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N-Graves

linkedin-mcp-server

by N-Graves

linkedin_create_post

Publish a LinkedIn post with optional image and visibility settings. Uploads and confirms images first, then posts live immediately since no draft state exists.

Instructions

Publish to LinkedIn. ⚠️ There is NO draft state — LinkedIn's Posts API has no unpublished lifecycle to fall back on, so this goes live the moment it succeeds. Any human approval has to happen BEFORE this is called, never after.

An image is uploaded and confirmed first, so a picture LinkedIn rejects fails before anything is published — a LinkedIn post cannot be edited afterwards to add media.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesPost commentary. LinkedIn's limit is 3000 characters.
image_pathNoLocal .png/.jpg/.gif to attach. Uploaded before the post is created.
visibilityNoPUBLIC
image_alt_textNo

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses irreversibility (no draft state, goes live on success), approval ordering, image upload/validation before publish, and that media cannot be added later via edit. This is high-value behavioral context beyond the schema.

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?

Three sentences, front-loaded with the core action, followed by two dense warnings that each earn their place. No filler or repetition of schema details.

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

Completeness4/5

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

The critical context for a publish operation is covered: no draft, approval before, image failure behavior, and post-edit limitation. The only gap is that the return value/output is not described, which matters given there is no output schema.

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 already documents text and image_path, and the description adds useful behavioral semantics for image_path (uploaded and confirmed first, cannot add media later). However, visibility and image_alt_text are left to inference despite 50% schema coverage, and the description doesn't explain their role.

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 opening phrase 'Publish to LinkedIn' names a specific verb and resource, making the operation unambiguous. It is clearly distinct from siblings linkedin_get_me (read), linkedin_delete_post (destructive), and linkedin_call (raw API).

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 explicit workflow guidance: approval must happen before the call because there is no draft lifecycle, and the post goes live immediately. It doesn't explicitly contrast with sibling tools, but the context is strong enough for an agent to know when this tool is appropriate.

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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