Choosing between n8n and Dify feels a bit like picking between a Swiss-army knife and a laser-focused scalpel. Both are open-source, both let you build without drowning in code, but they solve very different problems. Below is a straight-talk comparison that should save you a weekend of trial-and-error.

What n8n Does Best

n8n is the go-to when you need to glue apps together, move data around, or automate the boring stuff. Think of it as Zapier you can self-host and bend to your will.

Strength	Why it matters
Visual flow builder	Drag-and-drop nodes; no YAML nightmares
400+ native integrations	Slack, Gmail, Airtable, Postgres—you name it
Custom nodes	Write a few lines of JS when the built-in ones fall short
Self-host or cloud	Keep data on your own server or let n8n handle uptime
Branching & loops	Build multi-step logic that actually scales

Typical use-cases

Auto-create Jira tickets from form submissions
Sync Shopify orders to Google Sheets every hour
Post Slack alerts when a server metric spikes

What Dify Does Best

Dify is purpose-built for AI apps. If your product needs a chatbot, semantic search, or any flavor of LLM magic, Dify wraps the heavy lifting in a friendly UI.

Strength	Why it matters
LLM-first design	One-click switch between GPT-4o, Claude, Llama-3, etc.
Prompt chaining	Stack prompts like Lego blocks; no Python glue code
Retrieval-Augmented Generation (RAG)	Upload PDFs or crawl a site, then chat with the content
Low-code UI builder	Spin up a branded chat widget in minutes
MCP (new)	Turn any workflow into a reusable MCP server—more on that below

Typical use-cases

Customer-support bot that cites your knowledge base
Internal “ask-the-docs” assistant for a 500-page PDF manual
AI co-pilot that drafts marketing copy from CRM data

The New Kid on the Block: Dify’s Bidirectional MCP

Dify quietly shipped a game-changer called bidirectional MCP (Model-Context Protocol). In plain English:

Inbound: Pull in any existing MCP server—so your Dify app can suddenly call 50+ new tools.
Outbound: Publish your own Dify workflow as an MCP server, then summon it from ChatGPT, Claude Desktop, or any MCP-ready client.

That means the workflow you built for “deep research” isn’t trapped inside Dify. You can invoke it mid-conversation in your favorite AI client, get richer answers, and never context-switch.

Quick demo recap

Grab the “Deep Research” template in Dify.
Swap in GPT-4.1, hit “Publish”, toggle “Expose as MCP”.
Copy the localhost URL.
In CherryStudio (or any MCP client) → Add Server → paste URL.
Ask the same question twice—once with vanilla search, once with your MCP server. The second answer is deeper, sourced, and structured.

Decision Matrix

If your priority is…	Pick
General business automation across many SaaS tools	n8n
Hosting automations on your own infra with full control	n8n
Building AI chatbots, assistants, or RAG apps	Dify
Experimenting with LLM chains without writing Python	Dify
Need both worlds (soon)	Dify + MCP to expose flows, or n8n to orchestrate

TL;DR

n8n = best all-around automation workhorse.
Dify = best AI app factory, now supercharged with MCP so your flows stop being lonely islands.

Ready to stop wrestling with workflows and start shipping? The team at Tenten builds custom automation stacks and AI products on both n8n and Dify—whichever fits your reality. Book a 30-minute strategy call and let’s map out the fastest path from idea to production.

n8n vs Dify: Which One Actually Fits Your Workflow?