Schemaflow Mcp Server

Real-time PostgreSQL & Supabase schema access for AI-IDEs via Model Context Protocol (MCP)

SchemaFlow MCP Server provides your AI-IDE with live access to PostgreSQL and Supabase database schemas through the Model Context Protocol. Get real-time schema context for smarter code generation in tools like Cursor, Windsurf, and VS Code + Cline.

🚀 Quick Start

Visit SchemaFlow →

1. Get Your MCP Token

Visit SchemaFlow Dashboard to:

Connect your PostgreSQL or Supabase database
Load and cache your schema
Generate an MCP token

2. Configure Your AI-IDE

For Cursor IDE:

Open Cursor Settings
Go to Features → MCP
Click “Add New MCP Server”
Use this configuration:

{
  "name": "schemaflow",
  "type": "sse",
  "url": "https://api.schemaflow.dev/mcp/?token=your-token-here"
}

For Windsurf IDE:

Add to your MCP configuration:

{
  "mcpServers": {
    "schemaflow": {
      "type": "sse",
      "url": "https://api.schemaflow.dev/mcp/?token=your-token-here"
    }
  }
}

For VS Code + Cline:

Configure in Cline’s MCP settings:

{
  "mcpServers": {
    "schemaflow": {
      "type": "sse", 
      "url": "https://api.schemaflow.dev/mcp/?token=your-token-here"
    }
  }
}

🛠️ Available MCP Tools

`get_schema`

Retrieves complete database schema information including tables, columns, relationships, functions, triggers, enums, and indexes from PostgreSQL or Supabase databases.

Parameters:

query_type (optional): Filter specific information (tables, columns, relationships, functions, triggers, enums, indexes, all)

Example AI queries:

“Show me my database schema”
“What tables do I have?”
“Show me all relationships”
“List database functions”

`analyze_database`

Performs comprehensive database analysis including performance insights, security assessment, and structural recommendations for PostgreSQL and Supabase databases.

Example AI queries:

“Analyze my database performance”
“Check database security”
“Review database structure”
“Give me a database overview”

`check_schema_alignment`

Validates your PostgreSQL or Supabase schema against best practices and identifies potential issues with actionable recommendations.

Example AI queries:

“Check schema alignment”
“Validate my database”
“Any schema issues?”
“Check naming conventions”

🔧 How It Works

Schema Caching: When you load your schema in SchemaFlow dashboard, it’s automatically cached for MCP access
Secure Connection: Your AI-IDE connects using MCP with secure token authentication
Real-time Access: Your AI assistant can query schema data in real-time for better code generation

🔒 Security

Schema metadata only - No actual data is accessed or stored
Token-based authentication - Each user has a unique, revokable token
Encrypted connections - All MCP communication is encrypted
User-specific access - Tokens only access your own cached schema data

📚 Complete Documentation

For detailed setup instructions, troubleshooting, and advanced configuration, visit:

Complete MCP Integration Guide

🌐 SchemaFlow Platform

This MCP server is part of the larger SchemaFlow platform which also provides:

Interactive Schema Visualization - Explore your PostgreSQL/Supabase database structure through intuitive diagrams
Multi-Format Export - Export schemas in JSON, Markdown, SQL, and Mermaid formats
Schema Browser - Navigate through tables, relationships, and database components
Performance Analysis - Get insights into your database structure and optimization opportunities
Supabase Integration - Native support for Supabase projects with direct connection

Visit SchemaFlow →