Fresh Linkedin Profile Data MCP Server

Get Companys Posts

get_companys_posts

Retrieve LinkedIn posts published by a given company from its profile URL. Supports pagination via tokens and sorting by top or recent to browse full post history.

Instructions

2 credits per call.

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": {
      "linkedin_url": "<linkedin_url>"
    },
    "name": "get_companys_posts"
  }
}

Input Schema

Name	Required	Description	Default
`start`	No	Use this param to fetch posts of the next result page: 0 for page 1, 50 for page 2, etc.	0
`sort_by`	No	Possible values: top, recent
`linkedin_url`	Yes	Example value: https://www.linkedin.com/company/amazon/
`pagination_token`	No	Required when fetching the next result page. Please use the token from the result of your previous call.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Sep 4, 2026

TDQS

D1.4/5.0

Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only states '2 credits per call.' It does not mention pagination behavior, required tokens, data returned, or any operational 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.

Conciseness2/5

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

The text is short but not usefully concise—it is severely under-specified. The only sentence ('2 credits per call.') does not help an agent understand or invoke the tool.

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

Completeness1/5

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

The tool has four parameters, no annotations, and no output schema, yet the description provides no functional context. An agent cannot determine what data this returns, how to chain pagination, or how it differs from sibling post-related tools.

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 each parameter already has a description. The tool description adds no parameter-level meaning, but the schema largely compensates, meeting the baseline.

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

Purpose1/5

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

The description is '2 credits per call.' and contains no verb or resource indicating what the tool does. The name 'get_companys_posts' implies fetching a company's posts, but the description itself provides no purpose statement.

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

Usage Guidelines1/5

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

No guidance is given about when to use this tool versus alternatives such as search_posts, get_profiles_posts, or get_post_details. The description only mentions credit cost and provides no context for selection.

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

Deploy Server