Scrapingdog MCP Server

LinkedIn Profile / Company API

linkedin_profile

Scrape public LinkedIn person or company profiles using the profile type and link ID. Get structured profile data for sales prospecting and market research.

Instructions

Scrape a public LinkedIn person or company profile by its public identifier (the slug in the profile URL).

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": {
      "type": "<type>",
      "linkId": "<linkId>"
    },
    "name": "linkedin_profile"
  }
}

Input Schema

Name	Required	Description
`type`	Yes	Profile type to scrape.
`linkId`	Yes	The public LinkedIn id/slug, e.g. 'williamhgates' for linkedin.com/in/williamhgates.
`premium`	No	Use premium mode for higher success rate. (API default: false)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Aug 1, 2026

TDQS

A3.6/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions 'public' profiles, but does not disclose rate limits, error behavior, premium mode implications, or output characteristics. This lack of detail leaves the agent without insight into expected behavior or edge cases.

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 a single, well-structured sentence that immediately conveys the essential action and target. No redundant information or unnecessary elaboration, making it maximally concise.

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

Completeness4/5

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

Given the low complexity (3 params, no output schema), the description provides sufficient context for a basic scrape operation. The schema fills in parameter details, but the lack of any annotation or output description leaves minor gaps in expected return behavior, though not critical.

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?

The schema descriptions cover all parameters (100% coverage), including the example for linkId and the purpose of premium. The description itself adds no additional meaning beyond referencing the slug, so the baseline score of 3 is appropriate.

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's action ('Scrape'), target ('public LinkedIn person or company profile'), and identification method ('by its public identifier'). It effectively distinguishes from sibling tools by specifying LinkedIn, unlike general web scraping or other social profile tools.

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

Usage Guidelines3/5

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

The description implies use for LinkedIn profile/company scraping via the given slug, but it does not explicitly compare with alternatives like x_profile or web_scrape. No exclusions or 'when not to use' guidance is provided, making the usage context only implicit.

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