Pgtuner MCP
P

Pgtuner MCP

A PostgreSQL performance tuning server based on the MCP protocol, providing AI-driven query analysis, index optimization, database health checks, and performance monitoring functions, supporting HypoPG virtual index testing and multiple deployment modes.
2.5 points
7.2K

What is the PostgreSQL Performance Tuning Assistant?

This is an intelligent database performance optimization tool based on the Model Context Protocol (MCP). It can automatically analyze the performance issues of your PostgreSQL database, provide professional optimization suggestions, and help you improve the database operation efficiency without in-depth knowledge of complex database tuning techniques.

How to use the Performance Tuning Assistant?

After connecting to your PostgreSQL database through simple configuration, you can use various tools to analyze query performance, check the database health status, and optimize index configuration. The tool provides an intuitive interface and clear suggestions, making database optimization simple and efficient.

Applicable Scenarios

Suitable for any application scenario using the PostgreSQL database, especially: - The application response becomes slow, and there is a suspicion of database performance issues. - Regular database health status checks are required. - You want to optimize query performance but lack professional knowledge. - Evaluation before planning a database architecture adjustment. - Daily monitoring and maintenance of the production environment database.

Main Features

Query Performance Analysis
Automatically identify slow queries, analyze execution plans, and find performance bottlenecks. Support EXPLAIN and EXPLAIN ANALYZE analysis, and provide detailed performance statistics.
Intelligent Index Optimization
Recommend the optimal index configuration based on AI algorithms, support virtual index testing (no actual creation required), and help you safely optimize the index strategy.
Comprehensive Health Check
Provide a database health score, monitor key indicators such as connection usage, cache hit rate, lock contention, and replication delay, and detect potential problems in a timely manner.
VACUUM Monitoring
Monitor the progress of VACUUM operations in real-time, analyze the effectiveness of automatic cleaning configuration, identify tables that need maintenance, and ensure efficient use of database space.
I/O Performance Analysis
Analyze disk read and write patterns, identify hot tables and indexes, monitor cache efficiency, and help optimize storage configuration and query patterns.
Bloat Detection
Detect space bloat problems in tables and indexes, identify recyclable space, provide cleaning suggestions, and reduce storage waste.
Configuration Review
Analyze PostgreSQL configuration parameters, provide optimization suggestions, covering key settings such as memory, checkpoints, WAL, and automatic cleaning.
Advantages
AI-driven intelligent suggestions, reducing the threshold of professional knowledge
Virtual index testing function, avoiding risks in the production environment
Comprehensive health check, covering all aspects of the database
Real-time monitoring ability, detecting performance problems in a timely manner
Detailed execution plan analysis, accurately locating bottlenecks
Support for multiple deployment modes, flexibly adapting to different environments
Limitations
Requires PostgreSQL extension support (such as pg_stat_statements)
Has a certain performance impact on the database (about 1 - 5%)
Requires appropriate database user permissions
Some advanced features require PostgreSQL 14+
Virtual index testing is at the session level and will失效 after restart

How to Use

Install the Tool
Install the performance tuning assistant package through pip
Configure Database Connection
Set environment variables to specify database connection information
Install PostgreSQL Extensions
Enable necessary extensions on the target database
Configure the MCP Client
Add server configuration in Claude Desktop or other MCP clients
Start Using
After starting the tool, you can use various performance analysis functions

Usage Examples

Diagnose the Problem of Slow Application Response
When users report that the application response is slow, use the performance tuning assistant to quickly locate database-level problems.
Regular Health Check
As part of the daily maintenance of a DBA, regularly run health checks to ensure the database is in good running condition.
Performance Evaluation Before New Feature Launch
Evaluate the impact on database performance before deploying new features or major version updates.
Space Optimization and Cleaning
When disk space is tight, identify the bloated space that can be cleaned.

Frequently Asked Questions

Does this tool have a performance impact on the production database?
What permissions do I need to use this tool?
Is virtual index testing safe?
Which PostgreSQL versions are supported?
How to exclude queries from specific users (such as monitoring users)?
Where will the data collected by the tool be stored?
Can multiple databases be monitored?
How to update the configuration suggestions of the tool?

Related Resources

GitHub Repository
Source code and latest version
PyPI Package Page
Python package installation and version information
Docker Image
Docker containerized deployment
PostgreSQL Official Documentation
PostgreSQL official documentation and reference
MCP Protocol Documentation
Model Context Protocol technical specification
Glama.ai MCP Server Directory
Page in the MCP server directory

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "pgtuner_mcp": {
      "command": "python",
      "args": ["-m", "pgtuner_mcp"],
      "env": {
        "DATABASE_URI": "postgresql://user:password@localhost:5432/mydb"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

{
  "mcpServers": {
    "pgtuner_mcp": {
      "type": "http",
      "url": "http://localhost:8080/mcp"
    }
  }
}

{
  "mcpServers": {
    "pgtuner_mcp": {
      "type": "sse",
      "url": "http://localhost:8080/sse"
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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