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LinkMCP: hosted LinkedIn MCP server

Get LinkedIn Job

linkedin_get_job
Read-onlyIdempotent

Get one LinkedIn job posting by its URL or job ID. Returns the title, company, location, work type (remote, hybrid or on-site), job type, experience level, posted date, number of applicants, the full job description, how to apply, and the hiring team (the people who posted the job, with their LinkedIn profile URLs) when LinkedIn shows them. Fields that LinkedIn does not show for a job are null. Get job URLs from linkedin_search_jobs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobYesThe LinkedIn job URL (e.g. https://www.linkedin.com/jobs/view/4012345678) or the numeric job ID (e.g. "4012345678").

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
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). The description adds behavior the annotations cannot: null for fields LinkedIn does not expose, and that the hiring team is included only 'when LinkedIn shows them'. Useful but not exhaustive about failure modes (e.g. invalid ID or private job).

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

Conciseness4/5

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

Three sentences, front-loaded with the core action before the return-field detail. The middle return-value sentence is long but every clause maps to a distinct output field, so little is wasted.

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

Completeness5/5

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

With no output schema, the description carries the full burden of describing returns, and it enumerates them thoroughly (job fields, apply info, hiring team with profile URLs) plus the null-handling rule. Nothing an agent needs to call or interpret this tool is missing.

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% and already documents the 'job' parameter with URL and numeric-ID examples. The description restates the same URL-or-ID duality without adding format, validation, or normalization semantics, 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 one LinkedIn job posting') and the exact input forms (URL or job ID). The closing pointer to linkedin_search_jobs distinguishes it from the sibling search tool, so an agent can tell get-one from search-many without opening schemas.

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?

Explicitly says where to obtain valid inputs ('Get job URLs from linkedin_search_jobs'), which routes the agent to the alternative for discovery. It does not state when-not to use it, but the get-vs-search context is clear.

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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