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LinkMCP: hosted LinkedIn MCP server

Get Company Posts

linkedin_get_company_posts
Read-onlyIdempotent

Get a company's recent LinkedIn posts by company URL, slug, or numeric ID. Returns up to ~30 posts with text, engagement counts, and post URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoContinuation cursor from a previous call. Pass this to fetch the next batch of posts.
identifierYesLinkedIn company URL (e.g. https://www.linkedin.com/company/acme), company slug (e.g. "acme"), or numeric ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower. The description still adds real value by disclosing the ~30-post cap per call and roughly what each post contains (text, engagement counts, URL), which matters because there is no output schema to fall back on.

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?

Two sentences, no filler, and the core action and identifier forms are front-loaded before the return summary. Every clause carries information.

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?

With no output schema, the description does the necessary minimum by sketching the return shape and the per-call cap. Pagination is handled by the cursor field's own schema text, so the remaining gap is only the absence of explicit sibling routing.

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 coverage is 100%, so the schema already documents both parameters in detail. The description restates the three accepted identifier formats, which duplicates the identifier field's schema text without adding syntax or validation nuance, and it never mentions the cursor parameter.

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 gives a specific verb and resource ('Get a company's recent LinkedIn posts') plus the identifier forms accepted, which is far more than a restated title. It stops short of explicitly distinguishing itself from the closest siblings (linkedin_get_person_posts, linkedin_get_company), leaving that inference to the agent.

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 when-to-use or when-not-to-use guidance, and no named alternative. The agent must infer from the name alone that company posts are not person posts and that linkedin_get_company is the route for company metadata rather than content.

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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