Validates and tests DynamoDB data models against DynamoDB Local. Use this tool to validate, test, and verify your DynamoDB data model after completing the design phase. This tool automatically checks that all access patterns work correctly by executing them against a local DynamoDB instance. WH...
Part of the AWS DynamoDB MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call dynamodb_data_model_validation to retrieve information from AWS DynamoDB MCP Server without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though dynamodb_data_model_validation only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
tools:
dynamodb_data_model_validation:
rules:
- action: allowSee the full AWS DynamoDB MCP Server policy for all 8 tools.
Agents calling read-class tools like dynamodb_data_model_validation have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
Validates and tests DynamoDB data models against DynamoDB Local. Use this tool to validate, test, and verify your DynamoDB data model after completing the design phase. This tool automatically checks that all access patterns work correctly by executing them against a local DynamoDB instance. WHEN TO USE: - After completing data model design with dynamodb_data_modeling tool - When user asks to "validate", "test", "check", or "verify" their DynamoDB data model - To ensure all access patterns execute correctly before deploying to production WHAT IT DOES: 1. If dynamodb_data_model.json doesn't exist: - Returns complete JSON generation guide from json_generation_guide.md - Follow the guide to create the JSON file with tables, items, and access_patterns - Call this tool again after creating the JSON to validate 2. If dynamodb_data_model.json exists: - Validates the JSON structure (checks for required keys: tables, items, access_patterns) - Sets up DynamoDB Local environment (Docker/Podman/Finch/nerdctl or Java fallback) - Cleans up existing tables from previous validation runs - Creates tables and inserts test data from your model specification - Tests all defined access patterns by executing their AWS CLI implementations - Saves detailed validation results to dynamodb_model_validation.json - Transforms results to markdown format for comprehensive review WHAT TO DO ON SUCCESSFUL COMPLETION: After validation completes, you MUST present the user with TWO options: 1. Deploy to AWS: Call `generate_resources` tool with resource_type='cdk' to create a CDK app for provisioning tables 2. Generate Python code: Call `dynamodb_data_model_schema_converter` to convert the model to schema.json, then generate code The user can choose one or both options. If they choose CDK first, you can still generate Python code afterward. Args: workspace_dir: Absolute path of the workspace directory Returns: JSON generation guide (if file missing) or validation results with transformation prompt (if file exists). It is categorised as a Read tool in the AWS DynamoDB MCP Server MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for dynamodb_data_model_validation. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the AWS DynamoDB MCP Server MCP server.
dynamodb_data_model_validation is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the dynamodb_data_model_validation rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the Intercept policy for dynamodb_data_model_validation. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
dynamodb_data_model_validation is provided by the AWS DynamoDB MCP Server MCP server (awslabs.dynamodb-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.