supabase-community/supabase-mcp

> Connect your Supabase projects to Cursor, Claude, Windsurf, and other AI assistants.
The Model Context Protocol (MCP) standardizes how Large Language Models (LLMs) talk to external services like Supabase. It connects AI assistants directly with your Supabase project and allows them to perform tasks like managing tables, fetching config, and querying data. See the full list of tools.
Setup
1. Follow our security best practices
Before setting up the MCP server, we recommend you read our security best practices to understand the risks of connecting an LLM to your Supabase projects and how to mitigate them.
2. Configure your MCP client
To configure the Supabase MCP server on your client, visit our setup documentation. You can also generate a custom MCP URL for your project by visiting the MCP connection tab in the Supabase dashboard.
Your MCP client will automatically prompt you to log in to Supabase during setup. Be sure to choose the organization that contains the project you wish to work with.
Most MCP clients require the following information:
If you don't see your MCP client listed in our documentation, check your client's MCP documentation and copy the above MCP information into their expected format (json, yaml, etc).
CLI
If you're running Supabase locally with Supabase CLI, you can access the MCP server at http://localhost:54321/mcp. Currently, the MCP Server in CLI environments offers a limited subset of tools and no OAuth 2.1.
Self-hosted
For self-hosted Supabase, check the Enabling MCP server page. Currently, the MCP Server in self-hosted environments offers a limited subset of tools and no OAuth 2.1.
Configuration options and tools
See the Supabase MCP Server docs for the full list of available tools and configuration options.
The docs also feature an interactive URL builder to populate configuration options for you.
Usage with AI SDK's MCP Client
The @supabase/mcp-server-supabase package exports createToolSchemas() to populate input and output schemas for Vercel AI SDK's MCP client. This allows Supabase MCP tools to be treated as static tools with client-side validation and inferred TypeScript types for their inputs and outputs.
createToolSchemas() accepts similar filtering options as the MCP server's URL parameters:
- features: Restrict to specific feature groups (e.g. ['database', 'docs']). Defaults to all default feature groups.
- projectScoped: When true, omits project_id from tool input schemas and excludes account-level tools — use when connecting to a server configured with project_ref. Defaults to false.
- readOnly: When true, excludes mutating tools — use when connecting to a server configured with read_only=true. Defaults to false.
> [!NOTE]
> This server does not send structuredContent in MCP tool results. AI SDK falls back to parsing JSON from content text.
For more information, see Schema Definition and Typed Tool Outputs in the AI SDK docs.
Self-hosting the MCP endpoint
The @supabase/mcp-server-supabase package exports createSupabaseMcpHandler() to serve the tools over HTTP from your own endpoint. It accepts the same SupabaseMcpServerOptions as createSupabaseMcpServer(), most importantly platform.