- Postgresql Mcp
Postgresql Mcp
## Overview
This is an MCP (Model Context Protocol) server that provides intelligent analysis, documentation, and complete CRUD operations for PostgreSQL databases. It combines deterministic schema extraction with AI-powered reasoning and secure data manipulation operations to help users and AI agents understand and interact with complex database structures.
**Performance Optimized & Extended:** Started at 38 tools, optimized to 19 tools (~50% reduction), then strategically extended to 27 tools with high-value query optimization, data management, transactions, and monitoring capabilities.
### Key Features
- **Comprehensive Coverage**: 27 carefully designed tools covering all PostgreSQL operations
- **Schema Extraction**: Automatically extract tables, columns, relationships, and constraints
- **Intelligent Analysis**: Detect junction tables, implicit relationships, and suggest optimal joins
- **AI-Powered Insights**: Leverage Ollama/LLM to generate business explanations and recommendations
- **Complete CRUD Operations**: Unified tools for all data manipulation with SQL injection prevention
- **Query Optimization**: Execution plan analysis, combined index analysis (suggest + unused detection)
- **Data Management**: Import/export (CSV/JSON/SQL), full-text search
- **Transaction Support**: Atomic multi-operation transactions with rollback
- **Monitoring**: Database statistics, cache metrics, slow queries, connection tracking
- **Multiple Output Formats**:
- Mermaid ER diagrams (with SVG rendering)
- Mermaid relationship flowcharts (with SVG rendering)
- Comprehensive Markdown documentation
- Visual diagram files (SVG, PNG, PDF)
- **Query Assistance**: Smart join type recommendations (INNER vs LEFT)
- **Modular Architecture**: Clean, extensible design organized by capability
- **Diagram Rendering**: Auto-generate visual database structure diagrams
- **Security**: Parameterized queries, input validation, SQL injection prevention
Overview
Overview
This is an MCP (Model Context Protocol) server that provides intelligent analysis, documentation, and complete CRUD operations for PostgreSQL databases. It combines deterministic schema extraction with AI-powered reasoning and secure data manipulation operations to help users and AI agents understand and interact with complex database structures.
Performance Optimized & Extended: Started at 38 tools, optimized to 19 tools (~50% reduction), then strategically extended to 27 tools with high-value query optimization, data management, transactions, and monitoring capabilities.
Key Features
- Comprehensive Coverage: 27 carefully designed tools covering all PostgreSQL operations
- Schema Extraction: Automatically extract tables, columns, relationships, and constraints
- Intelligent Analysis: Detect junction tables, implicit relationships, and suggest optimal joins
- AI-Powered Insights: Leverage Ollama/LLM to generate business explanations and recommendations
- Complete CRUD Operations: Unified tools for all data manipulation with SQL injection prevention
- Query Optimization: Execution plan analysis, combined index analysis (suggest + unused detection)
- Data Management: Import/export (CSV/JSON/SQL), full-text search
- Transaction Support: Atomic multi-operation transactions with rollback
- Monitoring: Database statistics, cache metrics, slow queries, connection tracking
- Multiple Output Formats:
- Mermaid ER diagrams (with SVG rendering)
- Mermaid relationship flowcharts (with SVG rendering)
- Comprehensive Markdown documentation
- Visual diagram files (SVG, PNG, PDF)
- Query Assistance: Smart join type recommendations (INNER vs LEFT)
- Modular Architecture: Clean, extensible design organized by capability
- Diagram Rendering: Auto-generate visual database structure diagrams
- Security: Parameterized queries, input validation, SQL injection prevention
Server Config
{
"mcpServers": {
"SchemaIntelligence": {
"command": "C:\\Users\\user\\.local\\bin\\uv.EXE",
"args": [
"run",
"--frozen",
"--with",
"mcp[cli]",
"--with",
"psycopg2",
"--with",
"ollama",
"--with",
"pymermaid",
"--with",
"requests",
"--with",
"pillow",
"mcp",
"run",
"C:\\Users\\user\\Desktop\\MCP-ToolHub\\PostgreSQL-MCP\\postgresql_server.py"
],
"env": {
"DB_HOST": "localhost",
"DB_PORT": "6739",
"DB_NAME": "MCP",
"DB_USER": "postgres",
"DB_PASSWORD": "radha",
"OLLAMA_BASE_URL": "http://192.168.1.143:11434",
"OLLAMA_MODEL": "gpt-oss:120b-cloud",
"DEBUG": "False"
}
}
}
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