Transforming Your AI Agents into Postgres Experts

We’re excited to announce the launch of Postgres MCP Pro, an open source MCP server that turns AI tools such as Claude Desktop or the Cursor IDE into powerful database advisors.

Postgres MCP Pro implements the Model Context Protocol (MCP), an emerging standard that allows AI models to connect with external systems and tools, expanding their capabilities beyond what’s possible with their internal knowledge alone.

Postgres MCP Pro is built to support you at all stages of the software development process—from initial coding through testing and deployment, and into production tuning and maintenance.

Why We Built Postgres MCP Pro

Database performance issues represent one of the most persistent challenges in software development. Developers spend countless hours chasing down obscure performance problems, and too many applications suffer from poor performance or preventable bottlenecks. Even when teams identify an issue, they often lack the knowledge needed to fix it.

Root causes of database problems include missing or duplicate indexes, improper configuration, poorly written queries, inadequate capacity, inappropriate resource management. Though many different things can go wrong, the consequence is generally either poor application performance, poor availability, or wasteful spending on excessive capacity.

Developments in AI offers now make it possible for any developer to solve database performance problems that would have otherwise required an expert.

The features in Postgres MCP Pro all aim to address one of two core goals:

1. Removing friction. Eliminating the obstacles where developers get stuck, saving valuable time that could be better spent building the next new feature.
2. Adding quality. Making it easy for developers to build better software—applications run fast, remain reliable, deliver superior experiences to end users, and reduce infrastructure costs.

Packaging Crystal DBA’s core technology as an MCP server allows it to benefit from ecosystem effects. For example, using Postgres MCP Pro with a code editor such as Cursor builds a link between code and how it actually runs. When used alongside other MCP servers, the network effects grow. For example, you might extract data from files, process it, and store the results in a Postgres database.

Much More Than a Database Connection

While several Postgres MCP servers exist already, their functionality is limited to executing SQL queries and providing information about the tables in the database.

Postgres MCP Pro is fundamentally different. It incorporates industrial-strength database optimization algorithms, comprehensive health checks, and performance analysis capabilities.

These tools make it possible to do things that LLMs alone cannot do. Proven optimization algorithms search systematically, so we can guarantee that they will find a better solution if it exists. With LLMs, there are no such guarantees. Similarly, when it comes to basic database health checks, we want our tools to do the same thing every time, which is not what we get from LLMs.

The synergy can run the other way as well. In certain scenarios, an LLM might use its holistic understanding of the application’s code to suggest a database index. Postgres MCP Pro can then validate that suggestion by simulating the impact of the improvement.

Postgres MCP Pro in Action

To explore Postgres MCP Pro’s capabilities, we decided to build a movie ratings website using the IMDB dataset. In the process, we used Postgres MCP Pro to improve application performance dramatically.

We started by using an AI assistant to generate the initial application code—a fully functional website with ratings, search, and authentication capabilities. The code worked, but the performance was unacceptably slow. This is a common scenario: code, whether written by AI or humans, often works correctly but lacks the performance optimizations needed for use in production or at scale.

Here’s where Postgres MCP Pro made a dramatic difference. We connected it to Cursor, then asked it to improve our application’s performance. The AI agent, now equipped with Postgres MCP Pro’s capabilities:

1. Analyzed the database schema and code to identify problematic queries
2. Diagnosed performance issues using Postgres MCP Pro’s tools to examine query plans and resource usage
3. Added appropriate indexes to dramatically improve search performance
4. Removed unused and bloated indexes to reclaim storage space
5. Implemented caching for expensive queries and image loading
6. Created a migration script to safely apply all these changes

The results were impressive: The application felt dramatically faster and database load was significantly reduced. Postgres MCP Pro estimated that searches would run 10-100x faster and page loads improved 2-5x. All of this happened in minutes rather than the hours it would typically take even an experienced team.

We also used Postgres MCP Pro to identify and fix additional issues—missing data in movie detail pages and an incorrect sorting algorithm for top-rated movies. In each case, it helped the AI agent understand both the code and the underlying data, leading to solutions that were grounded in reality rather than educated guesses.

See the videos and read the play-by-play description.

Features

Key features of Postgres MCP Pro comprises a collection of tools. In the initial release, highlights include:

Advanced Index Tuning with Proven Algorithms

A key component of Postgres MCP Pro is a sophisticated index tuning capability based on the Anytime Algorithm, which was originally developed for Microsoft SQL Server and is recognized as an industrial-strength approach to automatic index tuning.

Comprehensive Database Health Analysis

Beyond indexing, Postgres MCP Pro provides thorough database health checks that systematically identify potential issues before they impact your application.

Among other things, these checks:

• Examine index health by looking for unused indexes or duplicate indexes, both of which waste space. It also looks for bloated indexes whose storage pages contain many invalid entries.
• Measure buffer cache hit rates to ensure your database is effectively utilizing memory resources and identifies connection issues that could be limiting performance.
• Monitor vacuum health, by looking for transaction ID wraparound.
• Without proper vacuuming, Postgres can eventually stop accepting writes altogether—a scenario Postgres MCP Pro helps you avoid.

Protected Execution for Development and Production

We know that different environments have different security needs. Postgres MCP Pro provides two access modes to give you appropriate controls:

• Unrestricted Mode allows full read/write access, enabling your AI assistants to help with schema changes, data manipulation, and other modifications. This is helpful for rapid application development.
• Restricted Mode limits operations to read-only transactions and imposes constraints on resource utilization, ensuring that exploratory work can’t impact your live systems.

Summary

Postgres MCP Pro is a powerful tool built to help every developer operate Postgres like an expert. Using the MCP protocol, it integrates with a wide range of AI assistants and agents, such as Claude Desktop, Cursor, Windsurf, and Goose.

The combination of AI traditional software are a potent mix, allowing developers to build better software, stop wasting time fixing database problems, and make the most of emerging AI code generation.

To get started, please visit the Postgres MCP Pro GitHub repository. Please star the project if you like it!

We are excited to see how Postgres MCP Pro will change how you build and run database applications.