Langflow
Open-source visual builder for AI agents and retrieval workflows
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What this product helps you do
Langflow combines a drag-and-drop flow editor with a Python runtime and component system. Developers can connect model, embedding, vector-store, data, tool, agent, and MCP components; test flows in the playground; and expose them through the API or deploy the open-source application themselves. The core software is free, while model APIs, databases, and hosting can create separate costs.
Problems it solves
- Agent and retrieval prototypes require repetitive integration code
- Teams need a visual way to inspect and change multi-step AI flows
- Model, vector-store, data, and tool components use different interfaces
- Prototypes need a path from interactive testing to callable services
Langflow is an open-source Python framework and visual editor for composing AI applications. Its component library covers models, prompts, agents, data ingestion, embeddings, vector stores, tools, APIs, and MCP connections.
Builders can test a flow interactively, edit component code, and invoke completed flows through supported APIs. The MIT-licensed project can run locally or on infrastructure selected by the adopter, with external service costs handled separately.
Information
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Langflow
Open-source visual builder for AI agents and retrieval workflows
Langflow is an open-source Python framework and visual editor for composing AI applications. Its component library covers models, prompts, agents, data ingestion, embeddings, vector stores, tools, APIs, and MCP connections.
Builders can test a flow interactively, edit component code, and invoke completed flows through supported APIs. The MIT-licensed project can run locally or on infrastructure selected by the adopter, with external service costs handled separately.
What this product helps you do
Langflow combines a drag-and-drop flow editor with a Python runtime and component system. Developers can connect model, embedding, vector-store, data, tool, agent, and MCP components; test flows in the playground; and expose them through the API or deploy the open-source application themselves. The core software is free, while model APIs, databases, and hosting can create separate costs.
Problems it solves
- Agent and retrieval prototypes require repetitive integration code
- Teams need a visual way to inspect and change multi-step AI flows
- Model, vector-store, data, and tool components use different interfaces
- Prototypes need a path from interactive testing to callable services
Information
You are leaving botconomy for the provider’s website. Link verified 9/22/2026.
Related AI products
GOAT SDK
GOAT SDK is an MIT-licensed TypeScript and Python toolkit with wallet adapters, agent-framework adapters, and plugins for payments, tokens, markets, data, and other onchain actions.
Daizy
Daizy provides AI agents designed to enhance marketing, sales, and research efforts within financial services, automating tasks such as content generation and client engagement to increase productivity.
MagickML
MagickML provides a visual node builder for creating AI-agent workflows, combining model choice, document processing, custom nodes, event-driven execution, integrations, testing, and deployment with open-source code and hosted metered billing.