AutoGen vs n8n
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | AutoGen | n8n |
|---|---|---|
| Pricing | Free | Freemium |
| User Interface | Code-first, with AutoGen Studio UI | Visual drag-and-drop canvas |
| Integrations | LLM-centric (OpenAI, Azure, Hugging Face, etc.) | 500+ pre-built (Slack, GSheets, Salesforce, etc.) |
| Deployment | Self-host, MIT license | Self-host (Docker) or cloud |
| Best For | Developers/researchers building multi-agent systems | IT/SecOps/DevOps automation |
| Key Differentiator | Agent conversation orchestration | Code-level control + visual workflow |
If you're automating operational workflows and need deep integration with business apps plus visual observability, go with n8n. If you're a developer or researcher building complex multi-agent AI collaborations with custom orchestration, AutoGen is your tool. For most enterprise automation scenarios, n8n wins for breadth and governance; for research/prototyping, AutoGen offers unmatched flexibility in agent design.
Feature-by-feature
n8n shines with a visual workflow builder where you can drag-and-drop nodes, insert JavaScript or Python anywhere, and tap into 500+ integrations covering Slack, Salesforce, GitHub, and more. It also gives you AI agent building with multi-agent and RAG, plus MCP support to hook into legacy systems. Crucially, n8n adds enterprise governance: human-in-the-loop approvals, RBAC, SSO/SAML/LDAP, encrypted secrets, and audit logs that stream to SIEM. Every step of an agent's reasoning is traceable on the canvas, and you can re-run single steps or replay mock data for debugging. AutoGen, by contrast, is a code-centric, MIT-licensed framework from Microsoft. It lets you define agents with distinct roles, tools, and LLM backends (OpenAI, Azure, Hugging Face, etc.) and orchestrate conversation patterns: sequential, group chat, or nested. It supports human-in-the-loop and has an AutoGen Studio for visual prototyping, plus code execution sandboxing via Docker. But its integrations are mainly LLM/API-based, not a plugin ecosystem like n8n's. AutoGen excels at multi-agent collaboration and simulations, whereas n8n excels at connecting to business tools and providing operational control. n8n's Git-based version control and workflow diffs are a boon for teams, while AutoGen's distributed agents via gRPC target scalable systems. In production, n8n's execution-based pricing and audit trails give it an edge for regulated industries, but AutoGen's open license means you can embed it anywhere for free.
Pricing compared
n8n operates on a freemium model: you can self-host the community edition (free) or pay for n8n Cloud, which uses execution-based pricing (not per step). That means you pay for what you run, which can scale predictably with volume, but high-volume flows may hit caps on lower tiers. AutoGen is fully free—MIT licensed—so you pay zero licensing fees, but you'll need to handle your own hosting (Docker required for code execution sandboxing) and LLM API costs. For teams that need managed infrastructure and support, n8n Cloud's cost is justified by zero-maintenance and added enterprise features like SSO and audit logs. For developers comfortable with self-hosting, AutoGen's free pricing is attractive, but you'll invest more time in setup and运维. Consider your total cost: n8n's execution pricing might be predictable if you have steady flows; AutoGen's hidden cost is infrastructure and expertise.
Who should pick which
- IT Operations ManagerPick: n8n
You need to automate onboarding, incident response, and connect to tools like Slack, Jira, and Okta. n8n's visual builder and 500+ integrations make it fast to implement, with human-in-the-loop approvals for safety.
- AI ResearcherPick: AutoGen
You're experimenting with multi-agent collaboration, need flexible role definitions, and want to customize conversation patterns. AutoGen's MIT license and code-first approach let you iterate freely.
- Security AnalystPick: n8n
You need to enrich threat intelligence and automate responses with SOAR-like workflows. n8n's audit logs, RBAC, and SIEM integration ensure compliance and traceability.
- Developer Building AI AgentsPick: AutoGen
You want programmatic control over agent orchestration, integrating with LLMs like Claude or Mistral. AutoGen's modular design and distributed support fit your stack.
- DevOps EngineerPick: n8n
You need to convert natural language into API calls and automate CI/CD pipelines. n8n's code-level control, Git versioning, and 500+ integrations beat AutoGen's narrow focus.
Frequently Asked Questions
AutoGen vs n8n: which should you choose?
If you're automating operational workflows and need deep integration with business apps plus visual observability, go with n8n. If you're a developer or researcher building complex multi-agent AI collaborations with custom orchestration, AutoGen is your tool. For most enterprise automation scenarios, n8n wins for breadth and governance; for research/prototyping, AutoGen offers unmatched flexibility in agent design.
Can AutoGen be used as a no-code tool?
No, the primary interface is code. AutoGen Studio provides visual prototyping, but it's for developers, not non-technical users.
Does n8n support MCP (Model Context Protocol)?
Yes, n8n includes MCP support, enabling connections to legacy systems that speak MCP.
What does 'execution-based pricing' mean for n8n?
You pay per workflow execution, not per step. That can be cost-effective for simple flows but may add up for high-volume operations.
Is AutoGen production-ready?
It's open-source and used in research, but production deployment requires effort. Official documentation and support are limited compared to commercial tools.
Which tool is better for a solo founder automating a SaaS?
If you need connected to many business apps quickly, n8n's integrations win. If you're building a novel AI product with custom agent logic, AutoGen offers flexibility.
Can I self-host both?
Yes. n8n is self-hostable via Docker, and AutoGen is open-source under MIT, so you can run it on your infrastructure.
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Last reviewed: August 14, 2026