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Mipiti MCP Server

by Mipiti
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Python
Hybrid

List Threat Models

list_threat_models

List threat models in the workspace, filterable by source, to discover model IDs for other tools or review the portfolio. Include assessment summaries to identify at-risk models.

Instructions

List saved threat models in the current workspace.

Read-only; no side effects. Returns {items: [{id, title, version, created_at, ...}], count}. Use this to discover model IDs to pass to other tools, or for a portfolio overview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoFilter by the system that created each model. One of "web", "mcp", "jira", "api". Omit (default "") to list all models regardless of source.
server_versionYes
include_assessment_summaryNoIf True, include an `assessment_summary` object per model (counts of mitigated / at_risk / unassessed control objectives plus a human-readable `message`). Use for aggregate posture queries across the workspace in a single call (e.g. "which of my models are at risk?") instead of calling `assess_model` once per model. Adds roughly 100 bytes per model. Default False.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.66.0
    • changedInput schema / properties / include_assessment_summary / description
      Previous value: -"If True, include an `assessment_summary`\nobject with each model (counts of mitigated / at_risk /\nunassessed COs plus a human-readable `message`). Useful for\naggregate posture queries across the workspace in a single\ncall — e.g. \"which of my models are at risk?\" — instead of\ncalling `assess_model` once per model (N+1 at the agent layer).\nAdds ~100 bytes per model to the response."New value: +"If True, include an `assessment_summary` object per model (counts of mitigated / at_risk / unassessed control objectives plus a human-readable `message`). Use for aggregate posture queries across the workspace in a single call (e.g. \"which of my models are at risk?\") instead of calling `assess_model` once per model. Adds roughly 100 bytes per model. Default False."
    • changedInput schema / properties / source / description
      Previous value: -"Filter by source system. One of \"web\", \"mcp\", \"jira\", \"api\".\nOmit to list all models regardless of source."New value: +"Filter by the system that created each model. One of \"web\", \"mcp\", \"jira\", \"api\". Omit (default \"\") to list all models regardless of source."
  2. First observedv0.57.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations present, the description must carry the burden of behavioral disclosure. It explicitly states 'Read-only; no side effects' and describes the return shape as {items: [{id, title, version, created_at, ...}], count}. This is strong transparency for a list operation, though it does not mention pagination, authentication, or rate limits.

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

Conciseness5/5

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

The description is two sentences with no wasted words. It front-loads the action and resource, then states side-effect behavior, return shape, and intended use in a compact, scannable way.

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 description is largely complete for a read-only list tool: it covers purpose, side-effect profile, return shape, and primary use cases. The main missing context is an explicit note about the required server_version parameter and guidance distinguishing this from get_threat_model for detailed model retrieval.

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 67%, covering source and include_assessment_summary, but the required server_version parameter has no description. The main description adds no extra parameter-level meaning beyond the schema, so the undocumented required parameter remains a gap.

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

Purpose4/5

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

The description clearly states it lists saved threat models in the current workspace, with a specific verb and resource. It does not explicitly differentiate itself from related siblings like get_threat_model or query_threat_model, but the term 'list' plus the focus on model IDs and portfolio overview make the core purpose unambiguous.

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 gives concrete use cases: discovering model IDs to pass to other tools and portfolio overview. It does not explicitly say when to prefer alternatives such as get_threat_model or query_threat_model, but the use cases are helpful enough to orient an agent.

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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