LinkedIn MCP

linkedin_prepare_post

Validate and prepare a LinkedIn post for review before publishing, including optional visibility settings, without publishing it.

Instructions

Validate and prepare a post for review; does not publish it.

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": {
      "text": "<text>"
    },
    "name": "linkedin_prepare_post"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes
`visibility`	No		PUBLIC

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 29, 2026

TDQS

B3.2/5.0

Behavior3/5

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

With no annotations, the description carries the full burden, and its one valuable disclosure is that the call is non-publishing — a real safety-relevant fact. It says nothing about what validation rules apply, what happens when validation fails, what state the post is left in for review, or whether it is idempotent, all of which matter for a mutation-adjacent tool.

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?

A single front-loaded sentence with no filler; the non-publishing constraint is placed where it will be read. It is efficient but borders on under-specified given the zero schema coverage.

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?

An output schema exists, so return values need not be explained. However, for a tool with no annotations and 0% parameter coverage, the description should say more about validation outcomes and the review state; the missing parameter context is the main gap.

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% and the description never mentions either parameter. The 'text' parameter is obvious from its name, but 'visibility' is an unconstrained string defaulting to PUBLIC with no enum, and the description gives no guidance on accepted values or that PUBLIC is the default.

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?

States a specific verb and resource ('Validate and prepare a post for review') and explicitly negates publishing, which cleanly separates it from the sibling linkedin_publish_approved_post. It does not name that sibling directly, but the negation is enough for an agent to tell the two apart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

'Does not publish it' implies this is the first step in a draft-then-publish workflow, but the description never says when to call this versus linkedin_publish_approved_post, nor what prerequisites (auth, existing draft) must hold. Usage is inferable rather than stated.

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

Deploy Server