linkdapi-the-best-linkedin-professional-data-api

Get Company Insights

get_api_v1_companies_company_insights

Get company Insights (This endpoint consumes 3 credits per request and is available exclusively to users on a paid plans.) Group: Companies. Billing per call: 1 Credits.

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": "get_api_v1_companies_company_insights"
  }
}

Input Schema

Name	Required	Description	Default
`id`	No	company ID

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 19, 2026

TDQS

C2.8/5.0

Behavior2/5

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

With no annotations, the description carries the full transparency burden. It discloses paid-plan exclusivity and credit cost, but the credit amount is internally inconsistent (3 credits vs. 1 credit), and it omits return behavior or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short, but it includes redundant and contradictory billing information plus a low-value 'Group: Companies' line. It is somewhat concise but not every detail 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?

The tool has no output schema, no annotations, and a single parameter, yet the description still provides minimal context about what the response contains or why 'insights' differs from other company endpoints. Credit and paid-plan info helps, but the overall picture is incomplete.

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 description coverage is 100%, so the schema already explains the only parameter, 'id'. The description adds no additional semantic detail about how the ID is used or what values are valid.

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 clearly states the tool returns company insights, using a specific verb and resource. However, it does not differentiate what 'insights' includes compared to sibling company tools like company_info or company_employees_data.

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 given on when to use this tool versus alternative company endpoints. The credit cost and paid-plan restriction are mentioned, but these are access constraints, not usage direction.

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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