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LinkedIn MCP

LinkedIn MCP

by rohankumbhar-01
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

linkedin_get_my_profile

Retrieve the signed-in member's basic LinkedIn profile fields via OpenID, provided the app has the required permissions.

Instructions

Read the signed-in member's basic OpenID profile fields, if the app has the required permissions.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "linkedin_get_my_profile"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It does disclose that this is a read of a limited 'basic OpenID' field set gated on app permissions, but adds nothing about failure behavior when permissions are missing, token requirements, or scope details.

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?

One sentence, front-loaded with the action and resource, and no filler. It is arguably a bit too terse for a tool with an auth prerequisite.

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?

An output schema exists so return values need not be described, but the auth/permission prerequisite and the relationship to the OAuth sibling tools go unstated, leaving a gap an agent could trip on.

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

Parameters4/5

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

Zero parameters, so the baseline applies; there is nothing parameter-wise for the description to compensate for.

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?

States a specific verb+resource: read the signed-in member's basic OpenID profile fields. That clearly separates it from siblings like linkedin_get_my_posts or linkedin_connection_status, though it doesn't name the boundary explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied (fetch the current user's identity), and the permission caveat hints at a prerequisite, but it never says when to prefer this over sibling calls or that OAuth (linkedin_start_oauth / linkedin_exchange_code) must complete first.

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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