"Supabase" matching MCP servers:

MCP server that lets AI coding agents (Claude Code, Cursor, Cline) audit Supabase projects for security misconfigurations AND apply the fixes — without leaving the agent. Tools: audit_project, list_findings, preview_fix (BEGIN/ROLLBACK safety), apply_fix (with confirmation), apply_all_fixes (transactional bulk). Closes the audit-fix loop entirely in the agent — other Supabase scanners only report.

An MCP server that provides deep schema introspection for Supabase/Postgres, exposing tables, columns, views, enums, RLS policies, functions, and more.

Enables auditing a Supabase project's security beyond the dashboard's Security Advisor, checking anonymous access, RLS policies, and cross-tenant data leaks via read-only probes and a two-account test.

Enables LLMs to interact with Supabase services including Database, Auth, Storage, and Edge Functions through the Model Context Protocol. It provides tools for CRUD operations, user management, file storage, and invoking functions.

Enables CRUD operations on Supabase structured data through PostgREST tools without exposing arbitrary SQL. Access can be constrained to specific tables via an allowed-tables setting.

MCP server for Supabase database and storage operations, enabling querying, inserting, updating, deleting rows, schema introspection, and file storage management.

A Model Context Protocol (MCP) server that provides programmatic access to the Supabase Management API. This server allows AI models and other clients to manage Supabase projects and organizations through a standardized interface.

Enables Claude to fully manage self-hosted Supabase instances, covering authentication, database, storage, edge functions, and more.

Enables creating storage buckets and uploading media files to Supabase Storage through natural language, with no delete or overwrite capabilities.

Real TypeScript MCP server for connecting Zynx agents to Supabase through safe, allowlisted tools.

A TypeScript-based MCP server for handling a simple notes system with NextJS that supports creating and summarizing text notes using MCP concepts.

Enables comprehensive management of self-hosted Supabase instances on Coolify, including database migrations, edge functions deployment, storage management, auth configuration, and full application lifecycle control through AI agents.

MCP server for Supabase instances running on Aliyun RDS, enabling AI assistants to interact with your Supabase instance hosted on Aliyun cloud infrastructure.

Enables MCP clients to safely inspect and query an explicitly allowlisted subset of a Postgres database through four read-only tools: a readiness check, table listing, column description, and typed row selection with filters, ordering, and paging. It runs over stdio for local clients or Streamable HTTP for separately managed ones, with bound parameters, bounded reads, and read-only transactions.

Read-only MCP server providing Wealthi's AI Coach with scoped access to student progress data from Firestore and Supabase, enabling AI to retrieve student profiles, progress, assessment results, and learning signals without direct database credentials.

Query PostgreSQL and inspect schemas over MCP. Connects to local, Docker, RDS, Neon, Supabase, or a database behind an SSH bastion.

One MCP server holding a live session with every client's account at once, so one agent can read across a dozen businesses and write inside only the one you name. It forwards each provider's own MCP tools (Cloudflare, Vercel, Resend, Supabase, Linear, Notion, Sentry, Netlify and more) with that client's credentials, and adds deterministic DNS and email checks that never call a model.

Gives AI assistants read access to SDLC project artifacts stored in Supabase, enabling natural language queries about projects, artifacts, screens, and tech stacks, with optional IT cost estimation via Vertex AI Gemini.

Enables AI coding assistants to scan projects for security issues such as leaked API keys, missing Supabase RLS, open Firebase rules, unauthenticated routes, and hallucinated packages, then fix and verify the results.

Enables AI agents to participate in meetings by pulling pending requests, reading context, and submitting answers through a Supabase-based MCP server.