Supabase MCP Server

The Supabase MCP Server bridges the gap between large language models and the rich ecosystem of Supabase, turning an LLM into a first‑class database client. By exposing a standardized set of tools—such as table management, configuration retrieval, and SQL execution—the server lets AI assistants perform complex data operations without developers writing custom adapters. This capability is especially valuable for teams that want to embed AI directly into their data workflows, allowing conversational agents to read from or write to a Supabase project as naturally as they would query a spreadsheet.

Key features include OAuth‑based authentication that scopes access to specific Supabase projects, ensuring that an assistant only sees the data it is permitted to. The server also supports read‑only mode, which locks down write operations by running SQL against a dedicated read‑only Postgres user. This mitigates accidental data corruption while still enabling powerful queries and analytics. Additionally, the server’s feature groups let developers enable or disable subsets of tools—such as schema management or project listing—tailoring the assistant’s capabilities to the task at hand.

Real‑world use cases span from automated data cleaning pipelines, where an AI assistant can fetch raw tables, apply transformations, and write cleaned results back to Supabase, to dynamic reporting dashboards that let users ask natural language questions and receive up‑to‑date answers pulled directly from the database. Because the MCP standardizes communication, any client that understands MCP—Cursor, Claude, Windsurf, or custom tooling—can instantly interact with Supabase without bespoke integration code.

Integration into existing AI workflows is straightforward: a client simply points to the Supabase MCP endpoint () and authenticates via OAuth. The server then presents a catalog of tools that the LLM can invoke, and the assistant’s prompt can reference those tools to perform actions like or . This declarative approach keeps the AI’s reasoning separate from execution logic, improving maintainability and security.

What sets Supabase MCP apart is its native alignment with Supabase’s permission model and the ability to run on both cloud and local environments (via when using Supabase CLI). Developers can prototype locally with a subset of tools and then seamlessly roll out to production, confident that the same MCP interface will behave consistently across environments. This consistency, combined with fine‑grained access control and read‑only safeguards, makes the Supabase MCP Server a robust foundation for building AI‑powered data applications.