Turn Your AI Assistant Into a PostgreSQL Performance Expert

Stop letting your AI assistants guess at database performance issues. Postgres MCP Pro transforms any MCP-compatible AI into a skilled database administrator with professional-grade PostgreSQL optimization tools.

Why This Exists

You know the drill: your app slows down, queries take forever, and you're stuck manually analyzing EXPLAIN plans or guessing which indexes might help. Meanwhile, your AI assistant can write SQL but has no clue about the performance implications or database health.

Postgres MCP Pro bridges that gap. Instead of having your AI generate generic "try adding an index" suggestions, it gets access to the same algorithmic approaches used by enterprise database tuning advisors.

What Makes This Different

Real DBA Tools, Not Just Query Execution

Most PostgreSQL MCP servers just wrap database connections. This one includes:

• Industrial-strength index tuning based on Microsoft SQL Server's Anytime Algorithm
• Comprehensive health monitoring covering buffer cache, vacuum health, replication lag, connection utilization
• Workload analysis using pg_stat_statements to identify actual performance bottlenecks
• Hypothetical index simulation with hypopg to predict performance gains before making changes

Safety Without Sacrificing Capability

Two access modes give you flexibility:

• Unrestricted: Full read/write for development environments
• Restricted: Read-only with query time limits for production safety

The restricted mode uses SQL parsing to prevent transaction control statements, making it safe to connect to production databases without risking data integrity.

Real-World Impact

Development Workflow: Your AI can now diagnose why that ORM-generated query is taking 3 seconds, suggest specific indexes, and show you the projected performance improvement—all in one conversation.

Production Troubleshooting: Connect safely to production databases and get health reports, slow query analysis, and index recommendations without manual EXPLAIN plan interpretation.

Code Reviews: Have your AI analyze database schemas and query patterns to catch performance issues before they hit production.

Getting Started

Install with Docker (recommended) or Python 3.12+:

# Docker approach
docker pull crystaldba/postgres-mcp

# Python approach  
pipx install postgres-mcp

Configure with Claude Desktop, Cursor, or any MCP client:

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

What Your AI Can Do Now

• "Check my database health" → Get comprehensive reports on indexes, vacuum status, buffer cache hit rates, connection health
• "Why is this query slow?" → Analyze execution plans and get specific optimization recommendations
• "Suggest indexes for my workload" → Analyze pg_stat_statements data and recommend optimal index configurations
• "What are my top resource-consuming queries?" → Get ranked lists of queries by execution time, frequency, or resource usage

Performance Analysis That Actually Works

The index tuning implementation deserves special attention. Rather than having your AI guess at indexing strategies, it:

1. Identifies problematic queries from pg_stat_statements data
2. Generates candidate indexes by parsing SQL and identifying filter/join/sort columns
3. Uses greedy search optimization to find optimal index combinations within time/space budgets
4. Simulates performance improvements with hypopg before recommending changes
5. Shows before/after query plans so you understand exactly what will change

This isn't theoretical—it's the same algorithmic approach used by enterprise database tuning tools.

SSE Transport for Team Usage

Unlike stdio-only servers, this supports Server-Sent Events transport, letting multiple developers share one server instance:

docker run -p 8000:8000 \
  -e DATABASE_URI=postgresql://... \
  crystaldba/postgres-mcp --transport=sse

Point multiple MCP clients at http://localhost:8000/sse and you're set.

Ready to Install?

Your AI assistant is already capable of understanding complex database concepts. Give it the tools to act on that understanding with professional-grade PostgreSQL optimization capabilities.

The combination of AI reasoning with proven algorithmic approaches beats both pure AI guessing and manual database administration. Install Postgres MCP Pro and see the difference in your next database performance conversation.