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linkedin-mcp

linkedin-mcp

by 2060-io
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

upload_media

Accepts a base64-encoded image and returns its image URN for use in creating image posts or multi-image posts.

Instructions

Upload an image (base64) and return its image URN for use in create_image_post / create_multi_image_post.

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": {
      "image_data": "<image_data>"
    },
    "name": "upload_media"
  }
}

Input Schema

NameRequiredDescriptionDefault
image_dataYesBase64-encoded image bytes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, and the description only mentions returning a URN. It does not disclose any behavioral traits such as storage, limits, side effects, or error conditions, leaving significant gaps for an upload action.

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?

The description is a single sentence, front-loaded with the action and purpose, with no wasted words. It is extremely concise and structured effectively.

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?

Given no output schema, the description mentions 'return its image URN' but does not specify the response format (e.g., plain string or object). It also omits error conditions and limitations. Adequate for a simple tool but with gaps.

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 coverage is 100% with the parameter 'image_data' described as 'Base64-encoded image bytes.' The description adds a little by tying it to image URN, but does not provide additional format or validation details.

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 the action 'upload an image (base64)' and the output 'return its image URN', with explicit mention of sibling tools where it is used, distinguishing it from them.

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 indicates usage context by naming create_image_post and create_multi_image_post as consumers of the output, but does not explicitly state when not to use or mention alternatives.

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

Deploy Server

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