Skip to main content
Glama
rasmuslinkin

ActiveVacancies MCP Server

by rasmuslinkin

search_jobs

Find verified tech job postings from multiple platforms using filters for location, salary, remote status, employment type, and more.

Instructions

Search active, verified tech job postings across Greenhouse, Lever, Ashby, and Workable with multi-parameter filtering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (1-indexed)
limitNoNumber of listings to return (1-50, default 15)
queryNoKeywords matching job title, tech stack, or description (e.g. 'Senior TypeScript Engineer', 'Staff Kubernetes')
sort_byNoSorting strategy (recent or salary)recent
currencyNoISO currency code (e.g. USD, EUR, GBP)USD
locationNoCity, country, or region (e.g. 'Berlin', 'United States', 'EMEA')
min_salaryNoMinimum base annual salary in specified currency
company_slugNoFilter by specific company identifier (e.g. 'stripe', 'vercel')
remote_statusNoRemote work policy filterany
employment_typeNoEmployment type filterany

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds one meaningful fact: results are pre-filtered to 'active, verified' postings, which is genuinely useful and not derivable from the schema. However, it omits pagination behavior (page/limit exist in the schema but response pagination is unmentioned), rate limits, and any note about the response format. Partial coverage of behavior only.

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?

A single sentence with zero wasted words. The core action and resource are front-loaded, the ATS sources are named compactly, and the filtering capability is stated last. Every clause earns its place; nothing is redundant or padded.

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

Completeness2/5

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

This is a complex tool with 10 parameters, multi-source aggregation, no output schema, and no annotations, yet the description is minimal. It does not explain that results are paginated, what the response structure looks like (critical given there is no output schema), whether salary sorting requires a matching currency, or how filters combine. For a tool of this complexity, the description falls well short of what an agent needs to use it correctly.

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% with rich parameter descriptions and concrete examples ('Senior TypeScript Engineer', 'stripe', 'Berlin'). The description itself adds nothing about parameters beyond the phrase 'multi-parameter filtering,' so the baseline of 3 applies since the schema is doing the heavy lifting. No compensation is needed because the schema already documents all parameters well.

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 uses a specific verb ('Search') and resource ('active, verified tech job postings'), and names the four aggregated ATS sources (Greenhouse, Lever, Ashby, Workable). This clearly differentiates it from siblings like get_job_details (single-job detail lookup), list_companies, and match_resume_to_jobs (resume-driven matching), so an agent can tell this is the general multi-source job search.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus its siblings. It never mentions that get_job_details should follow a search result to fetch full details, that list_companies provides the company_slug values, or that match_resume_to_jobs is the alternative when a resume is available. The agent is left to infer routing entirely from the schema and tool names.

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