About this project

MySQLTuner is a Perl script designed to help database administrators quickly review MySQL, MariaDB, and Percona Server installations and make informed adjustments to improve performance and stability. The tool retrieves current configuration variables and status data, presenting them in a concise format alongside actionable performance suggestions. Key features include: - Comprehensive Analysis: Supports over 900 indicators, KPIs, and recommendations covering system resources, server version, error logs, cloud infrastructure, storage engines, security, connections, performance, replication, performance schema, schema modeling, predictive capacity planning, and a weighted health score (0-100). - Broad Compatibility: Full support for MySQL, Percona Server, MariaDB, Galera Cluster, and Percona XtraDB Cluster. Partial support for Windows via WSL2. - Security Auditing: Checks for anonymous users, weak passwords, SSL/TLS configuration, authentication plugin security, and CVE vulnerabilities. - Cloud Support: Experimental support for AWS RDS/Aurora, GCP Cloud SQL, Azure, and DigitalOcean with automatic detection. - AI and MCP Integration: Native support for AI workflows including a Model Context Protocol (MCP) server daemon and structured JSON output for AI client tools like Claude Desktop, Cursor, and VS Code/Cline. - Reporting: Generates text, HTML, JSON, and Markdown reports. Supports historical trend analysis by comparing with previous runs. - Guided Auto-Fix: Generates ready-to-apply SET GLOBAL SQL statements and configuration blocks from recommendations. - Container and Systemd Integration: Automatic log detection from Docker, Podman, Kubernetes, and Systemd journal. The tool requires Perl 5.6+ and appropriate MySQL privileges (SELECT, PROCESS, SHOW DATABASES, EXECUTE, REPLICATION CLIENT, SHOW VIEW). It can be installed via direct download, git clone, Homebrew, or Docker. Important notes: The tool recommends waiting at least 24 hours of uptime for accurate results, and users should understand each recommendation before applying changes. Always test in staging environments first.