n8n vs LangChain: Workflow Tool or Framework?
n8n is a workflow platform where you draw the steps on a canvas, and LangChain is a framework where you write them in code. Pick n8n when the job is “when X happens, do these steps” and you want a visual tool, LangChain when you are building an LLM application yourself, and neither if you want an agent that is already built. We make that third kind, POLYROB, and its autonomous runs stop at 150 steps and $2.00 by default (docs/[email protected]), so we can tell you what each approach leaves for you to build.
This page compares the two on what their own repositories and docs say. Every fact about n8n or LangChain was read on 2026-11-14 from the README, the LICENSE file or the n8n docs, and links to the source. POLYROB gets its own section near the end, including where it loses.
How do n8n and LangChain differ?
| n8n | LangChain | |
|---|---|---|
| What its README calls it | “Fair-code platform to build and deploy AI agents and workflows” | “a framework for building agents and LLM-powered applications” |
| How you build | Visual canvas, with JavaScript, Python and npm packages where you need code | Write code against a standard interface for models, embeddings and vector stores |
| Language | Runs on Node.js; code steps take JavaScript or Python | Python, with LangChain.js for JavaScript and TypeScript |
| Integrations | “1500+ integrations” and “9,000+ workflow templates” | Integrations for chat and embedding models, tools and vector stores, listed in its docs |
| License | Sustainable Use License, plus an Enterprise License for .ee. files | MIT |
| Hosting | Self-host with Docker, or n8n Cloud | A library: you host whatever you build. LangSmith Deployment is the vendor’s platform for deploying agents |
| Agent orchestration | Agent and workflow nodes on the canvas | Points you to LangGraph for more advanced orchestration |
Sources: the n8n README and the LangChain README, fetched 2026-11-14.
What is the main difference between n8n and LangChain?
n8n is a product you run. LangChain is a library you build with.
With n8n you install one program, open the editor on port 5678 and connect nodes. The README gives two ways to start: an install script, or docker run with a data volume (README, 2026-11-14). The result is a workflow someone else on your team can open and read.
With LangChain you add a package (uv add langchain in its quickstart) and write Python. You get a standard interface for models, embeddings and vector stores, and you decide how the agent loop, storage, scheduling and front end fit together. The README says the framework helps you “chain together interoperable components and third-party integrations”.
The two are not enemies. The n8n docs say its LangChain nodes are built on LangChain’s JavaScript framework, and that each node lets you choose your own agent, LLM and memory. The same page adds that n8n’s chain nodes do not support memory, so a workflow that must remember earlier messages should use an agent node instead. A page in the n8n docs also explains how to trace a self-hosted n8n instance with LangSmith, LangChain’s monitoring product.
When should you choose n8n?
Choose n8n if these describe your project:
- The work is event-driven: a webhook, a schedule or a new row starts a fixed sequence of steps.
- You need connectors more than you need custom agent logic. The README counts 1500+ integrations.
- People who do not write Python need to read and change the flow.
- You want the option of a hosted service. The README links a cloud login next to the self-hosting instructions.
Read the license before you ship it inside a product. The n8n LICENSE file says you may use or modify the software “only for your own internal business purposes or for non-commercial or personal use”, and may distribute it only free of charge for non-commercial purposes. Files with .ee. in their name are not under that license and need an n8n Enterprise License. That suits internal automation. If you plan to resell it, ask n8n about your case. We are quoting a license, not giving legal advice.
When should you choose LangChain?
Choose LangChain if these describe your project:
- You are building an LLM application and the agent is a part of your own code.
- You want to swap models without rewriting the app. The README lists model interoperability as a reason to use it.
- Your team is comfortable in Python or TypeScript and wants version control and tests around every step.
- You expect to grow into more control. The README sends you to LangGraph for agent orchestration and to Deep Agents for planning, subagents and file system use. Our LangChain vs LangGraph comparison covers that step.
Expect to build the surrounding parts yourself: where the agent runs, how it stores memory, how a person approves a risky step. LangChain’s README points to LangSmith and LangSmith Deployment for debugging and hosting, so those parts come from a second product or from your own code.
Can you use n8n and LangChain together?
Yes. n8n can handle the triggers and the 1500+ connectors, and a LangChain-based agent node can handle the reasoning step in the middle. You can connect any other n8n node to a LangChain node, according to the n8n docs. If you need logic that the nodes do not offer, n8n’s README says you can combine the canvas with JavaScript, Python and npm packages.
The cost is two systems to learn and two sets of versions to keep current.
Where does POLYROB fit between n8n and LangChain?
POLYROB is neither a canvas nor a library. It is the agent. You install it, describe a goal or a schedule in plain language, and it plans the steps, uses tools and reports back, in a terminal, a web console, a REST API or a chat app ([email protected]). It is MIT licensed ([email protected]).
curl -fsSL https://polyrob.dev/install.sh | bash
polyrob doctorA recurring job is one line, from docs/guide/[email protected]:
/job new "every day 09:00" Summarise the inbox and post the three items that need meWhat you get without building it, with the file behind each point:
- No agent framework underneath. The dependency list in
[email protected]names neither LangChain nor LangGraph; the agent loop and model layer are native code ([email protected]). - Goals and scheduled jobs that survive a restart, so the agent can keep working without a webhook to start it (
docs/guide/[email protected]). - A cap on every autonomous run: 150 steps (
AUTONOMOUS_MAX_STEPS) and $2.0 (AUTONOMOUS_RUN_BUDGET_USD) by default, set indocs/[email protected]. Autonomous loops stay off until you runpolyrob autonomy on(docs/[email protected]). - An MCP client, so it can call tools from any MCP server (
tools/mcp/@v1.7.9). The MCP client guide shows the setup. - Any OpenAI-compatible endpoint, such as Ollama, through a providers file (
docs/[email protected]). See running an LLM locally.
Pick it if the job is “keep working on this and ask me before high-impact steps” and you would rather configure an agent than draw or code one. The self-hosted AI agent guide walks through a full install.
Where does POLYROB lose to n8n and LangChain?
Plainly:
- Integrations. n8n lists 1500+. POLYROB ships tools for the web, files, code, a shell, git and GitHub, mail and MCP, and seven first-party packs (
[email protected],docs/[email protected]). Anything else comes through MCP or a skill you write. - No canvas. The console has five destinations, Chat, Inbox, Work, Money and Agent, and none of them is a node editor (
docs/guide/[email protected]). - Not a component library. If you need to embed one retrieval step in your own code and choose every model and vector store, LangChain is the right tool.
- Community size. Both n8n and LangChain run community forums, and LangChain also offers free courses. POLYROB is the newer project with a smaller community (
docs/[email protected]). - No migration tool. The migration guides cover Hermes and OpenClaw by hand, and none covers n8n or LangChain (
docs/guide/migration/). Moving a workflow means rebuilding it. - No hosted version. The README says there is none.
How do you decide?
| If you need | Look at |
|---|---|
| A visual workflow that non-developers can edit | n8n |
| Fixed steps started by a webhook or schedule, with 1500+ connectors | n8n |
| An LLM application in your own Python or TypeScript code | LangChain |
| Fine control over a stateful agent | LangChain with LangGraph |
| Both triggers and custom agent logic | n8n with LangChain nodes |
| A self-hosted agent that is already built and works toward goals | POLYROB |
If neither fits, see our lists of n8n alternatives and LangChain alternatives.
Frequently asked questions
Is n8n better than LangChain?
They solve different problems, so neither is better across the board. n8n’s README describes a platform for AI agents and workflow automation, and LangChain’s describes a framework for building agents and LLM-powered applications. Compare them on the shape of the job: a visual workflow points to n8n, an application in code points to LangChain.
Can I use n8n with Python?
Yes. The n8n README says you can combine the visual canvas with JavaScript, Python and npm packages. n8n itself runs on Node.js, so Python is an option inside code steps, not the language of the platform.
Is n8n built on LangChain?
Not as a whole. The n8n docs say its LangChain nodes use LangChain’s JavaScript framework. The rest of n8n, including triggers, integrations and the editor, is its own platform.
Who are the main competitors of n8n?
Activepieces, Windmill, Node-RED, Dify, Langflow and Sim are covered with README quotes and license notes in our n8n alternatives page, and POLYROB is on that list as the one that is an agent, not a canvas.
Is n8n old now?
We do not judge age. On 2026-11-14 the n8n README titles the project “The Platform for AI Agents and Workflow Automation”, which shows it is positioned for agent work today. We did not measure usage.
Sources
Fetched 2026-11-14: the n8n README, the n8n LICENSE file, the n8n docs page LangChain in n8n and the LangChain README. POLYROB facts are from the public repository at tag v1.7.9. Projects change quickly: check each link before you decide.
To try an agent that is already built, read how to install POLYROB.
POLYROB is an open-source AI agent you run and own. Install it or read the docs.