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Workflow automation with AI

Workflow and integration platforms with AI steps or agent nodes, for wiring models into the rest of your tools.

n8n leads with 76, ahead of Activepieces (65). 2 projects ranked by score.

The ranking

Workflow automation with AI: full ranking
RankProjectAdoptionFreshnessMaintenanceEasy to runAgent-readyScore
1n8nVisual workflow automation with code steps, AI agent nodes and 1500+ integrations206.9k stars, custom license, last commit Oct 20269910092337076 out of 100
2ActivepiecesSelf-hosted workflow automation with TypeScript integrations, alternative to Zapier25k stars, custom license, last commit Oct 20262710086508565 out of 100

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Reviews

176 out of 100

n8n

Visual workflow automation with code steps, AI agent nodes and 1500+ integrations

206.9k stars, custom license, last commit Oct 2026

n8n is a fair-code workflow platform that runs as one Docker container (docker.n8n.io/n8nio/n8n, port 5678) and combines a visual canvas with JavaScript, Python and npm code nodes. AI agent and workflow nodes connect to OpenAI, Anthropic, Google or open-source models, with human-approval steps and observability, and 1500+ integrations plus 9,000+ templates cover the rest of the stack.

Strengths

  • 1500+ integrations and 9,000+ ready-made workflow templates
  • Code nodes run JavaScript or Python and can pull npm packages
  • Single container on port 5678 with one data volume
  • Switch model providers without rebuilding the workflow

Weaknesses

  • Sustainable Use License (fair-code, source-available), not an OSI license
  • Some features require a separate n8n Enterprise License
  • README states no database, RAM or CPU requirements
  • no GPU
  • Models: OpenAI, Anthropic, Google, open-source models
  • port 5678
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
265 out of 100

Activepieces

Self-hosted workflow automation with TypeScript integrations, alternative to Zapier

25k stars, custom license, last commit Oct 2026

Activepieces is a no-code workflow builder with loops, branches, auto retries, HTTP calls and npm-backed code steps, and flows are versioned. Integrations are called pieces: TypeScript npm packages, 280+ of which are exposed as MCP servers for Claude Desktop, Cursor or Windsurf. It also has AI pieces for several providers, human-in-the-loop approvals, and chat and form triggers.

Strengths

  • Pieces are open-source TypeScript npm packages with hot reloading for local development
  • 280+ pieces usable as MCP servers from Claude Desktop, Cursor or Windsurf
  • Flows are versioned and support loops, branches and auto retries
  • Built-in approval, delay, chat and form triggers for human-in-the-loop flows

Weaknesses

  • Enterprise features sit under a separate commercial license, not MIT
  • README does not state RAM, CPU or database requirements
  • Automation-first; AI agents are one feature rather than the core design
  • README claims of 200+ and 280+ pieces are inconsistent
  • no GPU
  • Docker + Compose
  • Compose runs PostgreSQL, Redis
  • Models: OpenAI
Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)

Written from each project's README and checked facts. Spot something wrong? Report it on GitHub (opens in a new tab).