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HasData

Glassdoor MCP Server

glassdoor_listing: GET /

hasdata_glassdoor_listing_getJobListings

Search Glassdoor job listings by keyword and location to retrieve structured job data including salaries, employer ratings, and paginated results.

Instructions

Get GlassDoor Job Listings

Searches Glassdoor job listings by keyword and location with sort (recent/relevant), domain targeting, and nextPageToken pagination. Returns an array of jobs with title, company, location, salary estimate, posted date, job URL, and jobId, plus the next page token. Use to build job feeds, monitor hiring trends for roles/companies/regions, power candidate sourcing tools, and collect URLs for downstream full-detail scraping via the Glassdoor Job endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoThe sorting option for the search results.
domainNoThe domain of the Glassdoor site (optional).
keywordYesThe keyword used to search for job listings.
locationYesThe location to search for job listings.
nextPageTokenNoToken for fetching the next page of jobs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the burden. It discloses the return structure (array of jobs with specific fields and next page token) and pagination behavior. It does not mention authentication or rate limits, but for a read-only search tool this is acceptable; the description is not misleading.

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?

Three sentences, front-loaded with the core action and scoping. The return fields and use cases are listed efficiently with no filler. Each sentence earns its place.

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 no output schema, the description compensates by explaining the return array and pagination token. It covers purpose, usage, and routing to the details endpoint. It doesn't describe how to chain nextPageToken, but that's a minor gap given the clarity of the rest.

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 the baseline is 3. The description merely echoes the parameters (sort, domain, nextPageToken) without adding new semantics or usage details beyond what the schema already states.

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?

Clearly identifies the resource (Glassdoor job listings) and action (get/search). It distinguishes from the sibling details endpoint by mentioning 'downstream full-detail scraping via the Glassdoor Job endpoint', and from other platforms (Indeed, etc.) by naming Glassdoor explicitly.

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?

States explicit use cases ('build job feeds, monitor hiring trends...') and points to the alternative for full details ('collect URLs for downstream full-detail scraping via the Glassdoor Job endpoint'). This gives clear when-to-use and when-not-to-use guidance.

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