I built Cerefox, an open-source shared memory layer for AI agents, and deployed it entirely on Supabase. It uses Edge Functions and RPCs for the integration layer, with Supabase handling storage, auth, and the database.
This is my first time using Supabase and the project targets personal use, not enterprise scale. My own usage fits comfortably within the free tier, though a friend who has ingested several hundred documents is starting to bleed into the paid plan.
I built an MCP adapter as an Edge Function, which calls five primitive Edge Functions that handle embeddings server side and call Postgres RPCs. In my initial deployment, Claude / Claude Code agents connect directly to the MCP endpoint, while ChatGPT accesses the primitive Edge Functions directly via Custom GPT Actions since MCP won't work. I also have a local, python, stdio MCP server that handles embeddings and accesses the RPCs directly.
I would love feedback from experienced Supabase developers on how I am using the platform. Anything I could structure better?
Repo: https://github.com/fstamatelopoulos/cerefox
Happy to answer questions about the architecture or design decisions.
CrazyVast8570 developed an open-source shared memory layer for AI agents called Cerefox, using Supabase's Edge Functions and RPCs. The project is deployed on Supabase, utilizing storage, auth, and database features. The user seeks feedback from experienced Supabase developers on their architecture and design choices.
Very interesting!