"Supabase (open source Firebase alternative)" matching MCP servers:

Enables AI agents to interact with Firebase services including Authentication, Firestore Database, and Cloud Storage through a standardized MCP protocol.

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.

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.

A local policy wrapper for Supabase MCP that secures access tokens and enforces strict execution models, including project allowlists and write-access restrictions. It provides a safety layer to prevent AI agents from accidentally executing migrations or writing SQL against production environments.

An MCP server that enables interaction with the Firebase App Check API, allowing users to verify and manage the authenticity of requests to Firebase backend services through natural language.

Enables AI agents to safely interact with Supabase through read-only and gated-write tools, with bounded queries, allowlists, and explicit project targeting.

Deterministic agentic data firewall that secures, monitors, and controls AI agent interactions with data and software via MCP, preventing data leaks.

Enables AI agents to inspect, check, and audit signed offline spending authorizations, and to issue hash-chained receipts for each action taken against them. Enforces per-transaction, total, expiry, merchant, and human-approval constraints, returning allow, needs_human, or deny with the specific failing constraint.

Turns an OpenAPI specification into a broker-published slot of curated, LLM-ready tools that a human operator reviews, tests, and approves before anything goes live. The resulting tools are declarative and run under the broker's authorization, audit, execution limits, and secret handling.

Provides OAuth-protected remote access to an existing Open Brain, forwarding approved tool calls from Gemini Spark and Perplexity web clients without altering the upstream system.

Experimental read-only MCP for Supabase application data: memory_search, memory_get and memory_list_recent under user-bound PostgreSQL RLS. Setup and demo: https://github.com/jryski/Supabase_user_MCP/blob/main/docs/GETTING_STARTED.md . Public preview is POSIX-only and synthetic-only; native Windows, hosted OAuth, one-click installation and writes are not available.

Exposes your application's resources and tools as an MCP server using Supabase Auth, Postgres, and Row Level Security, allowing authorized users to connect via compatible MCP clients.

ZeroTrusted ai PII Detection

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.

Enables AI agents to vet npm and PyPI packages before installation, reporting typosquats, vulnerabilities in the selected version, publisher changes, and names that don't exist or were published within the last 30 days. It also exposes DNS, WHOIS, email, JWT and file/image utilities as tools over Streamable HTTP, with no signup or API key required.

Enables safe, read-only SQL exploration and debugging on Supabase Edge Functions, respecting user JWTs. It inspects schemas, explains query plans, proposes RLS policies, and runs guarded queries without destructive operations.

AI-powered security scanning MCP server that exposes 25+ professional tools, enabling penetration testing and security assessments through natural language interaction with AI agents like Claude Desktop.

Enables LLM clients to safely inspect database schemas and run only approved read-only queries and stored procedures, with auditing.

Enables MCP-compatible AI coding agents to retrieve shared skills, project architecture maps, vault secret statuses, handoff checkpoints, external MCP definitions, and code audit results on demand across multiple IDEs. It reduces context tokens and supports secure, cross-agent task continuity.

Enables auditing an AI agent's guardrails by providing adversarial test prompts and scoring responses against known refusal/guardrail patterns.