LinkedIn MCP

linkedin_get_post

Retrieve a specific LinkedIn post by its URN when authorized. Use this to fetch post content for analysis or display.

Instructions

Retrieve a specific post by its LinkedIn URN, if the app has permission.

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": {
      "post_urn": "<post_urn>"
    },
    "name": "linkedin_get_post"
  }
}

Input Schema

Name	Required	Description	Default
`post_urn`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 29, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations, the description carries the full burden. It mentions a permission condition but does not disclose that this is a read-only operation, what happens if permission is missing, or any rate limits or error behavior. The output schema covers return values, but behavioral context is sparse.

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, front-loaded sentence that efficiently conveys the core action and a key constraint. It is appropriately sized for a simple tool with one parameter.

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 low-complexity and has an output schema, so return values need not be explained. The description covers the permission prerequisite but omits usage differentiation from siblings and deeper behavioral details, making it minimally adequate but not fully complete.

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 0%, so the description must compensate. It does explain that the lone parameter is a 'LinkedIn URN,' adding meaning beyond the schema's bare 'string' type, but it does not specify URN format or examples. This partially compensates but leaves a gap.

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 states a specific verb ('Retrieve') and resource ('a specific post by its LinkedIn URN'), making the core action clear. It does not explicitly differentiate from the sibling tool linkedin_get_my_posts, which also retrieves posts, so a 4 rather than 5.

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?

The only guidance is the conditional 'if the app has permission,' which is a prerequisite rather than a when-to-use directive. There is no mention of when to choose this over linkedin_get_my_posts or other alternatives.

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

Deploy Server