Supabase MCP Server

Connect your Supabase projects to Cursor, Claude, Windsurf, and other AI assistants.

supabase-mcp-demo

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:

json

{
  "mcpServers": {
    "supabase": {
      "type": "http",
      "url": "https://mcp.supabase.com/mcp"
    }
  }
}

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.

import { createToolSchemas } from '@supabase/mcp-server-supabase';
import { createMCPClient } from '@ai-sdk/mcp';
import { streamText } from 'ai';

const mcpClient = await createMCPClient({
  transport: {
    type: 'http',
    url: 'https://mcp.supabase.com/mcp',
  },
});

const tools = await mcpClient.tools({
  schemas: createToolSchemas(),
});

const result = streamText({ model, tools, prompt: '...' });

for (const step of await result.steps) {
  for (const toolResult of step.staticToolResults) {
    if (toolResult.toolName === 'get_project_url') {
      toolResult.input;  // { project_id: string }
      toolResult.output; // { url: string }
    }
  }
}

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.

const mcpClient = await createMCPClient({
  transport: {
    type: 'http',
    url: 'https://mcp.supabase.com/mcp?project_ref=&read_only=true&features=database,docs',
  },
});

const tools = await mcpClient.tools({
  schemas: createToolSchemas({
    features: ['database', 'docs'],
    projectScoped: true,
    readOnly: true,
  }),
});

[!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.

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