LinkBridge MCP

Search Posts

search_posts

Read-only

Find LinkedIn posts globally by keyword to catch informal hiring signals before formal job listings appear.

Instructions

Search LinkedIn posts/content globally by keyword (the "Posts" tab).

Use this to catch informal hiring posts ("we're hiring", "Buscamos ...", "estamos contratando", "join our team") that often appear before a formal job listing exists. This is global content search, distinct from get_feed (your own home feed) and get_company_posts (one company's page).

Input Schema

Name	Required	Description
`keywords`	Yes	Search keywords (e.g., "Buscamos Unity", "AI automation hiring")
`max_pages`	No	Scroll depth as result "pages" of ~5 scrolls each (1-10, default 3). Content search is an infinite scroll, so this caps how far the page is scrolled rather than fetching discrete pages.
`date_posted`	No	Optional recency filter. One of "past-24h", "past-week", "past-month"; the "past_24_hours" / "past_week" / "past_month" spellings used by search_jobs are accepted too. Omit for any time.
`content_type`	No	Optional "Content type" filter. One of "documents" (PDFs and slide decks people upload), "images", "videos", "live_videos", "job_posts". Omit for all posts.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv4.29.0Nov 5, 2026

TDQS

A4.1/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety and reach profile is covered. The description adds that results are an open global content search, but says nothing about result volume, pagination behavior, or rate limits beyond what the schema's max_pages note already provides.

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?

Front-loads the verb, resource, and scope in the first clause, then justifies the use case and the sibling distinctions. Every sentence earns its place; only minor tightening is possible.

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 an output schema, full schema coverage, and read-only/open-world annotations, the description covers what an agent needs to select the tool. It could be richer about expected result volume for a scroll-based search, but nothing essential to correct invocation 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%, including enum-like values for date_posted and content_type and the infinite-scroll semantics of max_pages, so the schema carries the parameter burden. The description adds no keyword syntax, quoting, or filtering guidance beyond the schema.

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 LinkedIn posts/content") plus the scope "globally by keyword" and identifies the UI counterpart (the "Posts" tab). An agent can distinguish this from get_feed and get_company_posts purely from the description.

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

Usage Guidelines5/5

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

Gives an explicit use case (catching informal hiring posts before a formal listing exists) and names two alternatives with the condition that selects against them: get_feed for your own home feed and get_company_posts for a single company's page. Nothing about routing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.