Fresh Linkedin Profile Data MCP Server

Search Linkedin Company Pages Via Google

search_linkedin_company_pages_via_google

Find up to 100 LinkedIn company pages by searching Google. Use this to locate company profile URLs for prospecting or lead research.

Instructions

Find up to 100 companies 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_company_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

C2.4/5.0

Behavior2/5

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

No annotations are present, so the description carries the full burden. It transparently discloses the credit cost and result cap, but it fails to explain the absence of parameters, what 'criteria' actually means, or what the response contains. This leaves significant behavioral ambiguity.

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?

The description is a single efficient sentence that front-loads the core purpose, limit, and cost. It earns its place, but its brevity leaves out crucial details; still, it is not bloated.

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?

For a tool with no output schema, no annotations, and a large family of closely related search tools, the description is incomplete. It does not explain how to invoke it, what criteria are, what result shape to expect, or how it differs from siblings beyond 'via Google'.

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

Parameters2/5

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

With zero parameters, the baseline would normally be 4, but the description introduces a 'criteria' concept that maps to no schema field. This contradiction actively confuses rather than adds meaning, so the parameter-related semantics are poor.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific action and source ('Find up to 100 companies ... via Google') and includes a limit, so an agent knows the basic purpose. However, 'matches your criteria' is undefined because the input schema exposes zero parameters, making the scope vague and potentially misleading.

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?

There is no guidance on when to use this tool versus sibling alternatives like search_companies or search_companies_instantly. The only differentiator is 'via Google', but no usage context, exclusions, or alternative routes are provided.

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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