Supabase MCP Server

The Query MCP (Supabase MCP Server) turns a Supabase database into a first‑class AI‑friendly data source. Instead of writing raw SQL or using the Supabase UI, developers can embed a powerful, safety‑aware query engine directly into their IDE or conversational AI. The server exposes the database through the Model Context Protocol, allowing tools such as Cursor, Windsurf, or Cline to issue SQL commands in a structured, typed manner while the server handles authentication, validation, and execution control.

At its core, the server solves the problem of uncontrolled database access. By exposing a controlled interface, it lets teams delegate complex data operations to AI assistants without risking accidental schema changes or data loss. The server supports both read‑only and read‑write modes, enabling fine‑grained permission management. Runtime SQL validation assigns a risk level to each query—ranging from safe reads to destructive writes—so developers can trust that only approved operations reach the database.

Key capabilities include:

• Runtime SQL validation: Every query is parsed and scored for risk, ensuring that potentially harmful statements are flagged or blocked before execution.
• Three‑tier safety system: Queries fall into safe, write, or destructive categories, with configurable thresholds that can be adjusted per project.
• Management API access: Beyond raw queries, the server exposes Supabase’s management endpoints (e.g., role creation, bucket operations) through MCP resources.
• User authentication: Built‑in support for Supabase Auth allows the server to act on behalf of specific users, maintaining proper access control.
• IDE integration: By speaking the same protocol as popular MCP clients, developers can run queries directly from their editor’s command palette or a chat pane.

In practice, teams use the server to build AI‑driven dashboards, natural‑language query assistants, or automated data pipelines. A product manager can ask the assistant to “show me last month’s revenue by region,” and the MCP server safely translates that into a parameterized SQL query, validates it, and returns the result—all without exposing raw credentials. Similarly, a data engineer can prototype schema migrations in an AI chat, letting the server simulate the changes before committing them.

What sets this MCP server apart is its complete safety stack combined with native Supabase integration. Developers can prototype, test, and deploy AI‑enhanced database interactions while retaining full control over permissions and data integrity. The result is a seamless bridge between conversational AI and production databases, enabling rapid iteration without compromising security.