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Analyze and optimize AWS Aurora MySQL performance with natural-language AI reports.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "DB Assistant MCP Server" yet — see the docs or source repo.
Analyze this AWS Aurora MySQL database over the last 7 days, identify the slowest queries plus CPU and I/O bottlenecks, and generate an HTML report with optimization recommendations and priorities.
An HTML report with key metrics, slow-query analysis, bottleneck findings, and prioritized optimization recommendations.
Based on current Aurora MySQL query patterns and execution plans, identify missing or inefficient indexes, explain the likely impact of each index change on query latency and resource usage, and output a report.
A structured report listing index issues, impact assessments, and specific recommended changes.
Using Aurora MySQL performance data, workload trends, and historical knowledge, provide actionable tuning guidance including parameter changes, query optimization directions, and capacity planning advice, then generate an HTML summary.
An actionable HTML tuning summary covering parameters, SQL optimization, and capacity planning.
Inspect database schemas, index issues, table bloat, and query plans.
Manage MySQL databases with natural language for queries, CRUD, and monitoring.
Interact with MySQL databases using natural language for queries and management.
Interact with MySQL databases using natural language for queries and data operations.
Securely query and analyze multiple databases with natural language across systems.
Manage multiple databases with natural language for queries, analysis, backup, and security