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kaistenberg

MCP Server for LinkedIn

by kaistenberg

Get Sidebar Profiles

get_sidebar_profiles
Read-only

Get profile links from LinkedIn sidebar sections like 'People you may know' and 'More profiles for you'. Follows 'Show all' to return full lists, skipping premium redirects.

Instructions

Get profile links from sidebar recommendation sections on a LinkedIn profile page.

Extracts profiles from "More profiles for you", "Explore premium profiles", and "People you may know" sidebar sections. Follows "Show all" links to return the full list from each section. Sections that redirect to linkedin.com/premium are skipped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linkedin_usernameYesLinkedIn username of the profile page to scrape (e.g., "stickerdaniel", "williamhgates")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations declare readOnlyHint and openWorldHint; description adds concrete behaviors: following 'Show all' links to return full lists, and skipping sections that redirect to linkedin.com/premium. No contradiction.

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-sentence description is front-loaded with purpose and includes only relevant behavioral details (section names, Show all behavior, premium skip). 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 simple one-parameter read tool with output schema, the description covers what, where, and edge-case behavior (premium redirects), making it self-sufficient.

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% and the lone parameter linkedin_username is clearly described in the schema. Description adds no additional parameter semantics.

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?

Description uses specific verb 'Get profile links' and names exact sections ('More profiles for you', 'Explore premium profiles', 'People you may know'), clearly distinguishing it from sibling tools like get_person_profile or search_people.

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 clearly states the context: scraping sidebar recommendation sections from a LinkedIn profile page. It does not explicitly list when not to use or name alternative tools, but context is unambiguous.

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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