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LinkMCP: hosted LinkedIn MCP server

Create Post

linkedin_create_post

Create a LinkedIn post. Supports text with line breaks, image attachments (via public URLs), @mentions, link preview cards, and reposting existing posts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesPost content (max 3000 characters). Use \n for line breaks. Use {{0}}, {{1}} etc. to insert mentions from the mentions array.
repostNoOptional social_id of an existing LinkedIn post to share/repost. For a simple repost without commentary, text can be empty.
mentionsNoOptional mentions array. Reference in text as {{0}}, {{1}} etc.
image_urlsNoOptional array of publicly accessible image URLs (JPEG, PNG, GIF, max 5MB each, max 20). The server will fetch and attach them to the post.
content_checkNoControls LLM content artifact detection (default: "strict"). "strict" rejects text containing Unicode dashes (— – −) and other LLM artifacts. "autofix" automatically replaces em dashes with short dashes. "disabled" skips all content checks.
external_linkNoOptional URL for a link preview card. Must also appear in the post text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare the mutation profile (readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false), lowering the bar. The description adds capability context (server-side image fetching from public URLs, reposting) but never states that the post goes live immediately, that it cannot be undone through this tool, or whether credentials/scopes are required.

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?

Two tight sentences with the core action front-loaded and a compact capability list following. No filler or repetition, though it stops short of the kind of routing information that would make the brevity maximally valuable.

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?

For a mutation tool with no output schema, the definition omits what a successful call returns (e.g., the created post's id/URL) and what failure modes look like, which matters for follow-up calls. Annotations and the rich schema cover safety and inputs, so the gap is moderate rather than severe.

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 100%, and the schema documents every parameter in more detail than the description (character limits, mention placeholder syntax, content_check enum behavior, link card requirement). The description only broadly restates those capabilities, so the baseline 3 applies.

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 and resource ('Create a LinkedIn post') and enumerates the supported content types (text, images, mentions, link cards, reposts). It does not, however, contrast itself against the closest write sibling (linkedin_comment_on_post) or clarify it is for publishing new top-level posts rather than replies.

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?

No when-to-use or when-not-to-use guidance is given; the sentence describes capabilities, not selection criteria. Nothing tells the agent why it would pick this over linkedin_comment_on_post or how reposting relates to reading existing posts via linkedin_get_person_posts.

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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