Skip to main content
Glama
vlpmedialtd

linkedin-mcp

by vlpmedialtd

Get a LinkedIn post

linkedin_get_post
Read-only

Fetch a single LinkedIn post by its URN to access post content and metadata. Use this action to retrieve a specific post using its unique identifier.

Instructions

Fetches a single post by URN. Reading member posts requires the r_member_social permission (restricted); organization posts require r_organization_social.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_urnYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description adds critical context about required OAuth permissions (r_member_social vs r_organization_social) that is not in the annotations. This directly helps an agent anticipate authorization failures. No contradiction with 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?

Two sentences with zero fluff. The primary purpose is front-loaded in the first sentence, and the permission note is a concise, relevant addition. Every word earns its place.

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

Completeness3/5

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

The tool is simple (one param, read-only) and annotations cover safety. The description covers permissions, which is a key operational detail. However, the lack of output-format description and the weak parameter explanation (see parameter_semantics) leave minor gaps. Still, for a basic fetch, it is largely adequate.

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 for the post_urn parameter. It only repeats the phrase 'by URN', which adds no meaning beyond the parameter name itself. It does not explain what a URN looks like, how to obtain one, or any format nuances beyond the schema pattern. This is a significant 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?

The description states a specific verb ('Fetches') and resource ('a single post') and specifies the key discriminator (by URN). This clearly differentiates from sibling tools like linkedin_list_posts and linkedin_get_post_stats, and the intent 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 Guidelines4/5

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

The description gives clear context: use this when you have a post URN and need that specific post. It also notes permission prerequisites, which are important usage constraints. However, it does not explicitly exclude alternatives (e.g., 'use list_posts to find URNs') or state when not to use it, so it stops short of a 5.

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