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LinkMCP: hosted LinkedIn MCP server

Get Person Posts

linkedin_get_person_posts
Read-onlyIdempotent

Get a person's recent LinkedIn posts by profile URL, public ID (slug), or URN. Returns up to ~50 posts with text, engagement counts, and post URL. Use this to see what a prospect or a candidate posts about. For a company's posts, use linkedin_get_company_posts.

Input Schema

NameRequiredDescriptionDefault
cursorNoContinuation cursor from a previous call. Pass this to fetch the next batch of posts.
identifierYesLinkedIn profile URL (e.g. https://www.linkedin.com/in/john-doe), public ID / slug (e.g. "john-doe"), or URN (e.g. "urn:li:fsd_profile:ABC123").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety behavior is covered. The description adds real value beyond them by disclosing the result shape and volume cap (~50 posts with text, engagement counts, post URL), which matters since there is no output schema. Rate limits or behavior on private/invalid profiles are not mentioned.

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?

Three tight sentences: capability and identifier forms first, return shape second, disambiguation last. No filler and nothing buried.

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 usefully covers what comes back and the rough page size, and the schema covers pagination. Handling of private profiles, invalid identifiers, or rate limits is left unstated, which is the only real gap for a two-parameter read tool.

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% and the schema already documents both the identifier formats and the cursor continuation semantics. The description's enumeration of URL/slug/URN duplicates the schema rather than extending it, so baseline 3 applies.

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?

States a specific verb and resource (get a person's recent posts) and enumerates the accepted identifier forms. It also explicitly separates itself from the sibling company-posts tool, so an agent can pick correctly without opening either schema.

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

Usage Guidelines4/5

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

Gives a concrete use case ('see what a prospect or a candidate posts about') and names the alternative for companies. It does not address the other plausible alternative, linkedin_search_posts, so the routing story is clear but not exhaustive.

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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