Overview
SchemaFlow MCP Server provides your AI-IDE with live access to PostgreSQL and Supabase database schemas through the Model Context Protocol. It enables real-time schema context to support smarter code generation in popular AI IDEs such as Cursor, Windsurf, and VS Code plus Cline. When you load and cache your schema from the SchemaFlow dashboard, MCP access is streamlined with secure token authentication. All MCP communications are encrypted and token-based, with user-specific access so tokens only grant access to your own cached schema data. The server exposes three MCP tools: get_schema to retrieve complete schema information (tables, columns, relationships, functions, triggers, enums, indexes) with optional query_type filters; analyze_database for performance insights, security assessment, and structural recommendations; and check_schema_alignment to validate your schema against best practices and surface actionable issues. This MCP server is part of the SchemaFlow platform, which also offers interactive schema visualization, multi-format exports, and native Supabase integration. It emphasizes metadata security and provides a complete MCP integration guide.
Features
get_schema
Retrieves complete database schema information including tables, columns, relationships, functions, triggers, enums, and indexes from PostgreSQL or Supabase databases.
analyze_database
Performs comprehensive database analysis including performance insights, security assessment, and structural recommendations for PostgreSQL and Supabase databases.
check_schema_alignment
Validates your PostgreSQL or Supabase schema against best practices and identifies potential issues with actionable recommendations.
Schema caching
Schema data loaded via the SchemaFlow dashboard is automatically cached for MCP access.
Real-time access
Provides real-time access to schema data for AI assistants to generate code with up-to-date context.
Secure MCP connections
Uses token-based authentication with encrypted connections and user-specific access to MCP data.
Who Is This For?
- AI IDEs:Provide live schema context to AI-assisted coding workflows in MCP-enabled IDEs.
- Database developers:Access real-time database schemas to explore structures and relationships during development.
- Data engineers:Utilize schema insights for design validation and optimization in data pipelines.
