Use cases needing guaranteed long-term API stability without updates
- Simple single-LLM integrations better served by direct API calls
How teams use it
Customer Support Agent
Deploy a multi-agent workflow as an API that routes inquiries, retrieves knowledge base articles, and escalates complex cases to human agents.
Document Processing Pipeline
Build a visual workflow that ingests PDFs, extracts structured data using LLMs, stores embeddings in vector databases, and exposes results via REST API.
MCP Tool Integration
Convert internal workflows into MCP server tools that AI assistants like Claude can discover and invoke within conversational interfaces.
Research Assistant Prototype
Rapidly iterate on a multi-step agent that searches databases, summarizes findings, and generates reports using the interactive playground before production deployment.
Tech snapshot
Python51%
TypeScript25%
JavaScript23%
CSS1%
Makefile1%
Dockerfile1%
Frequently asked questions
What Python versions does Langflow support?
Langflow requires Python 3.10, 3.11, 3.12, or 3.13. It also requires the uv package manager for installation and execution.
Can I deploy Langflow workflows without using the visual interface?
Yes. Workflows can be exported as JSON and integrated directly into Python applications, or deployed as standalone APIs without ongoing use of the visual builder.
What is MCP server deployment?
Langflow can deploy workflows as Model Context Protocol (MCP) servers, allowing AI clients like Claude to discover and use your flows as callable tools within conversations.
How do I customize components beyond the visual interface?
Langflow provides direct access to Python source code for every component, enabling full customization while maintaining integration with the visual workflow.
Is Langflow suitable for production enterprise deployments?
Yes. Langflow supports Docker deployment to major cloud providers, includes observability integrations, and is designed for enterprise security and scalability under the MIT license.
Project at a glance
Active- Stars
- 144,037
- Watchers
- 144,037
- Forks
- 8,332
LicenseMIT
Repo age2 years old
Last commityesterday
Self-hostingSupported
Primary languagePython
Last synced yesterday