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Schemaflow   Database Schema Extractor

Schemaflow Database Schema Extractor

Remote
github.com/CryptoRadiDatabases10Updated 73w ago
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About Schemaflow Database Schema Extractor

SchemaFlow provides AI IDEs with access to live PostgreSQL and Supabase schema metadata. Its tools retrieve schemas, analyze databases, and check schemas against best practices, without accessing database contents.

Key features

  1. 01Retrieve tables, columns, and relationships
  2. 02Inspect functions, triggers, enums, and indexes
  3. 03Analyze performance and security
  4. 04Check schema alignment and recommendations
  5. 05Token-authenticated access to cached schemas

Use cases

  1. 01Give an AI IDE current schema context for code generation
  2. 02Review database structure and performance
  3. 03Validate a schema and identify potential issues

MCP support

The MCP server exposes schema retrieval, database analysis, and schema-alignment tools over SSE. AI IDEs connect with a user-specific token to access cached schema metadata.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://api.schemaflow.dev/mcp/?token=<YOUR_TOKEN>
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

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:
  1. Open Cursor Settings
  2. Go to Features → MCP
  3. Click "Add New MCP Server"
  4. 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

  1. Schema Caching: When you load your schema in SchemaFlow dashboard, it's automatically cached for MCP access
  2. Secure Connection: Your AI-IDE connects using MCP with secure token authentication
  3. 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 →

🆘 Support

📄 License

MIT License - see LICENSE file for details.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.