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awslabs

Threat Modeling MCP Server

Official
by awslabs

add_data_store

Add data stores to your threat model architecture, individually or in batch, with classification, encryption, and backup settings.

Instructions

Add a new data store to the architecture. Supports batch operations via the 'items' parameter.

This tool adds one or more data stores to the system architecture. For single item: provide name, type, classification, and optional fields directly. For batch: provide a list of data store dicts in the 'items' parameter.

Args: ctx: MCP context for logging and error handling name: Name of the data store (required for single item mode) type: Type of the data store (required for single item mode) classification: Classification of the data (required for single item mode) encryption_at_rest: Whether the data is encrypted at rest backup_frequency: Frequency of backups (e.g., 'Hourly', 'Daily', 'Weekly') description: Description of the data store items: Optional list of data store dicts for batch operation

Returns: A confirmation message with the data store ID(s)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoName of the data store (required for single item mode)
typeNoType of the data store (e.g., 'Relational', 'NoSQL', 'Object Storage') (required for single item mode)
itemsNoOptional list of data stores to add in batch. Each dict should contain 'name', 'type', 'classification', and optionally 'encryption_at_rest', 'backup_frequency', 'description'. When provided, individual parameters are ignored.
descriptionNoDescription of the data store
classificationNoClassification of the data (e.g., 'Public', 'Internal', 'Confidential') (required for single item mode)
backup_frequencyNoFrequency of backups (e.g., 'Hourly', 'Daily', 'Weekly')
encryption_at_restNoWhether the data is encrypted at rest

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses the batch behavior (adding one or more data stores) and the return format (confirmation with ID(s)). It also notes that the 'items' parameter enables batch operation, which is useful beyond the schema. It does not detail edge cases like duplicate name handling, but for a create operation it is reasonably transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary, mode explanations, an args list, and a returns line. However, the Args list largely repeats the schema descriptions, making it longer than necessary. It is not overly verbose, but the redundancy prevents a higher score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 7 parameters, a batch mode, and an output schema. The description explains the two modes, the required fields for single-item mode, the batch structure, and the return value. It is sufficiently complete for effective use, though it could mention possible error conditions, but the output schema likely covers return details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds some context by distinguishing single-item parameters from the batch 'items' parameter and mentioning the 'ctx' parameter (not in schema), but most of the Args section duplicates schema descriptions. The added value over the schema is marginal.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Add a new data store to the architecture' and clarifies it also supports batch operations via the 'items' parameter. This clearly distinguishes it from sibling tools like update_data_store and delete_data_store, and from add_component/add_connection which target other architecture elements.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use single-item mode versus batch mode, with explicit instructions for each. It does not explicitly name alternatives or exclusion criteria (e.g., when to use update_data_store instead), but the usage context is well-defined and unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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