supabase-data-fabric

amit-sw's avatarfrom amit-sw

Use when Codex needs to query Supabase Postgres, manage auth, or trigger Edge Functions via the Supabase MCP server.

⭐0stars🔀0forks📁View on GitHub🕐Updated Dec 24, 2025⬇️1downloads
[Databases and Warehouses]

When & Why to Use This Skill

This Claude skill enables AI agents to seamlessly interact with Supabase infrastructure, providing a robust interface for executing PostgreSQL queries, managing user authentication, and triggering Edge Functions. It streamlines backend management and data operations by offering a structured, repeatable workflow for database administration and automation through the Model Context Protocol (MCP).

Use Cases

  • Executing and verifying complex SQL queries within Supabase Postgres databases to perform data analysis or updates.
  • Managing user authentication flows and row-level security (RLS) policies to ensure secure application access.
  • Triggering and orchestrating Supabase Edge Functions to automate backend logic and server-side processes.
  • Automating database schema migrations and documentation updates with built-in safety checks and verification steps.
  • Performing dry-run database operations using transactions to prevent accidental data loss during development.
namesupabase-data-fabric
descriptionUse when Codex needs to query Supabase Postgres, manage auth, or trigger Edge Functions via the Supabase MCP server.

Supabase Data Fabric

Purpose

Provide a repeatable workflow for reading/writing Supabase data and invoking project automation endpoints through the hosted server configured in servers/supabase.

Setup Checklist

  1. Export SUPABASE_PROJECT_REF and SUPABASE_ACCESS_TOKEN (service role or personal access token).
  2. Confirm row-level security policies allow the automation key to perform the planned operations.
  3. Sync table schemas into docs/supabase/schema.md whenever the database changes (manual step).

Environment Loading

If SUPABASE_PROJECT_REF or SUPABASE_ACCESS_TOKEN are not present, source load_env.sh from the repository root before invoking MCP tools.

Workflow

  1. Clarify – define the exact SQL or auth change needed and the safety checks (e.g., limit clause, expected row count).
  2. Prepare – if making schema changes, draft the SQL inside packages/migrations/ and have reviewers sign off before execution.
  3. Execute – call the MCP query, functionCall, or auth tools. Always pass an explicit timeoutSeconds.
  4. Verify – re-run a read-only query or health check to confirm the change took effect.

Notes

  • Avoid destructive statements without a backup; prefer temporary tables or BEGIN; ...; ROLLBACK dry runs first.
  • Document every data change in pull requests or docs/changelog.md for auditability.
  • Rotate service-role or access tokens quarterly and update SUPABASE_ACCESS_TOKEN in the deployment pipeline.