To drive adoption, lower the learning curve, and compete in the AI-first automation wave, n8n should expose structured metadata for all nodes—functions, input/output logic, usage context, and parameter rules—via a live, queryable format consumable by AI tools like OpenAI and Google Gemini.
Why?
- Today’s AI models are increasingly used to build workflows via natural language. But without current node data, GPT guesses or gives outdated instructions.
- If n8n made its node library AI-readable (e.g. via a plugin manifest or structured public API), tools like ChatGPT could reliably generate working, up-to-date workflows for new users.
- This would massively reduce friction for onboarding, support, and scale.
Zapier and Make are already heading this direction. n8n has a chance to lead in the open-source space—especially for developers looking to blend flexibility with AI-guided building.
Even if you can’t directly partner with OpenAI yet, exposing your node library in a structured, machine-readable format would let the community build that bridge ourselves.