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LinkMCP: hosted LinkedIn MCP server

Search LinkedIn Jobs

linkedin_search_jobs
Read-onlyIdempotent

Search open LinkedIn job postings by keywords and/or a region. Returns each posting with its title, company (and company page), location, posted date, and a link to the job. A location value (e.g., "Slovenia", "Berlin") is resolved to a LinkedIn region automatically. Useful for sourcing open roles or tracking hiring activity in a market. Pass the returned cursor to page through more results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoPagination cursor from a previous response. Pass this to fetch the next page of results.
keywordsNoJob search keywords (e.g., "software engineer", "sales manager").
locationNoRegion or location to search in (e.g., "Slovenia", "London"). Resolved to a LinkedIn region automatically.

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 read-only, idempotent, open-world behavior, so the safety profile is covered. The description adds genuinely useful traits beyond that: the automatic resolution of a free-text location to a LinkedIn region, the set of fields each posting carries, and the cursor-based paging mechanism.

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?

Four short sentences, front-loaded with the core action and return shape, with usage and pagination last. Tight overall, though the location-resolution and cursor sentences duplicate schema content.

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?

There is no output schema, yet the description enumerates the returned posting fields, so an agent knows what it will get back. All three optional parameters are covered and pagination is explained, leaving no practical gap for invoking the 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 description coverage is 100%, so all three parameters are fully documented in the schema. The description's mentions of location resolution and cursor paging restate what the schema already says rather than adding syntax, defaults, or constraints.

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 ('Search open LinkedIn job postings') plus the two filtering dimensions, which cleanly separates it from linkedin_search_people and linkedin_search_sales_navigator. An agent can select it without opening the 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?

'Useful for sourcing open roles or tracking hiring activity in a market' gives clear usage context, but there is no explicit when-not guidance or named alternative among the many sibling search tools. It stops short of routing the agent between options.

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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