Langflow: Low-Code Visual AI Agent Builder
Per the official site, "Langflow is a powerful tool to build and deploy AI agents and MCP servers." It is the largest-by-community open-source visual builder in the agent space, with 138k+ GitHub stars as of mid-2026. The combination of visual canvas, LangChain-aligned components, and explicit MCP server building puts Langflow in a category of its own among free open-source platforms.
The 30-second version
- What: low-code visual agent and MCP server builder, open source
- Who: developers and ops teams who want a canvas with LangChain components
- Price: self-host free; free enterprise-grade cloud option; paid tiers for teams
- Best at: visual agent building with LangChain compatibility and MCP server output
- Verdict: pick Langflow when you want the largest open-source community and LangChain alignment
What Langflow actually is
Langflow is a visual canvas for building AI agents. You drag components onto the canvas, connect them, and ship. The components map to LangChain primitives (LLMs, prompts, retrievers, agents, tools), which means flows built in Langflow can be exported to LangChain Python code if you want to graduate to raw framework use later.
The 2026 angle: Langflow can also build MCP servers. You can use the visual canvas to assemble a tool, then expose it via MCP for any MCP-compatible client to consume. That makes Langflow useful both as an agent builder and as a tool-server builder.
Per the homepage, Langflow ships state flows (visual state machines for agent control), reusable components, and rapid iteration. The community size (138k stars) means tutorials, templates, and third-party integrations are plentiful.
Key capabilities
- Open-source visual agent builder
- 138k+ GitHub stars (largest in the open-source visual category)
- LangChain-aligned components (export to Python possible)
- MCP server building from the same canvas
- All major LLMs and vector databases supported
- Self-host or free enterprise-grade cloud
- Visual state flows for agent control
- Reusable components and templates
Pricing
Self-hosted Langflow is free. The homepage advertises "a free, enterprise-grade cloud" option. Paid tiers exist for teams that need shared observability, deployment, or premium support. Check the Langflow site for current pricing.
Who Langflow fits
- LangChain developers who want a visual canvas without abandoning the framework
- Teams building both agents and MCP servers from one tool
- Builders who value community size and template libraries
- Operators who want a free managed cloud option
Who Langflow does not fit
- Pure non-technical users (some developer comfort still helps)
- Teams who do not use LangChain and would rather not inherit its mental model
- Multi-agent role-based work (CrewAI is more direct)
Langflow vs Dify and Flowise
| Axis | Langflow | Dify | Flowise |
|---|---|---|---|
| Community size | 138k+ GitHub stars (largest) | Strong | Strong |
| Framework alignment | LangChain | Self-contained | LangChain-influenced |
| MCP server building | Yes (explicit) | Via custom integration | Via custom integration |
| Cloud option | Free enterprise-grade | $59/workspace/month | Paid |
| SDKs | Python via LangChain export | APIs + SDK | TypeScript + Python |
| Best for | LangChain devs + community | Customer-facing LLM apps | Canvas + dual SDK |
Pros and cons
Pros:
- Largest community in the open-source visual builder tier
- LangChain compatibility means you can graduate to raw framework if needed
- Explicit MCP server building is rare
- Free enterprise-grade cloud is genuinely free
Cons:
- If you do not use LangChain, you inherit some of its concepts you may not want
- Setup curve for self-hosting
- Less product-shaped for shipping customer-facing apps than Dify
How I'd use Langflow on SellerShorts
I tested Langflow for building a tool that wraps as an MCP server. The visual canvas made it easy to chain an LLM, a tool, and a transformation step, then expose the whole thing via MCP. A SellerShorts tool builder could use the same pattern to ship a custom MCP server that any AI Tool buyer can plug into Claude Desktop or Claude Code. That use case alone makes Langflow worth knowing in 2026.
Try Langflow
Get started with Langflow
Self-host the open source version free, or use the free enterprise-grade cloud option.
Selling on Amazon and want AI tools sized for your stack? See the Amazon AI hub.
Frequently asked questions
What is Langflow?
Per the official site, 'Langflow is a powerful tool to build and deploy AI agents and MCP servers.' It is open source with 138k+ GitHub stars and supports drag-and-drop visual building, all major LLMs, vector databases, and a growing AI tools library. Self-host free or use the managed cloud.
Is Langflow free?
Yes. The open-source version is free under a permissive license. Langflow also offers 'a free, enterprise-grade cloud' option per the homepage. Paid tiers exist for teams that need shared infrastructure and observability beyond the free cloud.
Langflow vs Dify vs Flowise: which should I pick?
All three are visual open-source LLM app builders. Langflow leans LangChain-aligned and has the largest community (138k GitHub stars). Dify is the most product-shaped for customer-facing AI apps. Flowise has dual TypeScript and Python SDKs as the differentiator. Pick Langflow when you want community size and LangChain compatibility.
Does Langflow build MCP servers?
Yes. The Langflow homepage explicitly calls out MCP server building. You can use Langflow's visual canvas to assemble an MCP-compatible tool, then expose it to any MCP client (Claude Desktop, Claude Code, ChatGPT with MCP support).