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LinkedIn MCP Server (Salesbot)

by cz.salesbot

search_job_postings

Read-only

Search LinkedIn job postings by keywords, location, seniority, job type, and more. Returns job offers with company info — great for finding companies that are actively hiring for a specific role. Uses the connected LinkedIn account (Classic search, no Recruiter needed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (1-50, default 10)
job_typeNoJob type filter. Optional.
keywordsYesJob title or keywords to search for (e.g. 'Sales Manager', 'frontend developer')
locationNoHuman-readable location (e.g. 'Praha', 'Brno', 'Berlin'). Resolved to LinkedIn geo ID automatically.
presenceNoWorkplace type filter. Optional.
seniorityNoExperience level filter. Optional.
easy_applyNoFilter to Easy Apply jobs only. Optional.
locationIdNoRaw LinkedIn location ID. Use this OR location.
date_postedNoOnly jobs posted within this many days (e.g. 7 for last week). Optional.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description adds value by specifying that it uses the connected LinkedIn account and performs a classic search. No contradictions.

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?

The description is concise (two sentences), front-loaded with the core purpose, and includes a helpful benefit statement. No wasted words.

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?

The tool has 9 parameters (1 required) and no output schema. The description mentions return of job offers with company info but lacks details on pagination or response structure. However, given the annotations and schema coverage, it is largely complete.

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?

The input schema has 100% description coverage for all 9 parameters. The description provides a high-level summary of filter types but does not add significant detail beyond the schema. Baseline of 3 is appropriate.

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?

The description explicitly states the tool searches LinkedIn job postings with various filters and returns job offers with company info. It clearly distinguishes from sibling tools like search_linkedin_people and search_linkedin_navigator by focusing on job postings.

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?

The description provides context on when to use the tool (finding actively hiring companies) and notes the account requirements (Classic search, no Recruiter needed). It does not explicitly mention when not to use it, but the context is clear given the sibling tools.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap among search tools (search_job_postings, search_google_xray, search_linkedin_people, search_web) and messaging tools (send_connection_request, send_linkedin_message, reply_to_chat). However, detailed descriptions clarify the differences.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (e.g., add_contacts_to_campaign, list_campaigns). No mixing of conventions.

Tool Count3/5

48 tools is high but justifiable given the broad domain (LinkedIn outreach, CRM, campaigns, job postings, etc.). However, some tools could be consolidated (e.g., multiple search tools).

Completeness5/5

The tool set covers the entire workflow: searching, connecting, messaging, campaign management, CRM operations (fields, stages, tasks, notes), job postings, and posting. No obvious gaps.

Resources