I have been building Filament Studio as a dynamic data model manager for Filament v5 and Laravel 12. The original value prop was runtime-defined collections and fields on top of an EAV model, so you can build flexible admin/data systems without creating a new migration for every content type. That part worked. But while working on the project, I kept coming back to a different question: If this data layer is dynamic, how should an AI agent interact with it? My answer in v1.3.0 was to add the MCP foundation instead of hacking together one-off AI endpoints. So this release makes Filament Studio usable as an AI-facing layer, not just an admin-facing one. v1.3.0 MCP server foundation under src/Mcp/ HTTP/SSE transport mounted at /ai/studio stdio transport via php artisan mcp:start studio Reuse of StudioApiKey for MCP auth New management scope namespace for MCP operations Capability discovery resources like: studio://info studio://field-types studio://panel-types studio://operators 12 schema-management MCP tools for collections and fields Confirm-token flow for destructive operations Canonical serializer + exception handling for tool responses Tenant-aware behavior aligned with the rest of Studio A lot of AI integration work feels shallow to me. Either there is a chat UI bolted on top, or there is an agent wired straight into places it probably should not be touching. For a system like Filament Studio, neither approach feels right. If the schema is dynamic, the agent needs a real contract: discover what exists inspect schema safely mutate collections and fields through structured tools handle destructive actions with explicit confirmation tokens work through auth scopes instead of bypassing application boundaries That is the part I wanted to build first. Before this release, Filament Studio was mainly a human-operated system. After this release, it is starting to become an agent-addressable one. That is a much more interesting direction than sprinkling AI on top of the UI. I want the data model, schema rules, and operational boundaries of a Laravel app to be available to agents in a structured way. v1.3.0 is my first serious pass at that. This is not the final AI story for the project. It is the foundation. I started with schema management because if that layer is weak, everything above it becomes fragile. So I would rather get the contract right first, then expand the workflows on top of it. If you are building with Filament and thinking about AI agents beyond demo-level features, this is the direction I am building toward. Follow the project if you want to see where the MCP roadmap goes next. Feedback I would like GitHub: https://github.com/flexpik/filament-studio https://packagist.org/packages/flexpik/filament-studio