Hiveflow
Visual workflow orchestration for AI agents and automation
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
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.
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.
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.
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.
When teams consider Langflow, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
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.
Langflow requires Python 3.10, 3.11, 3.12, or 3.13. It also requires the uv package manager for installation and execution.
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.
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.
Langflow provides direct access to Python source code for every component, enabling full customization while maintaining integration with the visual workflow.
Yes. Langflow supports Docker deployment to major cloud providers, includes observability integrations, and is designed for enterprise security and scalability under the MIT license.
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