Skip to main content
Glama
BACH-AI-Tools

LinkedIn Data API MCP Server

search_jobs_v2

Search LinkedIn jobs with filters for keywords, location, company, salary, job type, experience level, date posted, remote/onsite, and more. Sort by relevance or recency to find suitable positions.

Instructions

Search Jobs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYesExample value: golang
locationIdNoplease follow this link to find location id92000000
companyIdsNoplease follow this link to find company id
datePostedNoit could be one of these; anyTime, pastMonth, pastWeek, past24Hours
salaryNoit could be one of these; 40k+, 60k+, 80k+, 100k+, 120k+, 140k+, 160k+, 180k+, 200k+ Example: 80k+
jobTypeNoit could be one of these; fullTime, partTime, contract, internship Example: contract
experienceLevelNoit could be one of these; internship, associate, director, entryLevel, midSeniorLevel. executive example: executive
titleIdsNoplease follow this link to find title id by title
functionIdsNoplease follow this link to find function id
startNoit could be one of these; 0, 50, 100, 150, 200, etc. The maximum number of start is 975
industryIdsNoplease follow this link to find industry id
onsiteRemoteNoit could be one of these; onSite remote hybrid example: remote
sortNoit could be one of these; mostRelevant, mostRecent
distanceNo0 = 0km 5 = 8km 10 = 16km 25 = 40km 50 = 80km 100 = 160km
Behavior1/5

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

No annotations are provided, and the description does not disclose any behavioral traits (e.g., rate limits, pagination, data freshness). The burden is entirely on the description, which is empty of such details.

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

Conciseness2/5

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

The description is extremely concise but under-specified. It sacrifices informativeness for brevity, making it inadequate.

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

Completeness1/5

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

Given the complexity (14 parameters, no output schema) and the number of sibling search tools, the description is completely insufficient. It does not explain output, pagination, or filtering behavior.

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 baseline is 3. The tool description does not add any additional meaning beyond what the parameter descriptions already provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Search Jobs' is a tautology of the tool name and does not specify the verb, resource, or scope. It fails to distinguish this tool from siblings like 'search_jobs'.

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

Usage Guidelines1/5

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

No guidance on when to use this tool versus alternatives such as 'search_jobs' or 'get_company_jobs'. The description provides no context for selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BACH-AI-Tools/bachai-linkedin-data-api'

If you have feedback or need assistance with the MCP directory API, please join our Discord server