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LinkedIn MCP Server

LinkedIn MCP Server

by Sabari2005
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

linkedin_update_location

Update your LinkedIn profile location by entering a recognizable city or region, automatically matched to LinkedIn's official list.

Instructions

Update the profile location. LinkedIn requires a location from its own list, so the value is matched against its typeahead — use a recognisable city or region name.

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": {
      "location": "<location>"
    },
    "name": "linkedin_update_location"
  }
}

Input Schema

NameRequiredDescriptionDefault
locationYesCity or region, e.g. "Berlin, Germany" or "London, England".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.6

TDQS

A4.5/5.0
Behavior4/5

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

The description adds behavioral detail about typeahead matching beyond the annotations, explaining how the value is processed, though it does not cover failure modes.

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?

Two concise sentences, front-loaded with the action, no filler.

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

Completeness5/5

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

For a single-parameter update tool with annotations and full schema coverage, the description provides sufficient context 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.

Parameters4/5

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

Schema already documents the parameter with examples; the description adds the matching-semantics nuance, which is useful beyond the schema.

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 tool updates the profile location with a specific verb and resource, distinguishing it from sibling tools like linkedin_add_experience or linkedin_update_about.

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?

It provides usage context by explaining LinkedIn's typeahead requirement and advising on recognisable city/region names, but it does not explicitly name alternatives or exclusions.

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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