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gtm-api: LinkedIn MCP Server

get_toolset_tools

Read-onlyIdempotent

List tools in a specified toolset, returning names and summaries by default or full descriptions, safety flags, and parameters in verbose mode so you can choose which tool to run.

Instructions

List the tools in a toolset. Default (lite) returns name + title + one-line summary; pass verbose:true for full descriptions, safety flags, and parameter names. Run one via call_tool.

Input Schema

NameRequiredDescriptionDefault
_metaNo
toolsetYesToolset id from list_toolsets, e.g. "linkedin.messaging".
verboseNoInclude full descriptions + parameter names.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description still adds real value by specifying that the default response is a truncated (lite) view and what verbose mode expands to include, which is behavior an agent cannot infer from annotations.

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?

Three short sentences, front-loaded with the core action, followed by the mode distinction and the handoff to call_tool. No filler and every sentence carries information.

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?

With no output schema, the description correctly takes on the burden of describing return shape for both modes, which it does well. It omits any mention of toolset size limits or pagination, a minor gap for a listing tool.

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

Parameters4/5

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

Schema coverage is 67%, so the schema covers most of the surface, and the description adds meaning beyond it: it defines the default state of verbose (false/lite) and enumerates what verbose reveals, including "safety flags" not mentioned in the schema text. The toolset parameter's origin is only implied, hence not a 5.

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 states a specific verb and resource ("List the tools in a toolset") and immediately disambiguates output modes. It also distinguishes itself from the sibling it would be confused with ("Run one via call_tool"), so an agent knows this enumerates rather than executes.

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?

It gives clear operating context: use the default lite mode for a quick scan, pass verbose:true when full descriptions/parameter names are needed, and use call_tool to actually invoke a listed tool. It does not explicitly name list_toolsets as the prerequisite for obtaining a toolset id, but the routing guidance is otherwise strong.

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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