An MCP server to query any Postgres database in natural language.

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PGMCP - PostgreSQL Model Context Protocol Server

PGMCP connects AI assistants to any PostgreSQL database through natural language queries. Ask questions in plain English and get structured SQL results with automatic streaming and robust error handling.

Works with: Cursor, Claude Desktop, VS Code extensions, and any MCP-compatible client

Quick Start

Prerequisites

  • Go 1.23+
  • PostgreSQL database
  • OpenAI API key (optional, can use other compatible APIs)

Installation

# Build
go build -o pgmcp-server ./server
go build -o pgmcp-client ./client

# Set up database (optional - works with any existing PostgreSQL database)
export DATABASE_URL="postgres://user:password@localhost:5432/mydb"
psql $DATABASE_URL < schema.sql

# Run server
export OPENAI_API_KEY="your-api-key"
./pgmcp-server

# Test with client
./pgmcp-client -ask "Who is the user that places the most orders?" -format table
./pgmcp-client -ask "Show me the top 40 most reviewed items in the marketplace" -format table

Environment Variables

Required:

  • DATABASE_URL: PostgreSQL connection string

Optional:

  • OPENAI_API_KEY: OpenAI API key for SQL generation
  • OPENAI_MODEL: Model to use (default: "gpt-4o-mini")
  • HTTP_ADDR: Server address (default: ":8080")
  • HTTP_PATH: MCP endpoint path (default: "/mcp")
  • AUTH_BEARER: Bearer token for authentication
๐Ÿ‘ค User / AI Assistant
         โ”‚
         โ”‚ "Who are the top customers?"
         โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                    Any MCP Client                           โ”‚
โ”‚                                                             โ”‚
โ”‚  PGMCP CLI  โ”‚  Cursor  โ”‚  Claude Desktop  โ”‚  VS Code  โ”‚ ... โ”‚
โ”‚  JSON/CSV   โ”‚  Chat    โ”‚  AI Assistant    โ”‚  Editor   โ”‚     โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
         โ”‚
         โ”‚ Streamable HTTP / MCP Protocol
         โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                    PGMCP Server                             โ”‚
โ”‚                                                             โ”‚
โ”‚  ๐Ÿ”’ Security    ๐Ÿง  AI Engine      ๐ŸŒŠ Streaming               โ”‚
โ”‚  โ€ข Input Valid  โ€ข Schema Cache    โ€ข Auto-Pagination         โ”‚
โ”‚  โ€ข Audit Log    โ€ข OpenAI API      โ€ข Memory Management       โ”‚
โ”‚  โ€ข SQL Guard    โ€ข Error Recovery  โ€ข Connection Pool         โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
         โ”‚
         โ”‚ Read-Only SQL Queries
         โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                Your PostgreSQL Database                     โ”‚
โ”‚                                                             โ”‚
โ”‚  Any Schema: E-commerce, Analytics, CRM, etc.               โ”‚
โ”‚  Tables โ€ข Views โ€ข Indexes โ€ข Functions                       โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

External AI Services:
OpenAI API โ€ข Anthropic โ€ข Local LLMs (Ollama, etc.)

Key Benefits:
โœ… Works with ANY PostgreSQL database (no assumptions about schema)
โœ… No schema modifications required  
โœ… Read-only access (100% safe)
โœ… Automatic streaming for large results
โœ… Intelligent query understanding (singular vs plural)
โœ… Robust error handling (graceful AI failure recovery)
โœ… PostgreSQL case sensitivity support (mixed-case tables)
โœ… Production-ready security and performance
โœ… Universal database compatibility
โœ… Multiple output formats (table, JSON, CSV)
โœ… Free-text search across all columns
โœ… Authentication support
โœ… Comprehensive testing suite

Usage Examples

# Ask questions in natural language
./pgmcp-client -ask "What are the top 5 customers?" -format table
./pgmcp-client -ask "How many orders were placed today?" -format json

# Search across all text fields
./pgmcp-client -search "john" -format table

# Multiple questions at once
./pgmcp-client -ask "Show tables" -ask "Count users" -format table

# Different output formats
./pgmcp-client -ask "Export all data" -format csv -max-rows 1000

Features

  • Natural Language to SQL: Ask questions in plain English
  • Automatic Streaming: Handles large result sets automatically
  • Safe Read-Only Access: Prevents any write operations
  • Text Search: Search across all text columns
  • Multiple Output Formats: Table, JSON, and CSV
  • PostgreSQL Case Sensitivity: Handles mixed-case table names correctly
  • Universal Compatibility: Works with any PostgreSQL database

Example Database

The project includes two schemas:

  • schema.sql: Full Amazon-like marketplace with 5,000+ records
  • schema_minimal.sql: Minimal test schema with mixed-case "Categories" table

Key features:

  • Mixed-case table names ("Categories") for testing case sensitivity
  • Composite primary keys (order_items) for testing AI assumptions
  • Realistic relationships and data types

Use your own database:

export DATABASE_URL="postgres://user:pass@host:5432/your_db"
./pgmcp-server
./pgmcp-client -ask "What tables do I have?"

AI Error Handling

When AI generates incorrect SQL, PGMCP handles it gracefully:

{
  "error": "Column not found in generated query",
  "suggestion": "Try rephrasing your question or ask about specific tables",
  "original_sql": "SELECT non_existent_column FROM table..."
}

Instead of crashing, the system provides helpful feedback and continues operating.

MCP Integration

Cursor Integration

# Start server
export DATABASE_URL="postgres://user:pass@localhost:5432/your_db"
./pgmcp-server

Add to Cursor settings:

{
  "mcp.servers": {
    "pgmcp": {
      "transport": {
        "type": "http",
        "url": "http://localhost:8080/mcp"
      }
    }
  }
}

Claude Desktop Integration

Edit ~/.config/claude-desktop/claude_desktop_config.json:

{
  "mcpServers": {
    "pgmcp": {
      "transport": {
        "type": "http",
        "url": "http://localhost:8080/mcp"
      }
    }
  }
}

API Tools

  • ask: Natural language questions โ†’ SQL queries with automatic streaming
  • search: Free-text search across all database text columns
  • stream: Advanced streaming for very large result sets with pagination

Safety Features

  • Read-Only Enforcement: Blocks write operations (INSERT, UPDATE, DELETE, etc.)
  • Query Timeouts: Prevents long-running queries
  • Input Validation: Sanitizes and validates all user input
  • Transaction Isolation: All queries run in read-only transactions

Testing

# Unit tests
go test ./server -v

# Integration tests (requires PostgreSQL)
go test ./server -tags=integration -v

License

Apache 2.0 - See LICENSE file for details.

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