Schemaflow Database Schema Extractor
RemoteAbout 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
- 01Retrieve tables, columns, and relationships
- 02Inspect functions, triggers, enums, and indexes
- 03Analyze performance and security
- 04Check schema alignment and recommendations
- 05Token-authenticated access to cached schemas
Use cases
- 01Give an AI IDE current schema context for code generation
- 02Review database structure and performance
- 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.
https://api.schemaflow.dev/mcp/?token=<YOUR_TOKEN>claude mcp add --transport sse schemaflow https://api.schemaflow.dev/mcp/?token=<YOUR_TOKEN>{"mcpServers":{"schemaflow":{"type":"sse","url":"https://api.schemaflow.dev/mcp/?token=<YOUR_TOKEN>"}}}Open in Cursor{"servers":{"schemaflow":{"type":"sse","url":"https://api.schemaflow.dev/mcp/?token=<YOUR_TOKEN>"}}}Open in VS Code{"mcpServers":{"schemaflow":{"type":"sse","url":"https://api.schemaflow.dev/mcp/?token=<YOUR_TOKEN>"}}}{"mcpServers":{"schemaflow":{"serverUrl":"https://api.schemaflow.dev/mcp/?token=<YOUR_TOKEN>"}}}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 READMESchemaFlow 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
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
🆘 Support
- Documentation: schemaflow.dev/mcp-guide
- Dashboard: schemaflow.dev/dashboard
- Issues: Create an issue in this repository
📄 License
MIT License - see LICENSE file for details.
Comments
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.