Fresh Linkedin Profile Data MCP Server

Get Posts Comments

get_posts_comments

Retrieve comments on a LinkedIn post using its URN, with options for pagination and sorting by relevance or recency.

Instructions

1 credit per call.

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": {
      "urn": "<urn>"
    },
    "name": "get_posts_comments"
  }
}

Input Schema

Name	Required	Description
`urn`	Yes	Example value: 7267273010393358336
`page`	No	Example value: 1
`sort_by`	No	Default value: Most relevant. Possible values: Most relevant, Most recent.
`pagination_token`	No	Example value:

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Sep 4, 2026

TDQS

D1.6/5.0

Behavior1/5

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

No annotations are provided, so the description must carry the full behavioral disclosure burden. It says nothing about pagination, sorting, auth requirements, output structure, or side effects; the only behavioral trait mentioned is the credit cost.

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

Conciseness2/5

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

The text is extremely short, but it is under-specified rather than concise. The single sentence covers cost while omitting the actual purpose, so it does not effectively earn its place.

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

Completeness1/5

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

For a tool with 4 parameters, no output schema, and no annotations, the description is severely incomplete. An agent lacks purpose, usage context, and behavioral information needed to invoke it correctly among many similar post-related siblings.

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?

Schema description coverage is 100%, with example values and defaults for all parameters, so the schema already carries parameter semantics. The description adds no parameter meaning, but the baseline of 3 applies because the schema is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description only states '1 credit per call' and never identifies the verb or resource. The name and title imply retrieving comments on posts, but the description itself provides no purpose statement.

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?

There is no guidance on when to use this tool versus siblings like get_posts_reactions or get_post_details. Cost information does not help an agent select the correct tool, and no alternatives or exclusions are mentioned.

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

Deploy Server