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AI Model Context Protocol (MCP) Server

1 post · Jan 2026

What this trail covers

PlanetScale is introducing an MCP server that allows AI tools to connect to the PlanetScale API, exposing organizations, databases, branches, schema, and Insights data. This enables AI tools to assist with database optimization, query analysis, natural language data querying, and debugging by providing direct access to database metadata and performance metrics. The MCP server includes configurable access permissions, built-in safeguards for query execution (replica routing, ephemeral credentials, destructive query protection, and human confirmation for DDL).

All PlanetScale trails
  1. Introducing the PlanetScale MCP serverThis post introduces the PlanetScale MCP server, a hosted service that exposes PlanetScale organizations, databases, branches, schema, and Insights data to MCP-compatible AI tools. It details the available tools for interacting with PlanetScale data (e.g., `get_insights`, `execute_read_query`, `execute_write_query`), configurable access permissions, and built-in safeguards for query execution such as automatic replica routing, ephemeral credentials, query tracking, destructive query protection, and human confirmation for DDL. Use cases include schema and query optimization, natural language data querying, and debugging with full context.