The official developer experience MCP Server for Amazon DynamoDB. This server provides DynamoDB expert design guidance and data modeling assistance.
This server provides the following tools for AI assistants:
Global Secondary Index configurations (optional)
Retrieves the complete DynamoDB Data Modeling Expert prompt with enterprise-level design patterns, cost optimization strategies, and multi-table design philosophy. Guides through requirements gathering, access pattern analysis, and schema design.
Docker, Podman, Finch, or nerdctl with a running daemon
Generates various resources from the DynamoDB data model JSON file (dynamodb_data_model.json). Currently only the `cdk` resource type is supported. Passing `cdk` as `resource_type` parameter generates a CDK app to deploy DynamoDB tables. The CDK app reads the dynamodb_data_model.json to create tables with proper configuration.
Generates type-safe Python code from schema.json including entity classes with field validation, repository classes with CRUD operations, fully implemented access patterns, and optional usage examples. The generated code uses Pydantic for validation and boto3 for DynamoDB operations.
Java JRE version 17 or newer (set `JAVA_HOME` or ensure `java` is in your system PATH)
Validates your DynamoDB data model by loading dynamodb_data_model.json, setting up DynamoDB Local, creating tables with test data, and executing all defined access patterns. Saves detailed validation results to dynamodb_model_validation.json.
Analyzes existing MySQL databases to extract schema structure, access patterns from Performance Schema, and generates timestamped analysis files for use with dynamodb_data_modeling. Supports both RDS Data API-based access and connection-based access.
Converts your data model (dynamodb_data_model.md) into a structured schema.json file representing your DynamoDB tables, indexes, entities, fields, and access patterns. This machine-readable format is used for code generation and can be extended for other purposes like documentation generation or infrastructure provisioning. Automatically validates the schema with up to 8 iterations to ensure corre
Validates schema.json files for code generation compatibility. Checks field types, operations, GSI mappings, pattern IDs, and provides detailed error messages with fix suggestions. Ensures your schema is ready for the generate_data_access_layer tool.
Direct connection via AWS RDS Data API (MySQL only)
One or more DynamoDB table definitions with partition/sort keys
Domain models (User, Order, Product, etc.) with typed fields
string, integer, decimal, boolean, array, object, uuid
Query/Scan/GetItem operations with parameter definitions and key templates
Patterns for generating partition and sort keys (e.g., `USER#{user_id}`)
Pydantic models with field validation and type safety
CRUD operations (create, read, update, delete) for each entity
Shared functionality for all repositories
Sample code demonstrating how to use the generated classes (optional)