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EgiStr

linkedin-mcp

by EgiStr

Create a LinkedIn Post

linkedin_create_post

Publish a text post to your LinkedIn feed with chosen visibility (public, connections only, or logged-in), returning post ID, URN, status, and direct URL.

Instructions

Create and publish a new LinkedIn post.

Publishes a text post to your LinkedIn feed. Supports PUBLIC, CONNECTIONS-only, or LOGGED_IN visibility settings.

Args:

  • text (string, required): Post content (1-3000 chars)

  • visibility ("PUBLIC" | "CONNECTIONS" | "LOGGED_IN"): Who can see the post (default: "PUBLIC")

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns (JSON format): { "postId": string, // Post ID "urn": string, // LinkedIn URN "text": string, // Text preview (first 100 chars) "visibility": string, // Visibility setting used "status": string, // Always "PUBLISHED" "url": string // Direct link to the post }

Requires scope: w_member_social (Share on LinkedIn product)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already show this is a write and non-idempotent operation. The description adds meaningful behavioral context: it requires the w_member_social scope, always returns status 'PUBLISHED', and creates a publicly visible or restricted feed post. It does not mention rate limits or reversibility, but it does not contradict the annotations.

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 well structured with a one-line summary, Args, Returns, and a scope requirement. There is mild redundancy between the first sentence and the title, but the content is relevant and front-loaded.

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

Completeness5/5

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

Given that the schema declares no parameters and there is no output schema, the description is remarkably complete: purpose, parameters, defaults, visibility enum, return fields, and auth scop e are all present. An agent can call this tool and interpret the response without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is empty, so the description carries the full burden of parameter documentation. It defines text as required with a 1-3000 character constraint, provides the visibility enum with a default, and documents response_format with a default. This is complete and actionable for an agent.

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 and resource: 'Create and publish a new LinkedIn post.' It further clarifies that it publishes a text post to the user's feed and supports distinct visibility modes, making it easy to distinguish from siblings like linkedin_send_message or linkedin_delete_post.

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 for when to use the tool: publishing a text post to the LinkedIn feed with PUBLIC, CONNECTIONS, or LOGGED_IN visibility. It does not explicitly name alternative tools or state when not to use it, so it stops short of full routing guidance, but the intended use case is unambiguous.

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

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