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UniFi MCP Server

by enuno
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Python
Hybrid

list_integration_clients

List connected clients via the integration API.

Instructions

List connected clients via the integration API.

Args: site_id: Site identifier settings: Application settings limit: Maximum number of clients to return (1-1000) offset: Number of clients to skip

Returns: Paginated list of integration API clients

Input Schema

NameRequiredDescriptionDefault
limitNo
offsetNo
site_idYes
controllerNoController to run against (see list_controllers). Defaults to the controller chosen with select_controller, then the server default.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.6.0
    • addedInput schema / properties / controller
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Controller to run against (see list_controllers). Defaults to the controller chosen with select_controller, then the server default."
+}
  2. First observedv0.2.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses pagination ('Paginated list') and the limit bound (1-1000), which is useful, but says nothing about auth requirements, default page size, ordering, or the controller-selection side effects that other tools imply.

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 purpose sentence is front-loaded and the Args/Returns layout is scannable and short. However, the Args block includes a phantom 'settings' entry and duplicates schema field names, so not every line earns its place.

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

Completeness2/5

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

An output schema exists, so return values need not be explained, but for a 4-parameter list tool with no annotations the description is still thin. It omits the controller parameter entirely and misstates the parameter set, leaving real gaps an agent must close from the schema.

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 coverage is only 25%, and the description does not fully compensate. It adds the 1-1000 range for limit (absent from the schema), but lists a 'settings' argument that does not exist in the schema and omits 'controller', which does. This mismatch undermines confidence in the documented parameters.

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?

States a specific verb+resource ('List connected clients via the integration API'), so an agent can distinguish it from siblings like get_integration_client (singular) and list_integration_devices. It lacks explicit differentiation language, but the resource is unambiguous.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance is given. The description never explains how this differs from get_integration_client or when to prefer it over other list_* siblings, leaving the agent to infer usage from the name alone.

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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