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awslabs

Threat Modeling MCP Server

Official
by awslabs

export_comprehensive_threat_model

Export a complete threat model with all global variables, including business context, architecture, threats, and mitigations, to Threat Composer JSON format.

Instructions

Export comprehensive threat model with all global variables to Threat Composer JSON format.

This tool exports the complete threat model including all global variables from all phases of the threat modeling process. It collects business context, assumptions, architecture, threat actors, trust boundaries, asset flows, threats, mitigations, and phase progress.

Args: ctx: MCP context for logging and error handling output_path: Path to save the exported threat model (will be saved in .threatmodel directory) include_extended_data: Whether to include extended data beyond standard Threat Composer format

Returns: A comprehensive export summary with details about what was exported

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_pathYes
include_extended_dataNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the side effect of saving to a .threatmodel directory and enumerates the content collected. However, it doesn't mention file overwrite behavior, directory creation, or whether the operation is destructive, which are relevant for a filesystem-writing tool.

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

Conciseness4/5

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

The description is well-structured with a clear top-line purpose, a bulleted list of included items, and an Args section. It's efficient, though the Args section partly restates the schema, adding modest value.

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?

For a comprehensive export tool with an output schema, the description covers the main scope, output location, and return summary. It could mention error conditions or exact return format, but the output schema likely fills that gap.

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 0%, so the description compensates. It explains output_path saves in .threatmodel directory and include_extended_data controls extended data beyond standard format, adding some meaning. But it doesn't detail what extended data includes or how the path is resolved.

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 clearly states the tool exports a comprehensive threat model to Threat Composer JSON format, with a specific verb (export), resource (threat model), and distinguishing qualifier (comprehensive, all global variables). This differentiates it from sibling export tools like export_threat_model_with_remediation_status.

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 implies when to use this tool: when a complete threat model with all global variables is needed, as it collects every phase's data. It doesn't explicitly mention alternatives, but the 'comprehensive' scope provides clear context for selection.

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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