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Mipiti

Mipiti MCP Server

by Mipiti
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Python
Hybrid

List Groups

list_groups

Retrieve all tags in the workspace, including IDs, names, descriptions, and model IDs, to discover tag identifiers for risk, compliance, dependency, export, or membership operations.

Instructions

List the workspace's tags. Read-only; no side effects.

A tag is a named, overlapping grouping of threat models, for audit scopes, products, ad-hoc selections or portfolios. A model may carry many tags, and a tag never affects posture or credit. Returns {"tags": [...]}, each with id, name, description and model_ids.

Discover tag IDs here before the tag risk, compliance, dependency or export tools, or before adding/removing members. For a single model's tags use list_model_groups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.85.0
    • removedInput schema / properties / kind
      Removed value: -{
-  "description": "``\"tag\"`` or ``\"system\"``.",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "server_version",
-  "kind"
-]New value: +[
+  "server_version"
+]
  2. Addedv0.68.2

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden, and it does disclose that the call is read-only with no side effects and that a tag never affects posture or credit. It also describes the return payload shape. It does not cover auth requirements or pagination, so it stops short of full transparency.

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?

Front-loads the action and read-only trait, then adds tag semantics, return shape and routing. Every sentence adds value with no padding.

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?

Tag semantics, safety profile, return shape and sibling routing are all covered, and an output schema exists so return-value detail is not strictly required. The one gap is the undocumented required server_version parameter.

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

Parameters2/5

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

Schema description coverage is 0% for the single required parameter server_version, and the description never mentions it or its format/expected value. With an undocumented required parameter, the description does not compensate for the coverage gap.

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 ('List the workspace's tags') and immediately distinguishes itself from the sibling list_model_groups by scoping. An agent can tell it apart from the tag-risk/export tools without opening a schema.

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

Usage Guidelines5/5

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

Explicitly routes the agent: discover tag IDs here before the risk, compliance, dependency or export tools, or before add/remove membership; and it names the alternative (list_model_groups) for a single model's tags. When-to-use and alternative are both stated.

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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