Skip to main content
Glama

Greenhouse

by io.github.pipeworx-io

Greenhouse Get Job

greenhouse_get_job
Read-onlyIdempotent

Get complete job details by ID. Returns description, requirements, hiring team, and linked applications.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesJob ID
_apiKeyYesGreenhouse Harvest API key

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoJob ID
titleNoJob title
statusNoJob status
departmentNoDepartment name
descriptionNoFull job description
hiring_teamNoMembers of hiring team
applicationsNoLinked applications for this job
requirementsNoJob requirements

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Complete job posting with description, requirements, and applications",
+  "properties": {
+    "applications": {
+      "description": "Linked applications for this job",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "department": {
+      "description": "Department name",
+      "type": "string"
+    },
+    "description": {
+      "description": "Full job description",
+      "type": "string"
+    },
+    "hiring_team": {
+      "description": "Members of hiring team",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "id": {
+      "description": "Job ID",
+      "type": "number"
+    },
+    "requirements": {
+      "description": "Job requirements",
+      "type": "string"
+    },
+    "status": {
+      "description": "Job status",
+      "type": "string"
+    },
+    "title": {
+      "description": "Job title",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-greenhouse-api-key",
+    "id": 54321
+  }
+]
  3. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to reiterate safety. It adds value by specifying the return content, but does not disclose additional behavioral traits such as rate limits or auth details beyond the schema.

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 that is front-loaded with the main action, using active verb and concise wording. No superfluous content.

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

Completeness5/5

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

For a simple read tool with complete annotations and an output schema, the description adequately covers the purpose and return values. No gaps in context for an agent to understand and invoke 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?

The input schema has 100% coverage with clear descriptions for both parameters (id and _apiKey). The description does not add further meaning beyond what the schema already provides.

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 clearly states the verb 'Get' and resource 'job', and specifies the returned fields (description, requirements, hiring team, linked applications). It distinguishes from sibling 'greenhouse_list_jobs' which lists jobs rather than retrieving details.

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

Usage Guidelines3/5

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

The description implies usage when a specific job ID is available and full details are needed, but does not explicitly state when to use it versus alternatives like 'greenhouse_list_jobs' or other tools. No exclusions or context are provided.

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

All Greenhouse toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes with detailed descriptions, but some overlap exists between research tools like ask_pipeworx, deep_research, and bet_research, which could confuse an agent. The Greenhouse-specific tools are clearly separated by the 'greenhouse_' prefix, aiding disambiguation.

Naming Consistency3/5

Tool names follow snake_case but vary in style: some have a prefix like 'greenhouse_' or 'pipeworx_', others do not (e.g., ask_pipeworx vs. deep_research). The verb-object pattern is inconsistent (e.g., 'generate_llms_txt' vs. 'entity_profile'), making naming less predictable.

Tool Count2/5

35 tools is excessive for a single server, especially one named 'Greenhouse' which implies an ATS focus. The set aggregates multiple domains (ATS, data research, memory, prediction markets) without clear scoping, overwhelming the agent and reducing coherence.

Completeness3/5

The Pipeworx/data research subset is fairly complete with lookups, comparisons, verification, and subscriptions. However, the Greenhouse ATS subset lacks create/update/delete operations, leaving notable gaps. The mixed domains make overall completeness uneven.

Resources