AutoGen vs n8n

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-08-15
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At a glance

DimensionAutoGenn8n
PricingFreeFreemium
User InterfaceCode-first, with AutoGen Studio UIVisual drag-and-drop canvas
IntegrationsLLM-centric (OpenAI, Azure, Hugging Face, etc.)500+ pre-built (Slack, GSheets, Salesforce, etc.)
DeploymentSelf-host, MIT licenseSelf-host (Docker) or cloud
Best ForDevelopers/researchers building multi-agent systemsIT/SecOps/DevOps automation
Key DifferentiatorAgent conversation orchestrationCode-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.

AutoGen
AutoGen

Open-source framework for building multi-agent AI workflows.

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n8n
n8n

Open-source AI workflow automation with code-level control and traceable agents

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Pricing
Free
Freemium
Plans
$0/mo
$0/mo
€20/mo (billed annually)
€50/mo (billed annually)
€667/mo (billed annually)
Contact Sales
Popularity
5.3k views
5.8k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
APIDesktopWeb
Web
Categories
🕸️ Agent Frameworks & Orchestration
🤖 Automation & Agents🕸️ Agent Frameworks & Orchestration
Features
Multi-agent conversation orchestration
Flexible agent role definition
Customizable conversation patterns (sequential, group chat, nested)
Integration with various LLMs via abstract interface
Extensible tool use
Human-in-the-loop support
Open-source (MIT license) with community contributions
AutoGen Studio visual prototyping UI
Code execution sandboxing (requires Docker)
Modular agent composition
Event-driven core for scalable systems
Distributed agents via gRPC
MCP server integration via McpWorkbench
OpenAI Assistant API integration
Visual workflow builder with drag-and-drop nodes
Insert JavaScript or Python anywhere
500+ pre-built integrations
AI agent builder with multi-agent and RAG support
MCP support for legacy systems
Human-in-the-loop approvals and guardrails
Self-host via Docker or n8n Cloud
Git-based version control with workflow diffs
SSO/SAML/LDAP, encrypted secrets, RBAC
Audit logs and log streaming to SIEM
Re-run single steps, replay or mock data
Execution-based pricing (not per step)
Native AI evaluation with real data
AI Assistant with credits (preview)
Offline model support
Integrations
OpenAI
Azure OpenAI
Hugging Face
LLaMA
Mistral
Claude
Slack
Google Sheets
Salesforce
HubSpot
Notion
GitHub
Jira
Anthropic
Microsoft Graph
IMAP
SMTP
HTTP
GraphQL
PostgreSQL

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 Manager
    Pick: 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 Researcher
    Pick: 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 Analyst
    Pick: 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 Agents
    Pick: 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 Engineer
    Pick: 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