Skip to main content
Glama
2060-io

linkedin-mcp

by 2060-io

create_image_post

Publish a LinkedIn post with a single image. Provide the image as a URN or base64 data.

Instructions

Publish a post with a single image. Provide image_urn (from upload_media) or image_data (base64).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
image_urnNo
image_dataNo
alt_textNo
visibilityNo
Behavior2/5

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

No annotations are provided, so the description bears full responsibility. It only states the basic action and parameter options. It fails to disclose key behaviors such as what happens if both image_urn and image_data are provided, size limits, default visibility, or the outcome (e.g., post creation and return value).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise at one sentence, which is good for readability. However, it sacrifices necessary detail, making it feel under-specified. It front-loads the purpose but lacks depth on parameters and behavior.

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

Completeness2/5

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

With 5 parameters, 1 required, no output schema, and no annotations, the description is incomplete. It does not cover the text parameter, what alt_text is for, visibility options, or what the tool returns. Significant gaps exist for an agent to use it correctly.

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 coverage is 0%, so the description must compensate. It only briefly mentions image_urn and image_data, but does not explain their relationship, when to choose one, or describe other parameters like text, alt_text, or visibility. The meaning and usage of the parameters remain largely unexplained.

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 clearly states it publishes a post with a single image, using a specific verb and resource. The word 'single' distinguishes it from sibling tools like create_multi_image_post, and it references upload_media for image_urn, making purpose unambiguous.

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 provides context on when to use image_urn vs image_data, and implies this tool is for single image posts. However, it does not explicitly list alternatives or state when not to use this tool, but the 'single image' qualifier effectively differentiates from siblings.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/2060-io/linkedin-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server