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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.

Input Schema

TableJSON 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

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the return shape (~50 posts with text, engagement, URL), which matters since there is no output schema, but it says nothing about auth requirements, rate limits, or pagination behavior beyond the schema's cursor.

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 tightly written sentences: the action and accepted inputs come first, the return shape second. No filler and nothing that could be cut.

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?

For a read-only lookup with no output schema, the description covers the input forms and the essential return contents, and annotations carry the safety profile. Pagination semantics are only implied by the cursor parameter, leaving a small gap.

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 both parameters are already well documented. The description repeats the identifier forms (URL, public ID, URN) without adding format or constraint detail beyond the schema, so the baseline 3 is appropriate.

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?

States a specific verb and resource ('get a person's recent LinkedIn posts') and the accepted identifier forms, which implicitly distinguishes it from the company-posts sibling. It stops short of naming that sibling or otherwise routing the agent, but the purpose is unambiguous.

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 when-to-use, prerequisite, or alternative guidance is given. Nothing tells the agent how this differs from linkedin_get_profile or linkedin_get_company_posts, or when this tool is the right choice over general profile retrieval.

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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