LangGraph, by LangChain, and n8n
A coding agent is not a business workflow with a model in it
LangGraph and n8n are excellent at what they are for. LangGraph is a low-level orchestration framework for building stateful agents in Python; n8n is a visual automation platform with over fifteen hundred integrations and its own AI agent nodes. Both come up when a team searches for "agent workflow engine", and both can be bent toward coding work. The question is whether you want to build a coding agent or govern one.
With either, the agent is yours to construct: the graph, the tools, the prompts, the loop. With CodyCody, the agent is Claude Code or Codex, unchanged, and the engine sits behind it deciding what happens next. That difference is the whole comparison. The rest is consequences.
What LangGraph, by LangChain, and n8n is
- LangGraph: "a low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful agents". Graphs are defined in Python — nodes, edges, compile — and can mix "deterministic, hand-coded steps with LLM-driven agentic steps in the same graph". Human-in-the-loop via interrupts; persistence so agents resume after failure; deployment through LangSmith.
- n8n: a "fair-code platform to build and deploy AI agents and workflows" combining a visual canvas with custom code, self-hosted or cloud, with "1500+ integrations" and explicit support for human approvals. Licensed under its Sustainable Use License, with an Enterprise license for enterprise features.
- Both are positioned for agents and automation in general, not for coding agents in particular.
What CodyCody is
- An engine for one kind of agent — the one editing code in your repository — with the discipline that kind needs: step order the agent cannot reorder, shell steps under an exit-code contract with output hashed to file, gates before irreversible changes.
- Nothing to build. The workflow is designed visually or taken from a package; the agent is the one you already run; the integration is one MCP entry.
Side by side
The same questions, both answers
| LangGraph, by LangChain, and n8n | CodyCody | |
|---|---|---|
| What you build | The agent itself (LangGraph) or the automation (n8n) | Nothing — you configure the agent you have |
| Where the model runs | In your graph or node, via the provider you wire | In your coding agent, as already configured |
| Workflow definition | Python code (LangGraph); visual canvas + code (n8n) | Visual designer; packages ready to run |
| Human in the loop | Interrupts (LangGraph); approval nodes (n8n) | Approval gates that halt the run |
| Verifying tool output | Whatever your code checks | Engine-fixed command, exit-code contract, output hashed to file |
| Coding-specific | No — general purpose | Yes — built around an agent in a repository |
| Self-hosting | LangGraph: library, deploy via LangSmith or yourself. n8n: self-hostable | Self-hosted binary; offline license; air-gapped on Enterprise |
| License | LangGraph: open source. n8n: Sustainable Use License | Commercial; Starter free |
Facts about LangGraph, by LangChain, and n8n are taken from its own documentation, checked on 2026-08-23. “Not documented” means we could not verify it, not that it is absent.
Choose LangGraph, by LangChain, and n8n if
- You are building an agent product of your own — a custom loop, custom tools, your own UI — and want a framework under it. That is LangGraph.
- The workflow is business automation: tickets, CRMs, mail, documents, with a model in the middle. That is n8n, and it has the integrations.
- You need to compose many systems, and code changes are one step among many.
Choose CodyCody if
- The agent is Claude Code or Codex and you want to keep it that way — no graph to write, no runtime to host for the agent itself.
- The work is in a repository and the risk is an agent that skips the test, edits outside scope, or reports success it did not earn.
- You want review and security workflows that run the same way for every developer, from a package, on day one.
Questions
Asked when comparing
- Could I reproduce CodyCody in LangGraph?
- A deterministic graph with interrupts is a good part of it, and LangGraph would be a fine choice for building that. What you would be building is an agent; CodyCody's bet is that you want to govern the one you already have, and that the verification of shell output is the hard part.
- Can n8n trigger a CodyCody workflow?
- The engine exposes its tools over MCP and its web interface over HTTP, so an n8n flow can start a run as a step — for example, a security review after a release. The review itself then runs on rails.
- Is CodyCody open source?
- No. It is a commercial, self-hosted product with a free Starter tier. If open source is a requirement, LangGraph is open source and n8n is source-available under its own license.
Sources
Where the facts come from
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