Last Updated October 18, 2025 8:59 PM EST - Production/Stable v1.1.1

Enterprise-grade PostgreSQL MCP server with enhanced security, comprehensive testing, AI-native database operations, intelligent meta-awareness, and guided workflows.

GitHub Docker Pulls License: MIT Version Status MCP Registry PyPI Security CodeQL Type Safety

Can't find what you're looking for? Use our AI-powered search interface to search both PostgreSQL and SQLite MCP Server documentation:

• 🤖 Natural Language Queries - Ask questions in plain English
• ⚡ Instant Results - AI-enhanced answers with source attribution
• 📚 Comprehensive Coverage - Searches all 63 PostgreSQL tools + 73 SQLite tools
• 🎯 Smart Context - Understands technical questions and provides relevant examples

→ Try AI Search Now

Example queries: "How do I optimize PostgreSQL query performance?", "What PostGIS features are available?", "How do I use pgvector for semantic search?"

For detailed documentation, examples, and guides, visit our comprehensive wiki:

• Quick Start Guide - Get running in 30 seconds
• Installation & Configuration - Detailed setup
• All Tool Categories - 63 specialized tools
• Security Best Practices - Production security
• Troubleshooting - Common issues

📰 Read the v1.0.5 Release Article - Learn about enterprise features, AI-native operations, and intelligent meta-awareness

63 specialized MCP tools + 10 intelligent resources + 10 guided prompts for PostgreSQL operations:

• Core Database (9): Schema management, SQL execution, health monitoring
• JSON Operations (11): JSONB operations, validation, security scanning
• Text Processing (5): Similarity search, full-text search, fuzzy matching
• Statistical Analysis (8): Descriptive stats, correlation, regression, time series
• Performance Intelligence (6): Query optimization, index tuning, workload analysis
• Vector/Semantic Search (8): Embeddings, similarity search, clustering
• Geospatial (7): Distance calculation, spatial queries, GIS operations
• Backup & Recovery (4): Backup planning, restore validation, scheduling
• Monitoring & Alerting (5): Real-time monitoring, capacity planning, alerting

• database://schema: Complete schema with tables, columns, indexes
• database://capabilities: Server capabilities and installed extensions
• database://performance: Query performance metrics from pg_stat_statements
• database://health: Comprehensive health status
• database://extensions: Installed extensions with versions
• database://indexes: Index usage statistics and recommendations
• database://connections: Active connections and pool status
• database://replication: Replication status and lag
• database://vacuum: Vacuum status and transaction ID wraparound
• database://locks: Current lock information
• database://statistics: Table statistics quality

• optimize_query: Step-by-step query optimization
• index_tuning: Comprehensive index analysis
• database_health_check: Full health assessment
• setup_pgvector: Complete pgvector setup guide
• json_operations: JSONB best practices
• performance_baseline: Establish performance baselines
• backup_strategy: Design backup strategy
• setup_postgis: PostGIS setup and usage
• explain_analyze_workflow: Deep dive into EXPLAIN plans
• extension_setup: Extension installation guide

Enhanced with pg_stat_statements, hypopg, pgvector, and PostGIS extensions.

1. PostgreSQL Database (version 13-18)
2. Environment Variable: DATABASE_URI="postgresql://user:pass@host:5432/db"
3. MCP Client: Claude Desktop, Cursor, or compatible client

See Installation Guide for detailed setup instructions.

Step 1: Pull the image

docker pull writenotenow/postgres-mcp-enhanced:latest

Step 2: Run with your database connection

docker run -i --rm \
 -e DATABASE_URI="postgresql://user:pass@localhost:5432/db" \
 writenotenow/postgres-mcp-enhanced:latest \
 --access-mode=restricted

Step 1: Install the package

pip install postgres-mcp-enhanced

Step 2: Run the server

postgres-mcp --access-mode=restricted

Step 1: Clone the repository

git clone https://github.com/neverinfamous/postgres-mcp.git
cd postgres-mcp

Step 2: Install dependencies and run tests

uv sync
uv run pytest -v

📖 See Full Installation Guide →

Click the button below to install directly into Cursor:

Install to Cursor

Or copy this deep link:

cursor://anysphere.cursor-deeplink/mcp/install?name=PostgreSQL%20Enterprise%20MCP%20Server&config=eyJkb2NrZXIuaW8vd3JpdGVub3Rlbm93L3Bvc3RncmVzLW1jcC1lbmhhbmNlZDp2MS4xLjEiOnsidHJhbnNwb3J0Ijp7InR5cGUiOiJzdGRpbyJ9fX0=

• ✅ Docker installed and running
• ✅ PostgreSQL database (version 13-18)
• ✅ DATABASE_URI environment variable configured

After installation, Cursor will use this Docker-based configuration. If you prefer manual setup, add this to your MCP client configuration:

{
 "docker.io/writenotenow/postgres-mcp-enhanced:v1.1.1": {
 "transport": {
 "type": "stdio"
 }
 }
}

📖 See Full Installation Guide →

Zero known vulnerabilities - Comprehensive security audit passed:

• ✅ SQL injection prevention with parameter binding
• ✅ 20+ security test cases covering all attack vectors
• ✅ Dual security modes (restricted/unrestricted)
• ✅ Advanced query validation
• ✅ CodeQL security scanning passing
• ✅ Pyright strict mode - 2,000+ type issues resolved, 100% type-safe codebase

Security Modes:

• Restricted (Production): Read-only, query validation, resource limits
• Unrestricted (Development): Full access with parameter binding protection

📖 Security Best Practices →

• Database health monitoring (indexes, connections, vacuum, buffer cache)
• Query performance tracking via pg_stat_statements
• Capacity planning and growth forecasting
• Replication lag monitoring

• AI-powered index tuning with DTA algorithms
• Hypothetical index testing via hypopg (zero-risk)
• Query plan analysis and optimization
• Workload analysis and slow query detection

• Vector similarity search via pgvector
• Geospatial operations via PostGIS
• Semantic search and clustering
• Natural language database interactions

📖 Explore All Features →

Explore comprehensive documentation for each category:

Resources provide real-time database meta-awareness - AI can access these automatically without explicit tool calls:

💡 Key Benefit: Resources reduce token usage by providing cached context vs. repeated queries!

Prompts provide guided workflows for complex operations - step-by-step instructions with examples:

💡 Key Benefit: Prompts guide users through complex multi-step operations with PostgreSQL best practices!

📖 View Complete Documentation →

Required extensions for full functionality:

• pg_stat_statements (built-in) - Query performance tracking
• pg_trgm & fuzzystrmatch (built-in) - Text similarity
• hypopg (optional) - Hypothetical index testing
• pgvector (optional) - Vector similarity search
• PostGIS (optional) - Geospatial operations

Quick Setup:

Run these commands in your PostgreSQL database:

CREATE EXTENSION IF NOT EXISTS pg_stat_statements;
CREATE EXTENSION IF NOT EXISTS pg_trgm;
CREATE EXTENSION IF NOT EXISTS fuzzystrmatch;

📖 Extension Setup Guide →

• 🌟 NEW: MCP Resources (10): Real-time database meta-awareness
  • Instant access to schema, capabilities, performance, health
  • Reduces token usage by providing cached context
  • AI can access database state without explicit queries
• 🌟 NEW: MCP Prompts (10): Guided workflows for complex operations
  • Step-by-step query optimization workflow
  • Comprehensive index tuning guide
  • Complete database health assessment
  • pgvector and PostGIS setup guides
  • JSONB best practices and optimization
• ✨ Intelligent Assistant: Transforms from tool collection to database expert
  • Proactive optimization suggestions
  • Context-aware recommendations
  • PostgreSQL-specific best practices
• 🔒 Code Quality: Pyright strict mode compliance
  • Resolved 2,000+ type issues
  • 100% type-safe codebase
  • Enhanced reliability and maintainability
• 📦 Zero Breaking Changes: All existing tools work unchanged

• Production Ready: Enterprise-grade PostgreSQL MCP server
• 63 Specialized Tools: Complete feature set across 9 categories
• Zero Known Vulnerabilities: Comprehensive security audit passed
• Type Safety: Pyright strict mode compliance
• Multi-Platform: Windows, Linux, macOS (amd64, arm64)

• Backup & Recovery: 4 new tools for enterprise backup planning
• Monitoring & Alerting: 5 new tools for real-time monitoring
• All 63 Tools Ready: Complete Phase 5 implementation

• Vector Search: 8 tools with pgvector integration
• Geospatial: 7 tools with PostGIS integration
• Extension Support: pgvector v0.8.0, PostGIS v3.5.0

• Statistical Analysis: 8 advanced statistics tools
• Performance Intelligence: 6 optimization tools

{
 "mcpServers": {
 "postgres-mcp": {
 "command": "docker",
 "args": ["run", "-i", "--rm", "-e", "DATABASE_URI", 
 "writenotenow/postgres-mcp-enhanced:latest", "--access-mode=restricted"],
 "env": {
 "DATABASE_URI": "postgresql://user:pass@localhost:5432/db"
 }
 }
 }
}

{
 "mcpServers": {
 "postgres-mcp": {
 "command": "postgres-mcp",
 "args": ["--access-mode=restricted"],
 "env": {
 "DATABASE_URI": "postgresql://user:pass@localhost:5432/db"
 }
 }
 }
}

📖 MCP Configuration Guide →

Common Issues:

• Connection Refused: Verify PostgreSQL is running with pg_isready
• Extension Not Found: Install required extensions (see Extension Setup)
• Permission Denied: Check database user permissions
• MCP Server Not Found: Validate MCP client configuration

📖 Full Troubleshooting Guide →

Run all tests:

uv run pytest -v

Security tests:

python security/run_security_test.py

With coverage:

uv run pytest --cov=src tests/

Test Results:

• ✅ Security: 20/20 passed (100% protection)
• ✅ SQL Injection: All vectors blocked
• ✅ Integration: All operations validated
• ✅ Type Safety: Pyright strict mode (2,000+ issues resolved)
• ✅ Compatibility: PostgreSQL 13-18 supported

• ✅ Zero Known Vulnerabilities - Comprehensive security audit passed
• ✅ Pyright Strict Mode - 2,000+ type issues resolved, 100% type-safe codebase
• ✅ Enterprise-Grade - Production-ready with advanced features
• ✅ 63 Specialized Tools - Complete database operation coverage
• ✅ 10 Intelligent Resources - Real-time database meta-awareness (NEW in v1.1.0!)
• ✅ 10 Guided Prompts - Step-by-step workflows for complex operations (NEW in v1.1.0!)
• ✅ AI Assistant Capabilities - Proactive optimization and recommendations
• ✅ Real-Time Analytics - pg_stat_statements integration
• ✅ AI-Native - Vector search, semantic operations, ML-ready
• ✅ Active Maintenance - Regular updates and security patches
• ✅ Comprehensive Documentation - 16-page wiki with examples

🌟 v1.1.0 Differentiation: Only PostgreSQL MCP server with intelligent meta-awareness and guided workflows!

• 📚 Complete Wiki - Full documentation
• 📝 GitHub Gists - 7 practical examples and use cases
• 🛡️ Security Policy - Vulnerability reporting
• 🤝 Contributing - Development guidelines
• 🐳 Docker Hub - Container images
• 📦 PyPI Package - Python package

GitHub Gists - Practical Examples:

• Complete Feature Showcase - All 63 tools with comprehensive examples
• Security Best Practices - SQL injection prevention and production security
• Performance Intelligence - Query optimization and index tuning strategies
• Vector/Semantic Search - pgvector integration and AI-native operations
• Enterprise Monitoring - Real-time monitoring and alerting workflows
• Geospatial Operations - PostGIS integration and spatial queries
• JSON/JSONB Operations - Advanced JSONB operations and validation

• Version 1.1.0 - Intelligent assistant release (October 4, 2025)
• 63 MCP Tools across 9 categories
• 10 MCP Resources - Database meta-awareness (NEW!)
• 10 MCP Prompts - Guided workflows (NEW!)
• 100% Type Safe - Pyright strict mode (2,000+ issues resolved)
• Zero Known Vulnerabilities - Security audit passed
• Zero Linter Errors - Clean codebase with comprehensive type checking
• PostgreSQL 13-18 - Full compatibility
• Multi-platform - Windows, Linux, macOS (amd64, arm64)
• 7,500+ lines - 14 modules, comprehensive implementation

• License: MIT - see LICENSE file
• Security: Report vulnerabilities to admin@adamic.tech
• Contributing: See CONTRIBUTING.md

Enterprise-grade PostgreSQL MCP server with comprehensive security, real-time analytics, and AI-native operations.