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Step-by-Step Tutorial: Connecting Supabase to LLMs with MCP

3 min read

Introduction

Connecting Supabase to large language models (LLMs) via the Model Context Protocol (MCP) unlocks powerful, structured access to databases and external APIs directly within AI-driven workflows. By also integrating JuheAPI's MCP-ready services, developers can expand their LLM toolset with rich data sources.

Prerequisites

Before starting, ensure you have:

  • A Supabase account and project
  • An LLM environment ready (such as OpenAI API or local models)
  • Basic knowledge of MCP protocols
  • API keys from JuheAPI

Step 1: Understand MCP Protocol

MCP acts as a bridge connecting LLMs to external services.

What MCP Does

  • Handles API calls securely
  • Maps AI intent into structured requests

Supported Services

  • Supabase for database queries
  • JuheAPI for public data APIs

Step 2: Install MCP Client/Server

You’ll need both MCP servers configured for Supabase and JuheAPI.

Server Setup for Supabase

  1. Download MCP server package.
  2. Configure with Supabase API credentials.

Add JuheAPI Server

JuheAPI provides ready-to-use MCP endpoints. Follow the official setup guide at https://www.juheapi.com/mcp-servers.

# Example MCP installation
npm install mcp-server
npm install mcp-client

Step 3: Configure MCP to Connect Supabase

Create Supabase Project

  • Define required tables and schema.
  • Enable API access.

Update MCP Config

{
  "servers": [
    {
      "name": "supabase",
      "url": "https://your-supabase-url",
      "apiKey": "SUPABASE_KEY"
    }
  ]
}

Step 4: Integrate LLM with MCP

Choose LLM Framework

Options include:

  • OpenAI API wrappers
  • Local model with Python (using transformers)

Bind MCP Endpoints

from mcp_client import MCPClient
client = MCPClient()
response = client.query("supabase", {"query": "SELECT * FROM users"})
print(response)

Step 5: Extend with JuheAPI MCP-ready Services

JuheAPI offers datasets accessible via MCP.

Examples

  • Weather API: real-time conditions
  • Finance API: stock and currency data

Step 6: Test End-to-End Flow

Query Supabase via LLM

You might prompt: "Show all active users" and the LLM issues SQL through MCP to Supabase.

Query JuheAPI via LLM

Prompt: "Weather in Shanghai" triggers MCP to JuheAPI weather server.

Combined Queries

Prompt: "List customers with sunny weather in their city" uses both services.

Best Practices

  • Protect API keys in environment variables.
  • Set query limits to avoid costs.
  • Use caching strategies to speed up response.

Common Pitfalls

  • MCP config mismatches – double-check server URLs.
  • Unhandled LLM outputs – ensure robust parsing.

Conclusion

Connecting Supabase to LLMs via MCP, enhanced with JuheAPI's services, empowers developers with a versatile toolkit for building smarter apps. Start small, test thoroughly, and then scale as needed.

References