PostgreSQL MCP Server v1.1.1 Release Notes

Release Date: December 6, 2025
Status: Production/Stable
Docker Image: writenotenow/postgres-mcp-enhanced:v1.1.1
PyPI Package: postgres-mcp-enhanced v1.1.1

🎉 What's New in v1.1.1

This is a maintenance and stability release building upon the major v1.1.0 intelligent assistant release. Version 1.1.1 focuses on reliability, performance improvements, and enhanced documentation.

Key Improvements

✅ Enhanced Stability

Improved error handling across all 63 tools
More robust connection pool management
Better handling of edge cases in complex queries

✅ Performance Optimizations

Reduced memory footprint for resource operations
Optimized query performance metrics collection
Faster schema introspection for large databases

✅ Documentation Enhancements

Updated installation guides with clearer instructions
Expanded troubleshooting section with real-world solutions
Improved examples in wiki documentation

✅ Security Updates

Updated dependencies to latest secure versions
Enhanced input validation for edge cases
Continued zero-vulnerability status

📦 Complete Feature Set

63 MCP Tools Across 9 Categories

Category	Tools	Description
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

10 MCP Resources - Database Meta-Awareness

Real-time database context that AI can access automatically:

database://schema - Complete database structure
database://capabilities - Server features and extensions
database://performance - Query performance metrics
database://health - Database health status
database://extensions - Extension inventory
database://indexes - Index usage statistics
database://connections - Connection pool status
database://replication - Replication lag and status
database://vacuum - Vacuum and wraparound status
database://locks - Lock contention information
database://statistics - Statistics quality

10 MCP Prompts - Guided Workflows

Step-by-step workflows for complex operations:

optimize_query - Query optimization workflow
index_tuning - Index analysis and recommendations
database_health_check - Comprehensive health assessment
setup_pgvector - pgvector installation and setup
json_operations - JSONB best practices
performance_baseline - Baseline establishment
backup_strategy - Backup planning and design
setup_postgis - PostGIS installation and usage
explain_analyze_workflow - Deep plan analysis
extension_setup - Extension installation guide

🚀 Quick Start

Docker (Recommended)

# Pull the latest image
docker pull writenotenow/postgres-mcp-enhanced:v1.1.1

# Run with your database connection
docker run -i --rm \
  -e DATABASE_URI="postgresql://user:pass@localhost:5432/db" \
  writenotenow/postgres-mcp-enhanced:v1.1.1 \
  --access-mode=restricted

Python Installation

# Install from PyPI
pip install postgres-mcp-enhanced==1.1.1

# Run the server
postgres-mcp --access-mode=restricted

One-Click Cursor Installation

🔧 Configuration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "postgres-mcp": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm", "-e", "DATABASE_URI",
        "writenotenow/postgres-mcp-enhanced:v1.1.1",
        "--access-mode=restricted"
      ],
      "env": {
        "DATABASE_URI": "postgresql://user:pass@localhost:5432/db"
      }
    }
  }
}

Cursor IDE

Add to MCP settings:

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

🛡️ Security & Quality

✅ Zero Known Vulnerabilities - Comprehensive security audit passed
✅ Pyright Strict Mode - 100% type-safe codebase (2,000+ issues resolved)
✅ SQL Injection Prevention - All queries use parameter binding
✅ 20+ Security Tests - All attack vectors covered
✅ CodeQL Scanning - Continuous security monitoring
✅ Dual Security Modes - Restricted (production) and unrestricted (development)

📚 Resources

Documentation

Complete Wiki - Full documentation with examples
Quick Start Guide - Get running in 30 seconds
Installation Guide - Detailed setup instructions
Security Best Practices - Production security
Troubleshooting - Common issues and solutions

Tools & Search

🔍 AI-Powered Documentation Search - Natural language search across all tools
📝 GitHub Gists - 7 practical examples and use cases
📰 Release Article - Deep dive into enterprise features

Distribution

🐳 Docker Hub - Container images
📦 PyPI Package - Python distribution
🌐 MCP Registry - Official MCP listing

🔄 Upgrade Guide

From v1.1.0 to v1.1.1

This is a drop-in replacement with no breaking changes:

Docker:

docker pull writenotenow/postgres-mcp-enhanced:v1.1.1
# Update your config to use v1.1.1 tag

Python:

pip install --upgrade postgres-mcp-enhanced

No configuration changes required - All existing configurations work unchanged.

From v1.0.x to v1.1.1

All v1.0.x tools remain fully functional. You gain:

✨ 10 new MCP Resources for database meta-awareness
✨ 10 new MCP Prompts for guided workflows
✨ Enhanced AI assistant capabilities
✨ Improved performance and stability

No breaking changes - Upgrade with confidence!

🐛 Bug Fixes

Fixed edge case in connection pool management under high load
Improved error messages for extension-related failures
Enhanced handling of very large result sets
Corrected resource caching behavior in certain scenarios
Fixed minor type annotations for improved IDE support

📊 Technical Specifications

PostgreSQL Compatibility: 13, 14, 15, 16, 17, 18
Python Version: 3.10+
Platform Support: Windows, Linux, macOS (amd64, arm64)
Container Size: ~150MB compressed
Dependencies: Fully pinned and audited
Code Quality: Pyright strict mode, zero linter errors
Test Coverage: 90%+ with comprehensive integration tests

🏆 Why Choose This Server?

✅ Most Comprehensive - 63 tools + 10 resources + 10 prompts
✅ Production Ready - Zero known vulnerabilities, enterprise-grade
✅ AI-Native - Vector search, semantic operations, ML-ready
✅ Intelligent - Meta-awareness and guided workflows
✅ Active Maintenance - Regular updates and security patches
✅ Well Documented - 16-page wiki + AI-powered search
✅ Type Safe - 100% Pyright strict mode compliance
✅ Multi-Platform - Docker + Python + pip installation options

📝 Changelog Summary

v1.1.1 (December 6, 2025)

Enhanced stability and error handling
Performance optimizations for large databases
Documentation improvements
Security dependency updates
Bug fixes for edge cases

v1.1.0 (October 4, 2025)

Added 10 MCP Resources for database meta-awareness
Added 10 MCP Prompts for guided workflows
Transformed into intelligent database assistant
Pyright strict mode compliance (2,000+ issues resolved)
Zero breaking changes

v1.0.0 (October 3, 2025)

Production release with 63 specialized tools
Enterprise-grade security and testing
Multi-platform Docker support
Comprehensive documentation

🤝 Contributing

We welcome contributions! See our Contributing Guide for details.

Report Issues: GitHub Issues
Security: Report vulnerabilities to admin@adamic.tech
Discussions: GitHub Discussions

📄 License

MIT License - See LICENSE file for details.

🙏 Acknowledgments

Thank you to the PostgreSQL community, MCP developers, and all contributors who made this release possible!

⭐ If you find this project useful, please star it on GitHub!

📥 Download:

Docker: docker pull writenotenow/postgres-mcp-enhanced:v1.1.1
PyPI: pip install postgres-mcp-enhanced==1.1.1
Source: GitHub Release

🔗 Quick Links:

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

v1.1.1 - Production/Stable