LinkedIn MCP Server

by oliverhruby

Overview Schema Source Related Servers Discussions Admin

Python

Local

list_comments

Retrieves comments for a LinkedIn resource path, giving you direct access to feedback on posts and social actions.

Instructions

List comments for a resource path, e.g. /rest/socialActions/{urn}/comments.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "list_comments"
  }
}

Input Schema

Name	Required	Description	Default
`path`	Yes
`query_json`	No		{}

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 5, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It indicates a listing/read operation, but does not mention authentication requirements, pagination behavior, error conditions, or how the optional query_json affects results. This leaves meaningful behavioral gaps.

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

Conciseness4/5

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

The description is a single concise sentence with an illustrative example; there is no unnecessary verbosity. It is appropriately short, though the brevity contributes to missing semantic detail elsewhere.

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?

Even with an output schema relieving the need to describe return values, the description does not explain the optional query_json parameter or provide any context about pagination, scoping, or required setup. For a tool with two parameters and no annotations, this is not complete enough for an agent to call it correctly in varied cases.

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%, so the description must compensate. The 'path' parameter is partially explained through the example URL, but 'query_json' is completely unexplained despite having a default value. The description adds some meaning for path but not enough for safe invocation.

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 the verb ('List') and resource ('comments for a resource path'), and provides a concrete path example. It is understandable and obviously distinct from sibling tools like create_comment or list_reactions, though it does not explicitly differentiate itself from them.

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 guidance is given about when to use this tool versus alternatives, nor are any exclusions or prerequisites mentioned. The example path hints at how to construct the resource path, but there is no explicit context for choosing this tool.

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