Schema Lint MCP

An MCP server that validates schema files against lint rules using Claude or Gemini AI.

Installation

1. Clone this repository

2. Install dependencies: npm install

3. Build the project: npm run build

Related MCP server: Lintbase

Configure with Claude Code

Add this to your Claude Code settings JSON file:

{
  "mcpServers": {
    "schema-lint": {
      "command": "node",
      "args": ["/path/to/schema-lint-mcp/dist/index.js"],
      "env": {
        "ANTHROPIC_API_KEY": "your-anthropic-api-key-here",
        "GEMINI_API_KEY": "your-gemini-api-key-here"
      }
    }
  }
}

Or use environment variables:

{
  "mcpServers": {
    "schema-lint": {
      "command": "node",
      "args": ["/path/to/schema-lint-mcp/dist/index.js"],
      "env": {
        "ANTHROPIC_API_KEY": "${env:ANTHROPIC_API_KEY}",
        "GEMINI_API_KEY": "${env:GEMINI_API_KEY}"
      }
    }
  }
}

Usage

Once configured, you can use the validate_schema tool in Claude Code:

// Using Claude (default)
validate_schema(schemaPath: "/path/to/schema.json", rulesPath: "/path/to/rules.json")

// Using Gemini
validate_schema(schemaPath: "/path/to/schema.json", rulesPath: "/path/to/rules.json", provider: "gemini")

Example Files

The examples/ directory contains sample schemas and rule sets:

Schema Files

• schema.json - Example JSON schema

• schema.sql - Example SQL schema with tables and relationships

Rule Sets

• rules.json - Basic JSON schema validation rules

• sql-rules.json - General SQL best practices

• schema-rules.json - Database schema structure and naming conventions (inspired by Bytebase)

• migration-rules.json - Database migration safety and compatibility rules (inspired by Bytebase)

Rule Categories

Schema Rules focus on:

• Naming conventions (tables, columns, indexes)

• Table structure requirements (primary keys, constraints)

• Column definitions (types, defaults, nullability)

• Index optimization

• Documentation (comments)

Migration Rules focus on:

• Backward compatibility

• DDL safety (avoiding table locks, data loss)

• DML safety (WHERE clauses, row limits)

• Performance considerations

• Migration hygiene (separation of concerns)