linkedin-agent-mcp

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Get my LinkedIn profile

linkedin_get_profile

Read-onlyIdempotent

Read the signed-in user's own LinkedIn profile details—headline, about, experience, education, and skills—and flag any incomplete sections without changing account state.

Instructions

[READ - no LinkedIn state is changed] Reads the signed-in user's OWN profile (headline, about, experience, education, skills). incompleteSections lists anything that could not be read completely; treat those parts as unknown, not empty.

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_profile"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`name`	No
`about`	No
`skills`	No
`headline`	No
`location`	No
`education`	No
`experience`	No
`incompleteSections`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 2, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the '[READ - no LinkedIn state is changed]' line is partly redundant. However, the incompleteSections caveat is genuine added value: it warns the agent that partial results must be treated as unknown rather than empty, which is not derivable from the annotations.

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 tight sentences with no filler; the safety marker and scope come first, followed by the returned fields and the caveat. Every clause earns its place.

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?

With an output schema present, the description need not explain return structure, and it correctly avoids that. Scope, safety, and the partial-read caveat cover everything an agent needs to call and interpret this no-parameter read tool.

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?

The tool takes zero parameters, and the extended schemas correctly apply the baseline of 4 when there is nothing to document. The description's field list describes output rather than input, so it neither helps nor hurts here.

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?

States a specific verb (Reads) and a precisely scoped resource (the signed-in user's OWN profile), then enumerates the fields returned (headline, about, experience, education, skills). This clearly separates it from siblings like linkedin_get_company (other entities) and linkedin_prepare_profile_update (writes).

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 OWN-profile scoping and the READ marker give clear context for when this tool applies, and the sibling set makes read-vs-write intent obvious. It stops short of naming an explicit alternative or a when-not condition, so it does not reach a 5.

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