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HasData

Glassdoor MCP Server

glassdoor_job: GET /

hasdata_glassdoor_job_getJobDetails

Fetches complete Glassdoor job posting from a vacancy URL, including title, company, salary, employment type, description, and apply link, to support ATS ingestion and job-data enrichment.

Instructions

Get GlassDoor Job Details

Fetches a Glassdoor job posting by its vacancy URL. Returns job title, company name and rating, location, salary estimate, employment type, posted date, full job description, qualifications/benefits, and apply link. Use for ATS ingestion, job aggregators, comp benchmarking, enrichment of company profiles, and feeding descriptions into LLM matching or resume-tailoring pipelines.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL of the job vacancy to retrieve details for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the burden of explaining behavior. It does list the returned fields and suggests practical use cases, but it does not mention potential limitations, error behavior, authentication, or rate limits. This is adequate for a simple fetch operation but not fully transparent.

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?

The description is reasonably concise and well-structured: a clear action sentence, a list of returned fields, and a list of use cases. The use-case list is somewhat broad but not excessive, and every sentence contributes useful context.

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?

For a single-parameter tool with no output schema, the description gives enough context to invoke it correctly: what URL to provide, what data will be returned, and common scenarios where it is useful. It does not overpromise or omit critical invocation details.

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 only parameter, 'url', is fully described in the schema as 'The URL of the job vacancy to retrieve details for.' The tool description largely repeats this and adds no new parameter-level details, so the description adds minimal value 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 the specific action ('Fetches a Glassdoor job posting by its vacancy URL'), the resource (Glassdoor job posting), and the scope (details by URL). This clearly distinguishes it from the sibling listing tool and other job detail tools.

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 explains when to use the tool ('by its vacancy URL') and lists relevant use cases such as ATS ingestion, job aggregation, and LLM matching. It does not explicitly name the alternative listing tool or say 'use this when you already have a URL', but the condition is strongly implied.

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