Generate Modules via AI
Use the Facets Module Generation MCP server from your AI coding host to turn a module concept into a working, standards-aligned Terraform module for Facets in minutes.
Skills, installed by praxis login
The usual way to build modules with an AI agent needs no setup beyond signing in. praxis login installs the Facets skills into every AI host it detects on your machine, so an agent working in a module directory already knows the module contract, the validation steps, and how modules get published.
praxis login
raptor loginFrom there you work in your own terminal: describe the capability you want, let the agent scaffold and edit the module, and let it run raptor module validate and the publish flow. Nothing is cloned or browsed by hand, and raptor remains the only thing talking to the control plane.
Facets' Module-Generation MCP
If your AI host connects over MCP rather than reading skills from disk, you can build custom modules with the Facets Module Generation MCP server (Model Context Protocol), which an AI coding host connects to in order to scaffold and validate Facets Terraform modules.
Some key advantages of using this MCP server:
- Faster module creation with guided prompts and validations
- Standardised structure that aligns with Facets' module registry
- Supports custom logic, templating, and metadata integration.
Try it out here and start building modules tailored to your infrastructure needs.
Check out this sample video:
Building a Facets Module
This section explains how to turn a module concept into a working Facets module. You'll define the module interface using `facets.yaml`, connect it to Terraform logic, and use the Facets CLI to scaffold and validate your work.
Form UI (X-UI Tags)
Reference for the x-ui-* extension fields in facets.yaml that shape module config forms: conditional display, dynamic dropdowns, layout, and validation.