Skip to main content
Glama
Mipiti

Mipiti MCP Server

by Mipiti
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

List Effective Entities

list_effective_entities

Get the full effective entity set for a threat model after ancestor composition, with provenance and qualified IDs for every trust boundary, component, asset, and attacker.

Instructions

Effective entity set (own ⊕ inherited) keyed by kind.

Returns the entity set this model sees after composition with ancestors: trust boundaries, components, assets, attackers, and (when applicable) attack paths. Each entry carries its provenance — whether it originates on this model or is inherited from an ancestor — plus a fully-qualified id so cross-model references are unambiguous.

Pair with list_effective_control_objectives and get_effective_coverage to see how inherited topology contributes to coverage credit.

Return shape::

{
  model_id, flag_enabled,
  kinds: {
    trust_boundaries: [{kind, qualified_id, owner_model_id,
      owner_title, origin, entity}, ...],
    components: [...], assets: [...], attackers: [...], ...
  },
  total, page, page_size,
}

When composition is disabled on the backend, kinds is returned with every kind mapped to an empty list and flag_enabled: false.

Omitting page / page_size defaults to page=1, page_size=100 — the response is paginated and no longer returns every entity in a single call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNooptional single entity kind to restrict the response to (e.g. ``"attackers"``, ``"assets"``, ``"components"``, ``"trust_boundaries"``). When omitted, all kinds are returned.
pageNo1-indexed page number (default ``1``).
model_idYesID of the threat model.
page_sizeNoentries per page (default ``100``).
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.57.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it delivers: it explains composition semantics, provenance, qualified ids, pagination defaults, and the exact behavior when composition is disabled (empty kinds and flag_enabled: false). The note that pagination means the response no longer returns every entity in a single call is especially valuable.

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 dense and well-structured, front-loading the core result, then providing a concrete return shape, a special-case behavior, and practical pairing guidance. Every section earns its place and the code block improves scannability.

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

Completeness5/5

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

The description is complete for an agent to invoke the tool correctly: it names all required context (model's effective set after composition), documents pagination defaults, describes the response shape, and explains the disabled-composition edge case. The presence of an output schema further reduces the need to explain return values, but the description still adds valuable semantic context.

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?

The input schema already documents kind, page, model_id, and page_size with defaults and descriptions, so the baseline applies. The description adds no significant parameter explanation beyond the schema, aside from confirming pagination behavior which the schema also covers via defaults.

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?

States a specific verb and resource: it returns the effective entity set after composition with ancestors, keyed by kind and including provenance and qualified ids. It clearly distinguishes itself from related sibling tools like list_effective_control_objectives and get_effective_coverage by describing exactly what entity data it provides.

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?

Provides clear context for when to use the tool: to retrieve the effective entity set with provenance and fully-qualified ids, and explicitly suggests pairing it with list_effective_control_objectives and get_effective_coverage for coverage analysis. It does not explicitly state when not to use it or mention alternatives like list_effective_attack_paths, but the usage intent is clear.

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

Deploy Server

Other Tools