Fresh Linkedin Profile Data MCP Server

Search Linkedin School Pages Via Google

search_linkedin_school_pages_via_google

Find up to 100 LinkedIn school pages that match your criteria using Google search. Get school data for lead generation or audience targeting.

Instructions

Find up to 100 schools that match your criteria via Google. 2 credits per call.

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": "search_linkedin_school_pages_via_google"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Sep 4, 2026

TDQS

B3.1/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does add useful facts—a 100-school cap and a 2-credit cost and the Google-based method—but it does not describe output shape, pagination, read-only behavior, permissions, or any side effects. This is a meaningful gap for a tool with no annotation support.

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 two short sentences with no wasted words. The primary capability is front-loaded, and the cost/limit detail is separated cleanly. Every sentence earns its place.

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

Completeness2/5

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

Given the absence of both annotations and an output schema, the description is too thin. It fails to explain what 'criteria' means given an empty input schema, how results are returned, or what the agent should expect after invocation. For a tool with zero parameters, the definition is minimally functional but not complete.

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?

There are zero parameters and schema coverage is effectively complete, so the description has no parameter burden. The phrase 'match your criteria' hints at inputs that the schema does not define, but since no parameters exist, the baseline 4 applies.

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?

The description states a clear verb and resource: 'Find up to 100 schools... via Google.' It is unambiguous about the entity type and the search mechanism, and the name also reinforces the school-pages scope. However, it does not explicitly differentiate itself from direct sibling search_linkedin_company_pages_via_google, so it stops short of a 5.

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

Usage Guidelines2/5

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

No guidance is provided about when to choose this tool over the many available search tools, nor when not to use it. It implies a use case (finding schools via Google) but gives no exclusions, prerequisites, or alternative routing, leaving the agent to infer usage.

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

Deploy Server